With rollback finally dropping in Dragon Ball fighters, I am super happy to finally be coming back to the game, but I'm extremely rusty. Yeah, the long wait waiting for that netco patch did not help the old fighters' skills, and now in these right patches you're about to see, I'm experiencing all of the consequences of my decision to wait for rollback to be added to the game. All I do is mix featuring Kojito, Vegeta, and Broly. Yeah, I'm cooked. Man, I just did my intro about how I was so happy and addicted to rollback, and bro, now I'm gonna get cooked. Oh, and it's Pink Kojito, bro. Pink Kojitas don't mess around, man. Rock assist. Oh, wait, never mind. Hold on, maybe I'm hit. Wait, where'd my confidence go? Ah, there it goes. I actually, I saw it leave my body just then. Never mind. Never mind. Wait a minute. Wait a minute. Maybe I've been, I've been too hard on myself. Standard knockdown procedure. Rock assist. If I get hit by DP one more time, I think I just gotta consider the option that I might be washed. Oh, so you knew I was gonna reflect. You knew I wanted it, and you took that option from me. Nice combo. Get off me. Yeah, I'm gonna stick. Oh, so you knew I was gonna mash. Ah, this guy's in my head. He knows every option I'm looking for. All right, hold on. I kind of want to spark because this is, this is supposed to be my Super Saiyan Goku outing, bro. What?  That jump was crazy. The float was crazy. It put too much pressure on me. All right, Broly combos. I should be dead here, but maybe he wants to spare me. I mean, if he wants to spare me, I'm totally open to that. I think I'm dead. I know I'm dead. Ah, so, damn. Well, I understand. I understand. Look, we got his spark. I could have played way better. We had a few openings. I think it really was that confidence that was getting me down. So let me just inject a little confidence into the, wow, he could have, he could have finished my entire family history with that one. Damn. That was nice. This should be his death though. All right, come on. There we go. That, that's death. Come on. You know, I count the numbers out precisely. You know, I had just the right amount of meter to get that going. I'm going to take that. All right, two, two. Honestly, the character lead is barely there, if they're at all. There we go. Get them off me. Good reflect. We love to play defense, especially in rollback. Rock assist, not going to work. Oh, but can he handle the, oh no, he couldn't. I didn't even get to the option mix. The mix was no mix. All right, standard knockdown. I'm going to take his level one just because he is a little far. Damn, I got rid of Broly too. I even checked him with a jab, but I just couldn't get rid of Vegeta. Checking Broly assist with a jab is actually really strong. Gets rid of that assist and then we're just free to play. Sadly, I forgot to play. No reflect here. Nice defense. Oh, crouch me. Just stay crouching. Why are we not crouching? Broly been playing too much Tekken. I got to remember to just crouch, take the beating and move on. Oh, oh. Damn, I'm dead. All right, y'all just kind of got tossed around. I'm not even, I'm not even going to lie. The combo is a bit aggressive visually. All right, well, there's the character lead is definitely back. Oh, you got hit by that. I honestly was just throwing that out as a final piece, but I'll take that. All right, no, no need to waste another bar with the level one and three. I'll just take the three. I think we go high here. Whoa, look at that Krillin Nuch. The Krillin neutral. One more. Oh, just the one Destructo disc. We're so back. We are so back. All we have to do is beat Limit Break Vegeta with six bars. Oh man, I didn't beat Limit Break Vegeta with seven bars. I think he just kills us here. But I could be, I could be gassing him up because he's going to level one. No, just level, level five. It's a level five. He didn't even use the level five. The pressure was too much for my little spirit, bro. My, my, whoa, whoa, whoa. All right, all right. That was only game one. That's game one. I need to warm up. I needed to warm up. I needed to warm up because what did my Goku really do that set? If we're being honest, nothing. All right, good. Glad we all agree that he did nothing. But now my Goku is going to step it up. My Goku is going to be clutch. And then I'm going to get a Broly dramatic finish. I actually know that's not on this stage, huh? There we go. I told you. I told you my Goku is going to be a little different today. This round is not last round. I'll tell you that right now. Oh, wow. He checked me pretty bad. Oh, I'll take that. I'll take that. I'm just looking for the damage here. Big time. Let's get a rock assist out here. Rock assist was so clutch into level one by Goku. Please be enough to kill. Yes. Yes. That was perfect. My life is still green. I haven't been touched. How did that not work? Oh, my goodness. Come here. Rock assist into the oaky on the ground. Yamcha is just waiting. Let's go. Let's go. That's what I want to see. Oh, hold on. I told you I was going to be a little different. I told you you were going to have to fear me. Oh, I should have known he was getting nervous. Of course, he would start squirming. Who wouldn't squirm when they could feel the overwhelming might of Super Saiyan Goku? All right. I'm going a little... All right, let's go. Back dash. Oh, yeah. I was mashing Vanish. Yeah, I was. And you know what? I'll tell the truth. I don't care. I do it again. It got me looking like the Punisher on the stand, man. I'm inching a Vanish. Okay. Hold on. Oh, put the Goku down. I miss my guard cancel. And now I die. Oh, come on, bro.  You ain't never had to. Damn it. Bro is allergic to combos under four minutes. I think that might just be Broly. I'm saying that like I wouldn't do combos that were longer than four minutes if I could. Oh, big mistake. You let me escape. Mix up. Oh, I should have held it. I mean, I shouldn't have not held it. I should have let it rock. All right. So the crump, the fumble has been immaculate. We've definitely fumbled our. I'm just going to guard cancel. Ah, you never guard cancel on that, bro. You never guard cancel on that. All right. I got to calm myself, center myself, find myself. I got to have a whole therapy session with myself, by myself. It's never, it's never looked so bad, bro. 63 hits, bro. Looking like Neji Huyga in his prime in every Naruto game. I'll command grab. But oh, you can combo up that. All right. All right. Krillin has won these matches before. Let's go. And just like that, welcome to Dragon Ball Fighters, bro. Because it is now a 1v1. I probably should have just kept the destructive just going. Damn. Remember how I couldn't beat Vigino? Now I have to beat Broly with Spark. That's why this team is dead. Oh, get off me. Oh, let's go. Ah, how does that still hit me? I threw out one tiny jet. Oh, look at this guy. Whoa, how did that hit him? Oh, it's cooked. It's cooked. Drop it. Drop it. Drop it. Drop it. Drop it. Please. Yes. And now it's over. You just made your last mistake, buddy. Get off me. Guard cancel that. Let's go. Super armor. Can I get a rematch? Hey, hey, Dragon Ball Fighters, if there's any justice in the post-rollback world, please, please match this up again. Great games. Great games. Let me get that run back, though. All right. We didn't get the rematch, but it is another Angel Ranks. Oh, that Vegeta color kind of goes great. Wait, hold on. That Vegeta color kind of crazy. Dragon Rush. I should have known on rollback you're taking that, bro. Oh, this is just Goku and Vegeta right now. Oh, he's him. No, wait, how did I get hit by that? We overplayed a bit of a scramble game here. Oh, no, Dragon Rush. This time, this is Dragon Ball Fighters right now. I'm having a great game. All right. All right. Keep them under pressure, though. Oh, the range on that low was crazy. You got the loops. You got the loops. The loops. No, I think we're good. Charge and then switch out just to keep Vegeta alive. Why cling to life when you could instead just fight? No mix ups, please. Oh, the run out of the corner was so quick. Oh, what are you doing? How did Cell find me there post vanish? Bro, track me down. He can see what others can't. All right. So we lose Yamcha, which is a pretty big blow to our game plan against this guy. All right. I'll take advantage there. I'm not going to superdash that. Wow. This is a game right here, folks. This is a game. Okay. I don't know that I need to learn the curl. Bro, I need to learn the new Krillin routes, man. I need to learn the new Krillin routes. Okay. I was going for old stuff. I was going for old stuff mixed with new stuff and you can't do that. I understand. I understand. I have to learn new Krillin routes. I totally get that. Totally. That's totally valid. But now that I admit that mistake, let me out of the corner. Let me out of the corner. That's all I ask. Oh, I definitely tech that. I definitely tech that. Let's just call it what it is. I forgot that's a mix. I forget that that goes side to side. That's so random. All right. So now it's Goku alone, bro. Looking like one of the greater, the better avatar episodes. All right. Level three to keep corner. Level three. Keep corner though. I've got to go through three guys, bro. Three guys. Hey, these are all villains. Goku is far though. All right. You can reflect that. But I have to play better defense than that. I got to play better defense than that, man. Down tech. Always be down teching. Always be up teching. That command grab was fast. I'm not going for any special combo. You got to be crazy if you think I'm trying to combo in this atmosphere. Hopefully, level three is enough to kill. Limit break Super Saiyan 3 version. Yeah, we're killing, bro. Please. Oh my God. It had me nervous, Goku. You had me nervous. All right. Then a mix. Come on. Let's talk. I thought I blocked that. I thought I blocked that. Yes. I think a barrier would work. Let me get one more. Bro. Damn. I'm going up against. Bro. I got me warmed up, man. Now I got to get warmed up. Hold on. Let me. I know Goku can do this. I know Goku can do this. This isn't even a question on if Goku can do this. Hey, we blocked those. So the old classic six semi-options. That's what's going to get you, huh? I'm so tapped in. All right. I was trying to get it in the legal Super Dash reset. Wow. Nice conversion. That was pretty sick. That was pretty sick. I'll give it up. Damn. The loops. The loops. All right. Dude, I got caught jumping. No. No way. Goku can't go out like this. Okay. I'm just going to start the worst decisions ever made. The worst decisions of all time. Yes. Second chances. I love second chances, bro. I love second chances. He panicked. He wanted the kill. Just give me a level three, man. Just give me a level three. I don't care, bro. I don't care. I'm so pissed. I'm so pissed. I have to get a run going right now. No. All right. Let's go real slow. Let's get this spark out of here. Actually, man, I'm just going to hit you with another level three. My bad. My bad, bro. I'm so nervous. I knew it. I knew a barrier. I didn't even say it on the video because I just didn't want it to happen. I didn't want there to be a barrier.  Wow. Nice 2H. That Super Dash was a little reckless. No. That was way too... Damn. Just always trying to get out of trouble, bro. Just set my feet. Play some goddamn defense. It might be too late to make that adjustment now. Oh. Genema in the corner is very frightening, though, because I'm not reacting to that grab. Damn. I just want to... I would do it so differently if I could do it again. If I could get another run back. Hey, Dragon Ball FighterZ, I know we didn't get the last run back, but... No. You know what? There's no need to ask for a run back when I'm still in the game. What are we doing? For those still in the game, I don't need to ask for a run back. Oh, that is crazy that you can do that. That is crazy that you can do that, bro. That is... This should be illegal. All right. Just get me out. I'd switch to low gorilla. Drop it. Drop it. I don't think there's going to be a drop. Come on.  There used to be three... In the last update, we couldn't do three matches. We couldn't go back to up to three rematches. All right. Final set of the video. I didn't get a run back with either, but we're going up against a Videl and UI Goku. So that alone is pretty interesting. Damn. I've been playing terrible today, man. And the worst is it hasn't even been like super terrible. Like just getting cooked. Oh, wow. Maybe it has been. Maybe that was a sobering realization. But I just got to... I got to get back in the fighter, man.  Why did I hit heavy? Oh, so you got the Videl loops. Dude, my decision making is terrible. Get Goku off my team. I got to learn Goku. Get Goku off my team for now, though. Never mind. Never mind. Never mind. He can stay. He can stay. He can stay. Let me just get a win. Let me get a win. Easy win coming up. Easy asterisk. Should have hit that DP because I'm going to keep mashing until one of us is gone, bro. I'm just going to keep mashing. I'm going to always mash. Krillin. Nice. We've got a character lead. Now, yes, we're low on sparking. But that doesn't matter. It's all about the character lead. I keep the pressure on. I keep the pressure on. Hey, take this level three real quick. Hold this level three, you, Goku. Don't do anything crazy. Oh, whoa, whoa, whoa, bro. Bro, it's supposed to be doing that no more. That was crazy. Hold drop, bro. The rollback was trying to decide if I could keep my combo or not. And Jiren. You could just wait right there, Jiren. I'll be there in a second. I'll be there in a second, Jiren. Say I'm waiting again. Rock.  I don't know why that was so funny to me. It looked like it actually hit him. Like that was in a programmed in animation. That was just like the character reacting to pain. Oh, wow. All right, I could have done so much better. I could have done so much better in the corner, but all you can get is level three. I'm living this honestly with the scaling and how tough Krillin is. That's a live. Easy. Mash it, mash it, mash it, mash it. Bend the beam back. I've heard of safe jumps, but have you heard of bending beams? Coward. Okay. So yeah, I wasted three bars. Yeah. I wasted three bars. What about it though? Damn. God, God. Damn. You're going to hit me hard. Okay. I can't. I don't want to fumble this game, man. I can't believe I just let Goku get beat up that bad. Oh, starting to get a bit nervous there. I'm not. Can't lie. I was starting to get a tad bit nervous. Let me get this level three real quick. Same side super same three level three. Little known Tekka's Yamcha Goku players know about. Can't even confirm off the ground. Oh, I guess you can in this environment. I can't fumble like this. I really thought Yamcha was going to hit. So I, ah, ah, no, ah, no. Dude, this is the fumbling episode. He didn't level one to three. He forgot about the system mechanics. This guy's been playing Dragon Ball fighters for years. Leave it. Oh God. But now what I do? Now what I do? Oh no, I knew you. I knew you. I am you. Funny little command grab. You thought I was going to be so nervous that I wouldn't react to it. Yeah. I know who you are, buddy. I've been you a few times in my life. Well, that honestly, the end of that game does not bode well for this game. I'm going to be honest. He has all the momentum. He might have lost, but he has all the momentum in the world. I'm just coming down. Put me down, bro. The PC streets is getting me today. Whoa, whoa, whoa, whoa, whoa, whoa, whoa, whoa, whoa, whoa. What's this lag about? Hold on. Hold on. Damn, two rocks in the back of the head is crazy. I hope this works. All right, good. Damn, that was a lot of damage. Why did that health bar look like it was melting off? I just need to play more patient, man. Why am I always trying to force things? There isn't been one situation today where I've been like, all right. Well, there was in the beginning of the first set of today. I, you know, I felt we were playing decent Dragon Ball fighters, but ever since then I've lost it.  Oh, the drops and the resets. And it's actually just a reset now. Yeah, look it up in the fighting game terminology book, bro. It went to a drop to a reset. It's true. All right. All right. A little comment. A little comment. A little comment. I can't speak. Get off me. It's always with this Jirid, man. This Jirid is always cooking me. Oh, see, I'm not falling for that no more, especially in the corner, honestly. Solar flare. Yes. Solar flare is so cheap. Anti air super fast. I'll take it every day. All right. I sit there. Watch this 2M. All right. But I'm all the way up here.  I'm still nervous. I'm going to fail, bro. I'm still nervous. I'm going to lose, man. Oh, wow. That 2M was risky. That 2M was brazen. I'm a bad man. I'm a Maverick. Well, that was actually just me dropping the combo, but it worked out GG's. Well played. Hopefully everybody enjoyed our time here tonight, folks, because honestly, the game might not be over. I might have spoken a little too soon.  All by Kamehameha. All by an instant transmission. Kamehameha behind his back. Yeah, I had to put him into dirt. Great games that everybody played today. I'm looking forward to all of our run backs. In fact, I need to run back with everybody. Hopefully you've enjoyed Dragon Ball FighterZ. Let me know some teams you want to see down below. Click on some videos on your screen, and I will see you in the next one. Bye.


Hello, my name is Jan Knodl. I'm the Extension Entomologist for North Dakota State University.  Sex pheromones are typically emitted by the female moth to attract the male moth for mating. Many of the pheromones have been identified for insect pests and are commercially available for pest monitoring. Pheromone traps can be used to detect early migrants that come up from the southern states, such as sunflower moth and sunflower and diamondback moth and canola. We also use pheromone traps for monitoring pest populations densities and also to define areas of infestation. In some instances, we can use pheromone traps to make management decisions, such as action thresholds. In this video, we will describe effective pheromone trapping and lure handling and also how to place your trap properly in the field. We will use banded sunflower moth and sunflower and birth armyworm and canola as examples. There are several different trap designs for various insect pests. The banded sunflower moth uses this wing styled pheromone trap with a sticky trap bottom that captures the insects. The birth armyworm uses a unibucket style of pheromone trap. Pheromone traps are typically placed close to the field edge for easy access for monitoring. When you place the trap in the field, make sure the entryways to the trap are not blocked with vegetation. You also want to place the trap on the windward side of the field so the pheromone is dissipated into the field. Wooded edges are not good trap sites because the pheromones will not dissipate over the field. If more than one trap is being placed at a field site, traps should be spaced at least 60 to 120 feet apart to avoid possible pheromone interference. The chemicals on the pheromone lures are real sensitive to high temperatures, so we recommend that you store the lures in the freezer. Keep them separated by each different insect. When you're ready to go to the field, take only the lures you need out. And place the lure in the cooler. And remember to put an ice pack in to keep the lure cold. And also your rubber gloves that you will need for handling the lure. Since vehicles can heat up quickly in the summer, use a small cooler with an ice pack to transfer the lures to the field. We recommend that you contact the pheromone manufacturer for the recommended interval of lure replacement in the field. For proper trap maintenance, we recommend that you service the trap at least once a week. This will prevent the trap from being overloaded with the targeted insect and make insect identification easier. To change the trap for the banded sunfire moth, we recommend that you just remove the old bottom and you can count the number of banded sunfire moths and record them on your trapping form. And then put in a new trap bottom. Before I fasten this bottom up, I'm going to change the lure. To change the lure, you need to wear rubber gloves so the oil from your skin does not contaminate the pheromone lure, which would interfere with the chemicals of the lure. So remove the old lure from the lure holder and get the new lure out and place the new lure into the holder. Put the old lure into the packet and then continue replacing the trap bottom because you want to avoid getting any of the chemical from the pheromone on the trap which might cause the targeted insect to be attracted to other areas of the trap rather than getting captured inside the trap bottom. When servicing the trap, be careful not to leave your gloves that you used for changing the pheromone lure or the pheromone lure in the old wrapper near the trap site because this could attract the targeted insect away from your trap. Now we're in the canola field and we're going to service the birth army worm trap. I have my gloves on ready to go to change the pheromone lure. The lure is contained in this upper basket in the trap. This is the old lure, the new lure which I removed from my cooler. The new lure out and you can just place the old lure back into the old wrapper. Put the new lure in and then snap it back onto the trap top. Remove your gloves before handling the trap to avoid the insect from being confused with pheromone lure on the outside of the trap. The moths are attracted to the pheromone and they'll fly into the trap and get down into the bottom of the trap where they become captured. And I've placed two red vipona strips which contains insecticide that kills the moths once they get down into the lower bucket. You can then place the moths that were captured from the previous week into a plastic bag. Take them back to the lab for identification and counting. And then put the trap bottom back on and you're ready for another trap week. When you're setting up the birth army worm pheromone trap be sure you put a little tie here to fasten it to the post so the trap does not swing in the wind. Information to record during each visit is shown in the sample field data sheet for pheromone trapping. Trap catches can also be graphed over time to easily show seasonal and year to year trends. Trap data from pheromone trapping networks can be mapped geographically using GPS coordinates illustrating pest populations across regions as shown in the Bandit Sunflower Moth map. I hope you enjoyed learning how to use pheromone traps for effective pest monitoring. Pheromone traps are relatively inexpensive, easy to use, and species specific. They make ideal tools of integrated pest management programs. Thanks and have a good day.


Once again Josh Reynolds makes our list why Cooper cup out from the season with a torn ACL Last time Cup was injured Josh Josh Reynolds did absolutely nothing the first week to touchdown scored the next week What can fantasy owners expect from Reynolds at this time around? I think we might expect some Inconsistency here, but we know that the Rams run a ton of three wide receiver sets and Josh Reynolds is the next man up Is he going to be Cooper cup per se for fantasy purposes? Absolutely not I think Brandon cooks and Robert would see an uptick in targets and consistency Josh Reynolds, you know, he's not going to be that top 20 that top 15 wide receiver that cup was But can he be a top 30 top 36 wide receiver in one of the most potent offenses in the NFL? I certainly do think that's possible per Adam Levitan on Twitter tweeted it this out Josh Reynolds The last time Cooper cup was out in two games played 120 of 129 possible snaps, but he only had 10% of the target share So he wasn't targeted all that much and maybe it's something that will develop over the second half of the season Because they don't really have a choice, right? So if he's on the field continues to develop that rapport with Jared Goff We know that Sean McVeigh is going to find creative ways to get Josh Reynolds the ball You look at his frame to Greg six three two hundred pounds He's a really big body who I think could be targeted in the red zone and utilized in that way You mentioned that game where he caught two touchdowns Maybe that's what we're looking at Josh Reynolds for not the safe floor Cooper cup type wide receiver that was in this Rams offense before which we could depend on for Six first 60 six for 70 whatever it might be But maybe he's the guy that's used more so in the red zone and scores touchdowns here So because Cooper Cubs out unfortunately, we have to look to Josh Reynolds who's the next man up in LA Reynolds is never going to get the target share that Cooper cup has because he just does not have the Relationship with Jerry got the Cooper cup has and also quite frankly. He's not as good So while Reynolds will be out there He won't be utilized near nearly as much so don't think you're getting Cooper cup We're picking up Josh Reynolds, but again six teams on a buy you are desperate for a flex Reynolds is the guy that you should go with


Well, hi everybody, I'm John Walls here and welcome back to theCUBE's continuing coverage of Splunk.conf 21. And we've talked a lot about data, obviously, and a number of partnerships and the point of resources that it's going on in this space. And certainly a very valuable partnership that Splunk has right now is one with Intel. And with me to talk a little bit more about that is Rick Echivarria, who is the vice president of sales and the marketing group at Intel. Rick, good to see you today. Thanks for joining us on theCUBE. It's good to see you, John, and thanks for having us. You bet. No, glad to have you as part of the.conf coverage as well. Well, first off, let's just for folks at home who would like to learn more about this relationship, the Splunk Intel partnership. If you would give us the 30,000 foot picture of it right now in terms of how it began and how it's evolved to the point where it resides today. Yeah, sure glad to do that. Splunk has had for many years position as one of the world's best security information and event management platform. So just like many customers in the cybersecurity space, they're probably trying to retire their technical debt. And one of the areas of important focus is the SIM space, right? The SIM segment within cybersecurity. And so the initial engagement between Intel and Splunk started with the information security group at Intel looking to again retire the technical debt, bring next generation SIM technology. And that started the engagement with Splunk. Again, to go solve the cybersecurity challenges. One of the things that we quickly learned is that those Splunk offers a great platform from a SIM point of view. As you know, the cybersecurity segment, the surface area of attack, the number of attacks they can continue to increase. And we quickly realized that this needed to be a collaboration in order for us to be able to work together to optimize our infrastructure. So it could scale, it could be performant, it could be reliable to protect Intel's business. And as we started to work with Splunk, we realized, hey, this is a great opportunity, Intel's benefiting from it. Why don't we start working together and create a reference architecture so that our joint customers also benefit from the collaboration that we have in the cybersecurity space as we were building the Intel cybersecurity infrastructure platform. So that was really the beginning of the collaboration that we're going to describe here in a little bit more detail. Right, so you had this good working relationship and said, hey, why don't we get together, let's get the band together and see what we can do for our joint clients down the road, right? So what about those benefits then? Because you've got this almost as force multiplier of Intel's experience and then what Splunk has been able to do in the data analytics world. What kind of values are being derived, do you think, with that partnership? Well, obviously we feel much better about our cybersecurity posture. And what's sort of interesting, John, is that we realized that we were, what started out as a conversation on SIM, it really turned out to be an opportunity for us to look at Splunk as a data platform. And in the technology world, you sometimes hear people talk about the horizontal capabilities and the vertical usages and really the security, the SIM technology really became one of several, sorry about the noise in the background, one became a vertical application. And then we realized, hey, we can apply this platform to some other usages. And in addition to that, when you think about cybersecurity and what we use to SIM, that tends to be part of your core systems in IT. We started to explore what can we do with, what could we do with other data types for other different types of applications. And so what we decided to do is, we would go explore usages of this data at the edge of the network and really started to move into much more of that operational technology space when we realized that Splunk could really, that we could integrate, that we can ingest other types of data. And that started a second collaboration around our open Vino technology and our AI capabilities at the edge with the ingestion and the machine learning capabilities of Splunk so that we can take things like visual data and start creating dashboards for example, managing the flow of people, especially in a COVID environment. So an understanding utilization of spaces. So it really started with SIM, it's moved to the edge and now we realize that there's a continuum in this data platform that we can build other usages around. You know what was that learning curve like when you went out to the edge? Cause a lot of people are talking about it, right? And there was a lot of banter about this is where we have to be. But you guys put your money where your mouth was, right?  And so what was that like and I guess maybe kind of being early in, what advantage do you think that has given you as that process has matured a little bit? Well, it's really interesting, John, because what really accelerated our engagement with Splunk in that space was the pandemic. And we had in 2020 Intel announced the its pandemic response technology initiative where we decided we were going to invest $50 million in accelerating technologies and solutions and partnerships to go solve some of the biggest challenges that a pandemic was presenting to the world at large. And one of those areas was around companies trying to figure out how to manage spaces, how to manage the number of people that are in a particular space and social distancing and things of that nature. And we ended up engaging with Splunk in this collaboration again to start looking at visual data, right? Integrating that with our OpenVINO platform. And again, their machine learning and algorithms and start then creating what you would call more operational technology types of application based on visual data. Now this will have other applications that can be used for security usages. It could be used for, again, social distancing, the utilization of assets. But the pandemic and that program that Intel launched is really what became the catalyst for collaboration with Splunk that allowed us to expand into space. Brian, you've done a tremendous amount of work in the healthcare space.  Can you give just a couple of examples of that, maybe the variety of uses or the variety of processes that you've had an influence in because I think it's pretty impressive. Yeah, we, there's quite a bit of breadth in the types of solutions we've deployed as part of the pandemic response. John, you can think of some of the, I wouldn't call these things basic things but you think about telehealth and improving the telehealth experience all the way to creating privacy aware, or sorry, solutions for privacy-sensitive usages where you're doing things like getting multiple institutions to share their data with the right privacy, which, you know, going back to secure but in privacy with the right protections for that data but being allowing organization A and organization B partner together, use data, create algorithms that both organizations benefit from. And an example of that is work we've done around X-ray and using X-rays to detect COVID on certain populations. So we've gone from those, you know, data protection, algorithm development type of solutions to work that we've done in telehealth. So, and a lot of other solutions in between. Obviously in the high performance space we've invested in high performance computing for to help the researchers find cures for the, you know, current pandemic and then looking at future pandemic. So it's been quite a breath of solutions and it's really a testament also to the breath of Intel's portfolio and partnerships to be able to enable so much in such a short amount of time. Oh, I totally agree. I mean, I was just reading a little bit about it, about that work and you talk about the breadth of that, the breadth and the depth of that is certainly impressive. So just in general, we'll just put healthcare in this big lump of customers. So what do you think the value proposition of your partnership with Splunk is in terms of providing, you know, ultimate value to your customers because you deal with so many different sectors. But if you could, you know, just give me a summary from your perspective, this is what we do. This is why this power works. Yeah. Well, customers talk about transformate, you know, there's a lot of conversation around transformation, right? Before the pandemic and through the pandemic, but there's a lot of talk about companies wanting to transform and, you know, in order to be able to transform, one of the key elements of that is to be able to capture the right data and then turn that data into the right outcomes. And that is something that requires obviously the capabilities and the ability to capture, to ingest, to analyze the data and to do that on an infrastructure that is going to scale with your business that is going to be reliable and that is going to be, to give you the flexibility for the types of solutions that you're wanting to deploy. And that's really what this plunk collaboration with Intel is going to do. It's just a great example, John, of this strategy that our CEO, Pat Gelsinger, recently talked about the importance of software to our business. This plunk collaboration is right in the center of that. They have capabilities in SIM, in IT, observability, in many other areas in this whole world is turning data into outcomes, into results. But that has to be done on an infrastructure that again will scale with your business just like what's the case with Intel and our cybersecurity platform, right? We need to collaborate to make sure that this was going to scale with the demands of our business and that requires close integration of hardware and software. The other point that I will make is that what started out as a collaboration between Intel and Splunk, it's also expanding to other partners in the ecosystem. So I like to touch a little bit on a work stream that we have ongoing between Intel Splunk, HPE and Deloitte. And why is that important? It's because as customers are deploying solutions, they're going to be deploying applications and they're going to have data in multiple environments, on-premise, across multiple clouds. And we have to give these customers the ability to gather the data from multiple sources and that's part of the effort that we're developing with HPE and Deloitte to allow people to gather data, perform their analytics regardless of where their data is and be able to deploy the Splunk platform across these multiple environments, whether it's going to be on-prem or it's going to be in a pure cloud environment or it's going to be in a hybrid with multiple clouds. We want to give our customers the most flexibility that we can and that's where that collaboration with Deloitte and HPE is going to come into play. Right, and you understand Splunk, right? You get the workload. I mean, it's totally, there's great familiarity there which is of great value to that customer base because you can apply that. So obviously you're giving this like multiple thumbs up about the partnership. What excites you the most about going forward? Because as you know, it's all about where are we going from here? It's not where we've been. So in terms of where you're going together in that partnership, what excites you about that? Well, first of all, we're excited because it's just a great example of the value that we can deliver to customers when you really understand their pain points and then have the capability to integrate solutions that encompass software and hardware together. So I think that the fact that we've been able to do the work on that core sim space where we now have a reference architecture that shows how you could really scale and deliver that Splunk solution for your cybersecurity needs and a scalable and reliable and with high level of security, of course. And the fact that we then also been able to co-develop fairly quickly solutions for the edge allows customers now to have that data platform that can scale and can access a lot of different data types from the edge to the cloud. That is really unique. I think it provides a lot of flexibility and it's applicable to a lot of vertical industry segments and a lot of customers. Right, and be attractive to a lot of customers. And that's for sure. Rick, Edge of Aria, we appreciate the time. Always good to see you and we certainly appreciate your joining us here on theCUBE to talk about .conf21 and your relationship with the folks at Splunk. Yeah, thank you, John. You've been talking about Intel, Splunk, good partnership, long-time partnership that has great plans going forward. We continue our coverage here of .conf21. You're watching theCUBE.


The study measured and modeled carbon dioxide, energy and water fluxes in a fresh clear cut surrounded by a mixed spruce birch aspen forest in the boreal zone of European Russia using eddy covariance and a process-based two-dimensional, 2D, hydrodynamic turbulent exchange model. The study found that the clear cut was a source of CO2 to the atmosphere prior to onset of vegetation growth during early spring, with mean daily latent, LE, and sensible, H, heat fluxes being very similar and the Bowen ratio, beta equals HLE, averaging about 1.0. Daily net ecosystem exchange of CO2, NE, was around zero GCM2D1 following onset of vegetation growth from mid-spring through summer, while beta declined to 0.6 to 0.7. The study also found strong diurnal variability in NE, LE and H over the measurement period that was governed by solar radiation and temperature as well as the leaf area index, LAI, of regrone vegetation. Modelled vertical CO2 and H2O fluxes along a transect that crossed the clear cut and coincided with the dominate wind direction showed that the clear cut strongly influenced turbulent fluxes within the atmospheric surface layer, while modelled atmospheric dynamics suggested that the clear cut had a large influence on turbulent fluxes in the downwind forest but little impact on the upwind side. The study concludes that an aggregated approach including field measurements and process-based models can be a useful approach to estimate energy, water, and carbon dioxide fluxes in non-uniform forest landscapes. This article was authored by V. Mamkin, J. Kerbetova, Via Vilov, and others. We are article.tv, links in the description below.


Moving on, constituents from Canoes Central, North and South Senatorial District have demanded for citizen participation in the selection, planning and execution of constituency projects in Canoes State while making their demands to the government our head of the 2023 fiscal year. The constituents who represented various youth-led community groups across the local government and the state were led by human rights activists from the resource centre for human rights and civic education in making their demands known. As part of their request, they arched the state during the Canoes State House of Assembly public hearing on the 2023 budget to pass the free maternal and child healthcare bill. The citizens also pleaded with the government to ensure the durability of projects across various constituencies in the state to ensure that the populace enjoy the dividends of democracy. We are hoping that the government will consider our health needs because we have so much things in our local government and so much needs concerning education, health and the environment. So we need the government to construct a youth and women vocational centre within our local governments in order to let our youths to acquire some certain skills and be educated to show out some social bias like drug abuse, political tuggery and some other things. We have already found our set in very much enhanced condition of having problems of water resources, problems of roads, problems of issue of only empowering youths that are there in our local government because we have many large numbers of people, therefore we are expecting the House to give us chance to construct roads from our local government to some different villages like Madachi, like Madachi, Garbawa, Kaswandala and the rest. So we are expecting us to, only in short period of time, we are expecting them to consider how the work is and how are they going to enter that particular needs towards the 2023 budget. Even from the design and implementation of those constituency projects, the masses are not carried along and at the end of the day you find out that those projects since it's not the community are not involved, they don't even take ownership of it and they don't even protect it or don't even see it as something that is their own. They believe it belongs to the representative. On the issue of the free maternal health care bill, we want the kind of state government as a matter of urgency to pass the kind of state free maternal health care bill. Unfortunately, kind of state has the highest rate of mortality when it comes to women and children. Hello, hope you enjoyed the news. Please do subscribe to our YouTube channel and don't forget to hit the notification button so you get notified about fresh news updates.


What's up everyone takedown here welcome back to another video today I'm gonna be sharing with you my PlayStation 4 video game collection The easiest way for me to record this video is to share what I have in my PlayStation 4 library because most of my games I have our digital versions. I do have some physical copies of my games But since PlayStation Store has a lot of great sales all of the time most of my games nowadays are digital So let's get right into this Okay, so up first is apex legends basically just a battle royale game You're gonna pick your legends and go and play honestly I find this is a lot of fun battle royale games to me are a lot more fun If you have friends to play them with but I really enjoy apex legends. Next is my arcade games We have dig dug galaga park man and miss park man Honestly, I got them because I really enjoy retro games I think they were no more than a dollar each and it's a great thing to do If you have nothing else to play if you want to go back to a retro game the fact that it's on the ps4 I really enjoy that Next is assassins creed freedom cry This is the first video game for assassins creed that I've ever played and it's basically an extension of Black flag which black flag is the first assassins creed full game that I purchased this here black flag I think it was only $15 whenever I purchased it on sale. I really enjoy it I still play it from time to time. I just haven't gotten back into it yet Next is the battlefield games. I own so battlefield one took place in world war one Honestly, it's a lot of fun It's what got me back into the battlefield series because at the time that battlefield one came out call of duty was still transitioning over into Futuristic games, which I do not enjoy so ever since battlefield one came out I go for battlefield more than call of duty. I do not like call of duty anymore So battlefield one is awesome Battlefield five is one that came out after battlefield one. It basically takes place in world war two I find the war stories for battlefield one and battlefield five Awesome, I think they're accurate the gameplay is awesome. The maps are huge So I get to actually sniping them compared to call of duty where I can't do that But then recently I got battlefield hard line, which it was only six dollars So I guess you get what you pay for it, but it wasn't that fun It was kind of cheesy gameplay is very minimal There is it's basically set up like a TV show or a movie where it just goes through each episode telling you what happens It goes through a lot more cutscenes than there is gameplay So I just didn't enjoy it as much as I did battlefield one or battlefield five, but it was only six dollars Next is the borderlands handsome collection. This was free for ps plus I think you get the pre-sequel and the second borderlands game. I only played the pre-sequel Honestly, I didn't find it too fun, but I've been told it's better with friends I just haven't had time to sit down and play this one with friends So I honestly don't enjoy it as much borderlands just might not be for me Moving on is burnout paradise remastered. I actually got a platinum out of this game It was a lot of fun reminded me of my childhood on the PlayStation 2, but it was very repetitive I never played burnout paradise before until I got this one on the ps4 the remastered version And it is very repetitive because for each level of your license you have to go back and play races and Play them over and over again after you get each less license upgraded. So Just very repetitive call of duty black ops 3. I enjoyed it What I didn't enjoy was the zombie mode for call of duty. I don't like the zombie modes in them I actually hate zombie and call of duty. So it was okay modern warfare remastered Was a free ps plus game. I think in March, I actually enjoyed it. This is the first time playing modern warfare. It was the ps4 remastered version I enjoyed it online actually sucked in my opinion, but the story was okay So that's why I enjoyed it call of duty World War two Honestly battlefield 5 took place in World War two called duty World War two lacked everywhere that battlefield 5 Did great on so it was an okay game The story was interesting, but it didn't have much going for it for me Next is cluster truck basically a cheap little time waster your character basically jumps from truck to truck trying to pass each level Cross-out you basically start off with a cheap Stock vehicle and then by getting kills and winning races or sorry not races But winning levels and matches and different things like that You can go and get more parts to basically customize your vehicle to whatever you want So that's really cool Dead Island retro revenge when I was on my hunt for retro games. I came up with this. I loved Dead Island I'm still waiting on Dead Island a new Dead Island to come out Which I don't think at this point it's going to happen But retro revenge no more than a dollar. I actually found it was fun Detroit become human This is my favorite free ps plus game that has ever come out since I got ps plus when I first got my ps4 I really enjoyed it. I think it's 10 out of 10 very phenomenal and I'm really close to getting a platinum for it Disc jam is basically like tennis, but with flying discs very simple fun game Don't bite me bro is basically a pixel zombie game not really fun It is kind of survival, but not much to it UFC 3 I don't know why it doesn't show UFC 2 because I actually have the hard copy of that game But UFC 3 was very more advanced. I love the career mode I really got me even more into UFC than I ever have been and I'm a huge fan of UFC right now because of it energy balance is basically a Math puzzle game, but I got the platinum out of it. It just wasn't that fun of game energy cycle is made by the same People it was a lot more of a fun puzzle game. I actually enjoyed this one a lot more and got a platinum out of it as well epic dumpster bear Very cheesy Basically kind of like a Mario esque game where you just go through each level kind of cheesy and I'm just gonna move on from here Everybody's gone to the rapture. It was interesting. I just never got into it because it's very slow and it was a free ps Plus game. That's why I got it Far Cry 5 first Far Cry game that I've ever played Huge fan would highly recommend it to anybody if you have yet to play it because it has a very cool Aspect to it and I got a platinum out of the game. I really enjoyed the game Far Cry new dawn is a continuation of Far Cry 5 Basically the aftermath of what happens in Far Cry 5 They did take out a couple of the features from Far Cry 5 when they brought out new dawn But I can move past it because I still enjoy new dawn and got the platinum for its fishing planet is I believe a free Game on the ps4 for fishing Honestly, I did not enjoy it I'd rather pay for a fishing game if that's what you're into a fishing simulator Fortnight just gonna move on because I haven't played it for a long time and I'm not into it anymore Foul play is a cool game, but it's not something I can grind out on. It's basically like A play and you're going through each level killing enemies, but it's to get a high score for your play or whatever For Kings casino and slots. It's basically just a casino game game of thrones is a telltale game So the story is on points and I've never really gotten to game of thrones, but this I Think it's the first season of game of thrones. That's what it's based on. I actually enjoyed the game. It was a lot of fun Gran Turismo Sport the actually I think I got it on PS3 I've had played Gran Turismo games before it's a lot of fun It's a great racing game and I still go back to it from time to time. It's just I have so much to play I just don't have time to just grind out on this game GTA 5 This is a game that since I got it back when it first came out I played it non-stop for years and I feel at this point. I've done everything that it came for the game I'm kind of burnout on the game. I have no intention of going back and playing it Grand Theft Auto San Andreas play this back on the PlayStation 2. I got it for I think a couple bucks on ps4 when it came out It reminded me of my childhood. That's why I wanted to get it and on the ps4. It's the first time that I actually got to Beat the game, so I actually enjoyed that I got a platinum out of it H1Z1 before pubg and apex legends came out. It's basically a free Battle Royale game. It's kind of cheap. I don't have any intention of going back and playing it heavy rain came from the creators of Detroit Become Human. It looks interesting. I just haven't had time to sit down and play it It's something I plan on going back to eventually Horizon Chase Turbo.  So I just haven't got the time to go and play it much Hunting simulator. I used to on the ps2 love hunting games. This one here. It's kind of cheesy wasn't worth it Hustle games is basically playing cool Doing stuff like that. I think that's all that it is infamous second son I Haven't had time to get this game. It was free for ps plus. That's why I downloaded it back whenever I got my ps4 I just the only ps the only infamous game that I played was the first one that came for my ps3 when I bought it I didn't enjoy it. So this one here. I have no intention right now to play it, but maybe someday Anxplosion is the cheapest Is one of the cheap games that I purchased that was extremely fun I would recommend it to anybody you can get a platinum out of it. I actually loved this game inside my radio is basically like a Game that you go through each level and the faster that you go the radio and the beat and the sound of the game goes faster So it's interesting Just cause three never really got into it whenever it came out I did but I never continued to play it because I had so many other games to play Killing floor two is basically a zombie game It's fun. It's repetitive I just have so much other things to play that I'd rather not play it Laser League when this first came out for free for the PlayStation 4 It was a lot of fun But now if you go and play and you try to find an online game where you match with online players It's hard because not too many people play the game anymore Next is the Lego games. So I have Lego Batman 3 Lego Marvel superheroes Lego Marvel superheroes 2 Jurassic World and Marvel's Avengers out of those games. I only beat Jurassic World and Lego superheroes Basically, it requires a couple playthroughs But you can get a platinum for each one when my hours at work go down in the winter I plan on playing the rest of the Lego games and beating them Life is strange before the storm Basically, it shows what happens before the events of the first life is strange game You can get a platinum out of it. I got it for a huge discount So I plan on playing it when my hours go down as well Little nightmares felt like this game is a lot of fun has a huge twist at the end of it I would definitely recommend it to anybody that's into kind of Creepy but also fun games little big planet 3 I Remember this being a very popular game a little big planet series. It's just not for me. I didn't enjoy this game Mad Max. It's an apocalyptic game It has racing aspects to it and killing of enemies. It's a lot of fun I plan on going back to it, but no time frame of when Mafia 3 I liked that it was in the 60s time period except the game is extremely repetitive So I don't know if I'm gonna go back and play it at all oops Marvel's spider-man a Huge fan of Marvel huge fan of spider-man the gameplay is phenomenal the Story is phenomenal the graphics are great. The story is amazing. I'm a huge fan of this game 10 out of 10 for me Mega Man legacy collection. I honestly did not like the Lego or the Mega Man games. I didn't find them fun. They're just not for me minecraft never really got into my name is Mayo Just gonna move past it Minefield is something I used to hate on PC now. I actually know how to play it and know how to beat it So I find it's fun Mx versus ATV is not what I expected I remember the ps2 version which is a lot more fun and a lot of gameplay this here is kind of cheap and cheesy NBA 2k 16 Was a lot of fun. It was free for ps plus this year of the year it came out So I enjoyed it I played with my friends and that got me to get NBA 2k 19 Which I only got for $20 for $20 to get back into NBA is a lot of fun for me Need for speed 2015 the first need for speed game that actually beats and got the platinum for I meant to race in games. This was a lot of fun for me. I'm a huge fan of it Need for speed payback. I just beat the campaign recently. I'm trying and grinding out for that platinum I know it's there. I know I can get it definitely would recommend it But there's a lot of features in need for speed payback that I did not like So I might make a video talking about what I did not like for payback in the future if you guys are interested to let me know NHL 16 NHL 18 18 I basically went and played over 30 seasons combined of my GM mode and my career mode It's a lot of fun. I plan on getting NHL 20 when it comes out this year Ninja Senkai DX Didn't enjoy it's a free ps plus game not a hero pixelated ps plus game did not enjoy it Onrush, which is a racing game, which reminded me of burnout. It was a lot of fun I'm one trophy away from the platinum, which I think I only have three races left to do It's a little bit of a grind, but I would recommend it Overcooked it was a free ps plus game I really wish it had online co-op, but I have been game-sharing and playing it with my friend Pac-man 256 is basically like a app on your phone of Pac-man. It's kind of cheesy But it is fun to waste time on payday, too I love anything about heists So this game I play I'm playing the campaign on my own and also playing the online with Jack Ratchet and Clank reminded me of my childhood PS2 playing this game. I just never got into it on the ps4 Qbert rebooted I played it on the Basically I got it because it's a retro game, but it's not fun pub G. I love Battle Royale games This was a lot of fun, but I never played unless I have somebody to play it with St. Rose Gadot of Hell a lot of fun. I enjoyed it. I love the apocalyptic underworld Sniper Elite 4 the first sniper elite game I played. I found it was fun a little bit of a grind, but I enjoy it Sonic mania basically a retro sonic game Mud spins sorry spin tires mudrunner basically a mud game. It's not what I expected it to be South Park stick of truth and South Park factored but whole I Really enjoyed these games. They reminded me of the show the comedy from the show for the years It's been around is there very fun Not too much for gameplay for the first one the second one is a lot more fun in my opinion Spiral splatter, which is a cheap game. You can platinum it, but it is a grind I don't play it too much, but it is something that I do want to eventually get the platinum a 4 and try to grind down and get it Next is steep, which is the first snowboarding game that I played in a very long time I remember having a computer game back in the early 2000s of snowboarding. So this reminded me of that Reminded me in my childhood. It's a lot of fun a lot of stunts. You can do in it. I really enjoyed it Super dust or not DX is basically a space invaders clone in a great way. It's a lot of fun. I got the platinum for it I really enjoyed the game. It was pretty cheap and Tetris ultimates, I never really got into I do enjoy Tetris games. I remember playing them as a kid I just don't have the time to go and invest into this one lot the the last of us remastered I Did enjoy this game. I did get Decently far in the campaign the online personally sucked. There's no zombies online. I thought that was a huge letdown The walking dead telltale series the first one I enjoyed I remember playing the first one on the ps3 beating it and platinum yet and on the ps4 It actually was free for ps plus. So I got it there The walking dead season 2 and the walking dead a new frontier, which is the third game Honestly, I enjoy most of the telltale games. I think they are a lot of fun, and I really enjoy them and I can't wait to play the final one. It's on sale right now for $20 But I can't justify paying $20 when all of the telltale games that I've ever played The three walking dead games walking dead Michonne Borderlands Batman and Game of Thrones. I only paid no more than $10 for all of them So I don't want to pay $20 for just one telltale game Even though it would complete my walking dead telltale game series and I would get a platinum Eventually I will get it, but just not yet trackmania It is an okay racing game. It's just not something that I play often trails fusion It was fun at first, but now I don't really have the time to invest into it tropical 5 is basically an app where you create and upscale your Worlds basically it's like an app you would play on your phone. It was fun at first It was the most expensive game back whenever I got it for free for play this PlayStation Plus I think it was like a 70 or 80 dollar game. I just don't play it anymore Uncharted Nathan Drake collection back whenever I got my first PlayStation 4 this came with it I actually have the hard copy disc of it. It is fun I remember playing the Uncharted games back on the PlayStation 3 Haven't played in a very very long time But it's something that I keep in my collection because I really want to one day go back to it Of course WWE 2k17 18 and 19. I have a WWE Video game collection. I think I've shared that on my channel in the past as well. I really enjoy it I just wish that WWE games would finally bring back the GM mode That's honestly what I'm waiting for and WWE 2k20. I'm honestly excited for it coming out this year So this was my PlayStation 4 video game collection. I hope you all did enjoy This was a little bit longer of a video than what you're used to because I wanted to share everything that I have in my PlayStation 4 video game collection and Also because most of my games are on digital So this was the easiest way that I could record this video and talk about the games along the way Because I do have a couple physical copies But most of my games are the digital version and I wanted to talk about the games on the way So that's why I recorded it this way and that's why it's so long because there's over 100 games in my collection That I have on my PS4 or that I've played on my PS4 Everything that I've played in the past or currently playing or what I'm grinding out for that platinum trophy right now So I hope you all did enjoy if you guys have a PlayStation 4 video game collection on your channel Comment it down below. I'll check it out I would say comment your collection down below But if you have a big collection like I do to type out all those games it'd be easier for you just to make a video Like I did so I hope you all enjoyed this video. See you guys in the next one. Please take care. Peace


So yes, thank you for surviving this long and being here for my talk.  So moving ahead because I know this is a common question or rather assumption, I am at the University of Oregon and there's also this thing called Oregon State and this there will be a quiz later. But how do you tell the difference? This is the University of Oregon, not our stadium, but that's the mascot, that's Donald Duck there, and this is Oregon State. Now I wasn't being you know mean to them, this is one of the first images that comes up when you google up their mascot so I just use it. Okay, so ducks versus beavers, green versus orange, all that good stuff. So acknowledgement for a few funding sources that have generously funded our work. So first I'm going to talk about performance of software and then I'm going to move on to what we do about developers. And typically to set up this, I don't get to choose the software whose performance we will be optimizing. This is basically application collaborators, so scientists in other domains who may want to improve the performance of their code and it doesn't have to be massively parallel, it could be running on a single workstation, but they want to just have it work faster. And so we have sometimes multi-year collaborations that focus on this. And the goals are usually to figure out what the goal is to that you want to achieve. I mean you can't take a code that currently runs in many hours on a single machine and hope that in a month it's going to be running in a few seconds on a supercomputer. So the goal, identify the problems then that may be addressed and then eliminate those problems and then relax. So the performance engineering cycle as it's called among my CS friends has a few obvious steps that I'll go over briefly. But basically as with anything whose performance you wish to improve, you basically have to measure the current state of things and then based on those observations you want to create some model of what's going on and then because those are all domain codes typically for me really understand what's going on means you have to talk to the scientists about their performance at the moment and then we need to talk about what we can do we cannot do. So I can't tell them oh yes switch to a less accurate method that will be faster right if the accuracy is something they care about. So this part here is pretty important here how do we communicate the results and then do we understand each other's language absolutely not and so we spend a fair amount of time in that box and then just cycles through eliminating problems one by one and I will talk about what that means in the last part of this section. So what do I mean about when I say understanding? So when you have a piece of code you want to know how much is possible to improve so your code already exists you have written it you've spent a lot of time on this implementation and you have maybe even have some architecture in mind that you wish to run on and then you want to figure out well what could I possibly achieve here and then also if you want to be able to run on a future architecture you may want to know in advance how well would you be doing on that new architecture and then when I say architecture those things matter a lot. I was originally at the Department of Energy Argonne National Lab so there was a lot of of course with each new supercomputer you want to be able in advance to prepare to run on those machines but even now with new Intel Xeon generations and other accelerators coming up you wish to be prepared for them before they actually come out and that never happens by the way so but we think about it so we do this through modeling and basically we do some through measurement and some through just pen paper mathematical models of performance which is you pick something like time execution time and now you want to create a model for that that helps you characterize some behavior and then we also use tools that look at the code itself to try to build a model of what's going on and those are think of them as compiler like tools that basically second the binary or the source code and build a model based on that so those three things and the most common one which is measurement also known as empirical analysis what we try to do here and this is where maybe I don't know so let's see a show of hands how many of you actually care about speeding up any code that you're currently working on okay so there's quite a bit of interest I should have asked this in the beginning but that's okay so this is sort of there are many many ways to do this and they're currently mostly most of them are pretty painful but our goal here is to make some sort of streamline the process for people who don't want to learn myriad of tools that are you know kind of steep learning curves you don't know whether to trust someone out and so forth so we're trying to generalize this analysis workflow for as many types of applications as possible and to collect empirical data and by that I mean not just timing so not just oh you know this function took seven seconds that function five but actually look at the memory performance in other aspects if you're multi-threaded or parallel in other ways how well is your code paralyzed all those things can be automated and so that's what we are working on at the moment I can't boast that we have a generic way to do this it's still you know once we establish a collaboration with somebody we can implement such work flows and they can use them easily but that's kind of the grand goal we use actually those are a lot of tools here that I throw around the names of but we use a lot of Python data analysis tools because there's so many and they're wonderful and so should be pretty low learning curve so we mentioned Tau Commander you may google it it's not that one instead there's I don't know if you can see it but it's TauCommander.TypeParatools.com which is the Tau Group is a big group that's been at University of Oregon way longer than me and they're still nice and happy but now there's this exciting Tau Commander on top of it that lets you actually program your analysis instead of having to click on some stupid Java we developed by students so it's really great okay so here's an example I just picked one of the projects that we're just collaborating with now but basically they have a medium-sized C++ code now the language doesn't matter too much although for some languages there's more tools than others and in this particular C++ code that's using Intel TBB for parallelism we want to find out which of their functions scale the worst you know so it's a fairly small amount in a Jupyter notebook of code to get to this kind of result right and so that's going to be the pattern and this shows this particular map seed hits is the worst scaling function as we discover it later it wasn't paralyzed at all which explains why it doesn't scale and so this is something that we started working on and then another thing so that particular function now we can go and say well what the heck is it doing when yes you can go read the code but when the compiler is done with it what is it really you know the instruction mix is one way of looking at it and those are by instruction we mean the low-level assembly level instructions right so as you know memory access is slower than flops and so we look at all these branches those are conditionals they impede parallelism okay if the compiler or library is trying to run something in parallel all these conditionals prevented from doing a great job there's a lot of memory operations going on there's hardly any computing so this these two little segments are all the computing there is so no wonder this doesn't do so well it is very memory intensive it has conditionals so so this is again a quick way to get some information about this function and then then you can say well but I don't know what this memory load store might be great it might be the architecture may be doing a great job fetching all my data as I need it right then we can check that quite easily again and figure out oh here's my level one cache misses so you can go very deep or not that's up to the developers but looking at scaling this is threads at the bottom here right you can see what doesn't scale from the point of view of memory and also the conditionals are here so you can see that you know ideally there should be flat lines they should not be going up okay and when you have the green line going up which is branch misprediction rate that's not good so that's not that's one thing that's anything is skating so this is just a ref analysis to tell you what you should be what problems you should be focusing on and then there's many many more that you can't all be included in a talk just to give you a flavor so then based on all the data we collect we may decide to build a model so is for example this miss rate here is it actually related to execution time does it does it affect it at all yes no right so we could actually check so we analyze with a little bit of linear regression usually simple enough and works and then more complex models when needed including somehow mentioned later so this is to predict execution time on an unreasonable number of threads like suppose I have in the future a thousand threads what's going to happen like things like that and then or suppose I reduce my miss rate by 50% how much speed up am I going to get is it worth my time to you know redo my data structures which is a big change right so the cost of that effort is huge and then we can evaluate it spec so static models those are weird I don't expect you to relate to them very much but they're pretty cool they're still kind of newish and so maybe not applicable to as many causes we like yet suppose you have a simple function that does something and in this case it's doing this very simple vector operation here and this is apologized for the c++ but you could be done in any language because what we do is we just count things at the binary level so it doesn't matter where it came from and you're just looking at the instruction mix except you're not running anything you're just looking at the generated binary code so remember the pie chart from a couple slides back so we get the same sort of data without running anything and based on that now you can try to determine other things so here's an example of that same data in a different form this is believe it or not instruction mix here those four values and the table or the matrix entries represent some transition probabilities because you have if statements and for loops and such where you take different paths in your code and so on so I'll tell you later what we use this for so right now it probably looks very obscure and like what the heck do you do with that so hang on to that okay because next up is performance optimization so all this was just a flavor of some of the I mean showing some of the flavors of analysis we do the goal is obviously to improve performance so eventually we have to do that even though it's so much fun playing with data and we don't want to stop so performance optimization could be simple but it's not and the plan is as I mentioned before as you figure out the problems you fix them you move on the reality is pretty nasty you know I don't know if you have you have your own war stories I'm sure but like we had a period of two three four years where you know Intel just did not let us measure flops which is for scientific computing floating point operations are kind of essential and so not being able to know how many of them your program actually did was a little bit crippling and that's why we started those static tools where we look at the binaries and try to estimate those I mean not manually but without running and then Nvidia of course you know I don't have to explain and then of course the the thing is how many of you have a machine that has Intel or AMD CPU in it and an Nvidia GPU and right so how many tools do you know that work with both these in concert and harmony languages so you have one which one oh very good yes um from the point of view of developing scientific software however it's zero and in fact I think they'll actively prevent you from from doing that because they're competing with each other so um and and yeah using those things simultaneously and well analyzing them simultaneously optimizing them simultaneously it's pretty much a no go if you wait for them to give you something so uh what we end up doing it so that's great because that's what you know why we exist and have cool collaborations with a lot of different scientific domains so so I'll just talk about our view of my view I guess because I tell the students and they do it um of what process we follow to optimize software in general so it's kind of high level um so the first thing we do um is check whether you know you have some time consuming operation that you're doing instead of blindly going and hacking loops we actually will talk seriously and they may laugh at us but we said you really need to be doing this and sometimes the answer is no um so the first step is to eliminate code that you shouldn't be um doing um and so that's pretty obvious but it's funny that you know we don't we didn't always start with that uh the next thing which is just for the brave it hardly ever happens in real life but in some cases it uh it does is that if there is a way to wean people from uh Fortran or C++ or C or whatever the heck they're using at the moment and they're unhappy with and introduce a higher level notation that expresses what they need and then introduce a code generation you know step uh that you can optimize automatically that is ideal and I give an example with MATLAB uh where you know things like uh this being you know if B happens to be a inverse you're not going to end up doing any multiplication right uh if you have that high level knowledge which if you encode this and see you know uh you'll never detect such a thing and you will be doing an n cube operation here right and I don't want to optimize that uh so it's just an extreme example but it does happen uh so wherever you can encode things in a higher um level language uh where you could actually employ some optimizations at that level that's uh that's ideal obviously there's a huge implementation cost to domain specific languages uh but it may be worth it in the long term because it will give you uh sort of a single code base multiple backends very optimized okay so that's for the programming languages so next we look at algorithms and maybe you um look numerical recipes and code that happens every single year I'm not joking that somebody I work with what actually needs an eigen solver and then yeah I mean they either you know found one on math overflow or whatever and or the numerical recipes book which I wish would be burnt um for good and they coded it up and it's really hard to convince them it's not great okay so you have to do a lot of work to prove that uh oh by the way you know they're much better algorithms nowadays than those that people came up 30 years ago so um so sometimes though that's not the case and there just aren't any and then you have to think about them and so we work on new algorithms with people who are interested this is not a typical scientific computing it's more so dynamic graphs I mean they can arrive arise anywhere but in hypergraphs actually um are used in uh computational chemistry and such and uh we and biology is heavy on on graphs um but basically how do you efficiently compute properties of graphs that actually keep changing and we sort of shy away from social networks because we don't care but um uh so so this is kind of part of the work we do is instead of just taking some um sequential graph algorithm that you're very familiar with this is single source shortest pass uh we really rethink what it is we're computing right and um or and then and static by that I mean you compute it once and you're done here new edges keep coming new vertices keep coming or being deleted how do you do this in parallel how do you do it fast um and so this just shows some results from something with it recently uh but I am happy to do this for any domain if I'm qualified to think about it um and then sometimes uh it's not that there isn't an algorithm so it's the opposite problem but you have way too many algorithms okay way too many methods available and this is a case at least for several uh different areas but this example is farce linear system solution right um there's dozens of methods that are uh theoretically equivalent so when we talk about iterative methods right uh so curl of methods they are all um the same complexity and theoretically in practice though they converge at very different rates and for most of them with preconditioning even um you cannot really predict which one would necessarily be the best for your particular problem and so uh this is where uh we uh you know how do we choose and we've given up on thinking and use machine learning and so uh this is a diagram of the complicated machine learning workflow that we use that's completely automatic for um one of the libraries we work with pet z but um the linear system um is you know the matrix is what uh we compute the properties of and based on those and you have to compute them fast and cheaply because that's overhead uh we have a machine learning model that uh then recommends what's over should you use for this particular one okay and there's a lot more uh how well does it work well it depends um if you actually train your model with uh sort of a more limited uh set of inputs from say the same domain okay not the same application just generic um and by domain it's not even the science it's more the numerical method so if you're doing the same sort of PDE solution uh you'll get a better result uh but generally uh we've been able even with a very diverse training data set uh get pretty good accuracy over 90 percent which means that in um over 90 percent of the cases when this thing recommends use this method it will be faster if you didn't use it so that's the the outcome here um the speed ups are uh we don't even consider the the case where you fail to solve it completely because speed up is infinity then uh but it's about uh you know ranges from uh a few percent to seven uh fold and this is for parallel things that can go pretty um large scale okay so anything else on this no oh low level optimizations those i'm gonna skip because i know that you want to see the human part uh but i'm happy to talk about them later if you want so there's a lot of uh details here um so humans how do we optimize humans uh right now i think we are not there yet we're not at the optimizing humans we're still studying the humans so we're doing the measurement plus analysis of humans part then leading into optimization um we only have data to go on we don't talk to anyone so that's one of just what we decided to do in this project uh so we don't not that we don't trust them we just don't want to have to deal with that and we use only available data which is the code people right um and so revision control system has a lot of metadata as well that that we use and issue trackers and such and the fun part the developer communications via email mailing lists or issue discussions and um right now we're just studying them uh different aspects of this and i'll show you a few examples and then maybe come up with some ideas of what to do or what not to do um so what metrics have we considered this is a partial list we've had more uh in the recent um months but uh you can guess you know people doing things i commit number of lines of code additions additions you know the usual um topics of discussion when you talk about the natural language part of this and so on um you can compute a whole lot of stuff so here's a specific example for three projects over uh the x-axis is depending on the project uh but it is at least several years so it's the whole lifetime of that project and those are uh bugs and fixes so you know when you use an issue tracker you submit a bug report things happen uh maybe you hope eventually it gets fixed it gets closed so this is what this is showing uh so this is cumulative bugs and fixes over time these are just issues any issues so community is just saying something um and then you respond or not if you're this project and so this is interesting right because i don't know where the bugs and fixes do you think this is how they i mean this doesn't look like a normal scenario right that you keep opening new bugs bugs bugs bugs bugs and then one day one guy uh and we checked wakes up it's a good day and he fixes them all so i mean i don't know i'd be a little worried if i was in this project and then there's more reasonable stuff and here people are clearly not keeping up in those two uh you know things are getting uh staying open closing rate is not keeping up and then uh you may want to think of well maybe they need more people in this project that they're dealing with this kind of stuff so this is uh so discussions focusing on natural language processing analysis of this so what are people talking about and those are three different um uh scientific projects and then they uh hot topics of discussion this is very standard analysis but basically bugs obviously enhancements bug fixes documentation and so on you can see sort of over time this is just a snapshot of all communications uh what do people email about a lot this is a petty mailing list developer mailing list and uh so it could be complicated the topics around the x-axis the number of emails is on the y-axis and the sizes of the bubble is how long this conversation lasted and um you know this this actually is many years the big red circles is e-years um and so apparently uh this is strange chebyshev estimate so we haven't labeled all of them obviously but you can look it up and configure error is by far the most uh long lasting discussion topic here and so uh bubble charts are not that useful but they're fun to look at this is a completely different project and they have advice and this one do not use openmp with playing lesson learned all right and then uh we did fun stuff like profanity analysis now we can do this for any git project okay so we did this for linux as well as other github open source projects and um we do have the actual words and the actual people and what they like the best but we're not showing this here um however this is not the profanity words this is the words in proximity to profane words so so those are the things you're cursing about obviously they do not like fixing things uh i have no idea who uh where's jeff yeah there's a now their vocabulary is very extensive uh now this is petsey and and they apparently curse about petsey the most so that's that's very you know and then some other topics um and the vocabularies are censored sorry um but those are this actually shows humans and what words they use the most and uh those can be looked up on demand by asking me um but what i know this is this is linux and this is i don't remember which um project to the scientific project but um those are the words on the outside so so there's very many many many many curse words that linux uses and not so many from the phd so you need to diversify your vocabulary i think um then we look at collaborations uh and there's two kinds of collaboration graphs that we create those are really cool i think um not enough time to talk about them but one shows how people are working on the same resources so the same files though they're being touched by multiple people if you if you commit to a file we draw an edge between you and the file and so you can actually see uh in some in some projects um i mean it's hard to visualize but you can do different analysis on this to show what parts of the code are in danger of being um un you know maintainable because too few people or nobody's touching them or vice versa people fighting over the same piece of code okay so and how people work with each other and whether you have one central person because if they get hit by a bus or a train i'm not transportation bias they will you know be in trouble um so here failed projects collaboration graphs so they're a little bit different from the previous ones which were successful and we're trying to learn from that our developers more productive when they're unhappy preliminary answers yes i will not explain this further you have to wait for the paper um and so um i think it's very hard to optimize productivity but what we're making here is the first steps in sort of quantifying as much as possible things that are relevant we think for people to make the right choices and optimizing their own work and so we won't tell them hey don't do this or don't do that but hopefully provide enough information that if fame is being wasted then they would know that as opposed to not knowing it at the moment and that's basically it we consider both the application and hardware performance and definitely like to talk about how to improve the human happiness and productivity so thank you oh before you ask questions here's the quiz um so which one is which what is this come on guys i was at the state very good university organ yes very thank you um i thought i was really thought provoking so maybe we have time for a few questions uh that's exactly what we're trying to determine we want to we see it when we play around with them but we can't quantify it yet and so we're trying different metrics to exactly uh that to tell you that there is a specific difference there's some uh where you have yes a single central node instead of multiple central so you compute high centrality nodes when you see oh there's only one that's a problem things like that and a lot of i call them dandelions because they're like very easy to disconnect pieces of the software if you have a lot of those that's a problem but i've not proven that yet so we're trying to make that more robust yeah well thank you oh yeah with the with the language um one thing to qualify is uh you you uh typically the the people who have ended up doing this in their domains is um are desperate and they have uh they're not going to get anything done um outside um of their project necessarily so the language is developed internally in the cases i'm involved in they know of um and it's not just single project necessarily but sub community decides that they had enough and now they're gonna do something about it and some even do it without knowing what they're doing they don't even call it a domain language but that's what they end up having um and most of the longer lasting projects um have done something like that already um and it's interesting because that's uh the critical point for many of them is when you end up having to develop two or three versions of your code so for example something that runs on code devices and something that runs on cpu's and now if you add another one and you say no way and now we're gonna switch to code generators for libraries if you can't use libraries then you don't really have much of a choice right so yeah thank you bojana um we are a little bit into our break um which was not your fault at all um but i thought this was a really interesting discussion and um part of your talk so i thought it was worth it


Here is an example of an audio file. Just a sample file. This illustrates the analog data in the time domain. So on the horizontal axis is time. So this is just a plot of a signal. Think of our signals from our first lectures. We plot the signal strength versus time. And in fact we have two plots here. So we have time along this axis. Zero seconds up to nine seconds. So it's nine seconds worth of audio. And the signal strength going up and down. We'll zoom in in a moment and we'll see it closer. This is an audio file which uses stereo. There are two channels left and right. And stereo just means that think of two separate audio tracks. And that's shown here. How big is the file if we save it? So let's say we recorded this nine seconds of audio. How are you going to calculate the file size when you save it to disk? What do you need to know? So I think this is the original analog audio. Analog data. How big is the file? Nine seconds of audio. Well, first you need to know what technique is used to encode the analog data into digital. So when we take the analog input, we save it as a file. Usually we select a file format which would imply the algorithm used to encode analog to digital, the codec. So when I save this, actually I export this in this case, and I can select the format here, there are different formats that some of you would have heard of. If you cannot see, there's WAVE, WAV, MP3, FLAC, AAC, AC3, WMA. These I think are formats or more specifically codecs used for encoding analog audio into digital. So when you play back music, you're usually using MP3 or one of the other codecs. Well, we want to use a codec which uses PCM, and commonly WAVE uses PCM. Not always, but it's common that when you save a file in WAVE format, WAV, the codec used is PCM, and it is the case in this one. And it says WAVE, Microsoft, because they standardised this format, signed 16-bit PCM. So when I save that file, or in this case exported, I get a file on the hard disk and we'll look at the moment the size. So the format of the file usually determines the codec used to encode that analog data into digital. This is using PCM. What else do we need to know? Well, when we save the file, it says 16-bit PCM, which means that there are 16 bits per sample. One sample is saved at a 16-bit value. With 16 bits, it means there's two to the power of 16 possible levels, or code numbers, about 65,000 levels in this case. The sampling rate, it's actually shown up here. The sampling rate, and it's common, we could have changed it, but the sampling rate in this case is 44,100. It's CD quality audio. So it's the same as a CD. 44,100 hertz. And it's in stereo, so we could calculate the file size. We did it yesterday for a CD. It's the same structure. What do we have? We have nine seconds of audio in this example. And the sampling rate of 44,100 hertz, which means 44,100 samples per second. And a sample size, that is, each sample is 16 bits. In other words, two to the power of 16 different levels. And it's in stereo. There are two tracks. So the data size in digital, well, we just calculate. We have, in one second, we have nine seconds worth. In one second, we have 44,100 samples. So four. So in one second, we have 44,100 samples. Each sample is 16 bits. And we have nine seconds worth. So that will tell us the number of bits for one track of audio. For nine seconds, this would give us the number of bits. But in fact, we have two tracks. We have left and right for stereo. So in fact, we multiply by two. Because each track, we must save those bits on the hard disk. So that's the total number of bits to represent this audio, which is, you'll get out your calculator, nine times 44,100 times 16 times two. That's the number of bits. And usually when we save on a disk, we use bytes. So let's just convert to bytes. So 1,587,600 bytes. So that's the amount of data we need to save on the disk. So we expect the file size to be at least that size. So when we save it in a WAV file, the file size should be around this. Let's check. Come back to that number. Where is it? I have it somewhere. The file size is 1,589,228 bytes. So the WAV file. 1,589. We calculated the data is 1,587. So the file is slightly larger than this. The file, the WAV file includes the data plus a few extra things to keep track of what type of data is inside here. So the format of what the data is. Think of it as like a header, some overhead to store there. So it's about 1.5 megabucks. What if I export it to a different file type or using a different codec? That was using WAV, which uses PCM. I haven't tried this, we'll see if it works. MP3. Save it as an MP3 file. And let's look at the size of the MP3. 145,000 bytes. The WAV file using PCM was 1.5 megabytes. The MP3 is about one-tenth of the size. So the same original analog audio, same original data, but we used a different codec. With WAV we used the PCM codec, the one that we've studied. But in the second case with MP3, it uses a different algorithm for converting the analog into digital. And in this case, it uses an algorithm such that the file size, the amount of data saved is much less. And that's the advantage of MP3. Same nine seconds of audio, but a smaller file to store it on disk. And much more easier to store many, a large amount of audio and also to transfer. So what's the difference? It's smaller, what's the problem with MP3? How does it get it smaller? With PCM we took samples and mapped each sample to 16 bits. With MP3 it's more complex and I don't even remember the details of the algorithm. But there's two things. To reduce the file size we can reduce the quality. So less samples and less bits per sample reduces the quality. So generally a smaller file size, a smaller quality. But it's not always true. What MP3 and other algorithms or other codecs do is that they look at the structure of the audio and the MP3 even removes some parts of the audio. So some of the frequencies which do not contribute much to the quality of the audio, it discards them. It throws them away. So when you play back the MP3 file you don't hear exactly the same as the original. Or you don't hear exactly the same as the WAI file because the MP3 codec discards some of the information. Why? Because it makes the file size smaller. That's a good thing. The problem is that the quality goes down a little bit. But in many cases your human ear will not be able to detect the differences. So that's the advantage of the MP3. Basically it compresses the data. So it compresses the data and discards some what it thinks is not useful data. So that the file is small but the quality may be less. So different codecs will produce different file sizes and will have an impact really on the quality. One last one. If we save it as one more export to... Actually I've done it before. I've also got in another format of FLAC. FLAC uses another codec and the file size is about half of the original WAV, the PCM encoded. So it's 770,000 bytes. The original was 1.5 megabytes. MP3, 145 kilobytes. FLAC, 772 kilobytes. So FLAC is in the middle. It's bigger than MP3 but smaller than the original PCM encoded WAV. FLAC is just used as a different algorithm. And the key part of FLAC and other similar algorithms is that it doesn't discard any of the audio. MP3 throws away some of the audio so when you play it back compared to the WAV file it will not be the same. But FLAC is what's called a lossless codec in that it compresses the audio it compresses the WAV file effectively but it doesn't discard any of the audio. So when you play it back you'll get exactly the same audio as when you play back the WAV file. So FLAC is what's called a lossless codec. No information is lost. It's just compressed. The same as you have a large text file you compress it using zip. When you decompress it you get the original text back. Nothing is lost. That's the same as FLAC. But with MP3 if you had a large text file you'd decompressed it with MP3 and you decompress you wouldn't get the original text back which is not so good for text files but for audio it is okay because their ears may not detect the differences. So many different codecs have trade-offs in terms of file size mainly the quality of the reproduction and also sometimes the time it takes to encode and decode to compress and decompress. As well as the support of those codecs in different pieces of software and in different pieces of hardware. Any questions to finish on PCM? We're not going to talk about the other codecs else is just about PCM but I think you've used many other codecs. Any questions before we finish this topic? It's hard to demonstrate in some time to think about but the same applies for video and other sources of analog data. Video, audio, data recorded from some sensor that records temperature for example that data or analog data we can apply a codec to convert it into digital. There's a few slides here that we didn't really use but they just summarise the steps used for PCM. So really if you can follow the examples we went through yesterday then that's all you need to understand about PCM. This just describes the steps that we used. This was the sampling theorem we should sample at two times the highest frequency component of the original input data. There are variations of PCM using what's called non-linear coding. In our case we divided the space into equal sized bands in this case from 0 up to 16 each row was the equal size. That's a linear coding but you can do other things like make it non-linear that is almost like a logarithmic scale. Here we have smaller bands and as we get to the larger amplitudes we get larger bands here but that's what we'll not cover non-linear coding. There's other modifications delta modulation, modifiers, PCM we will not cover that there's a couple of slides there. PCM think is the basic codec used for audio but there are many other codecs that try to improve upon the efficiency like compress the data more PCM doesn't compress anything and also maybe sacrifice some quality like MP3 does to reduce the file size. So that brings us to the end because the other topic we've covered before the midterm in the signal encoding techniques.