The narcissist's grandiosity is a very complex, multi-faceted, multi-layered phenomenon, and that, of course, is a highly grandiose statement. But today I'm going to deconstruct grandiosity. Grandiosity is not just about saying, you know, I'm unique, I'm godlike, I'm perfect, I'm omniscient, I'm all-knowing, I'm omnipotent, I'm powerful. These are the superficial, supercilious external manifestations of grandiosity. They are more common in narcissistic style, actually, than in narcissistic personality disorder. Narcissistic personality disorder involves a lot more Machiavellianism and so on and so forth. But this in-your-face type of grandiosity, known as haughtiness, kind of multifarious arrogance, this is more primitive. Grandiosity is a cognitive distortion. It operates unconsciously, consciously, and it involves multiple biases, mechanisms, and psychological processes. And this is precisely why the narcissist is so emotionally invested in his or her grandiosity. In this inflated, fantastic self-image, because grandiosity is the core and the pivot of the fantasy defense known as pathological narcissism. And apropos pathological narcissism. My name is Sanbaknin and I'm the author of Malignan's Self-Love, Narcissism, what else? Revisited. I'm also a former visiting professor of psychology and currently on the faculty of SEAPS, Commonwealth Institute for Advanced Professional Studies, all over the globe, Toronto, Canada, Cambridge, United Kingdom, and an outreach campus in Lagos, Nigeria. Grandiosity it is. Let's delve right in. Grandiosity involves, as I said, multiple mechanisms and so on and so forth. And one of the most formidable is known as ideas of reference or referential ideation. Let me give you a few examples of referential ideation or ideas of reference, believing that somehow everyone on a bus or in a club or in a room is talking about you, feeling that people on television or radio are either talking about you or talking directly to you or somehow signalling something to you in a kind of code that is known only to both of you.  They have special personal significance for you, these world events. Believing that the lyrics of a song are specifically about you, believing that social media posts, a YouTube video is actually meant as a coded message, a cipher just between you and the author, believing that the normal function of cell phones, computers and other electronic devices is sending secret and significant messages that only you can understand, believe and decode. Perceiving objects or events has even been deliberately set up or positioned to convey a particular meaning to you, thinking that the slightest careless movement on the part of another person, a twitch, a tick has great personal meaning to you, increased significance, a kind of signalling, thinking that internet blogs, as I said, posts and so on, have hidden meanings or cult meanings pertaining to you and believing that the behavior of others is in reference to an abnormal, offensive dimension of either the personality or the body, which is reality non-existent. This is known by the way as a reference syndrome and there is, for example, an olfactory reference syndrome where you believe that people are reacting to your abnormal or offensive body odor. Okay, so these are ideas of reference. You're getting the picture. The sense that events or actions of others talking, whispering, smiling relate particularly to yourself to an extreme and when this is taken to an extreme, it is known as delusion, delusion of reference. It is the false conviction that the actions of others and events occurring in the external world, they have some special meaning or significance, typically negative but not always, in relation to yourself. So ideas of reference, delusions of reference. This leads in extreme mental illnesses such as schizophrenia. This leads to what is known as a referential attitude. It is an expectancy attitude, anticipatory attitude that is sometimes observed, as I said, in severe psychotic disorders where you seek justification via the environment for ideas of reference or delusions of reference. So you misinterpret, the patient misinterprets the environment, rewrites it, reframes it. And now we are beginning to see the first nexus, the first connection between grandiosity and ideas or delusions of reference, a misinterpretation, a misreading and a falsification of the environment and impaired reality testing. But grandiosity involves a lot more than referential ideation. The grandiose person does believe that he or she is the center of the world, the focus of attention, the life of the party, the pivot and the axis around which everyone revolves, the prime cause and the only cause for other people's states of mind including their unhappiness or happiness. There is this godlike persuasion that one is the mover and shaker of one's world and one's environment and depending on the level of grandiosity, it could even devolve into paranoid ideation and expand hyper reflexively, expand to include the world at large, including world events, as I mentioned earlier. So this all is part and parcel and element and figment of grandiosity, but there are other things involved. The first is what I call, and yes I'm coining another phrase again, what I call object apophynia. Apophynia is a tendency to perceive meaningful connections between totally unrelated things.  So conspiracy theories, for example, are a form of object apophynia and especially if you're paranoid and you believe there's a conspiracy against you, that you are the target or the mark or the victim of malevolent intent and malicious actions on behalf of one or more group of people, that is object apophynia. When you see connections where there are none, tendency to perceive meaning where there is none and so on and so forth. So when apophynia has been defined by Klaus Conard in 1958, he said that it is the unmotivated seeing of connections accompanied by a specific feeling of abnormal meaningfulness, and that's still the greatest description of apophynia that I'm aware of. Apophynia is, of course, one of the antecedents, one of the first stages of delusional disorder. It's a delusional thought pattern. It's a kind of self-referential over interpretation of actual sensor, actual sensory inputs. It's not a hallucination, it's just a misinterpretation and mislabelling of information that emanates from the environment and it is delusional and it is self-referential and it is very common in grandiosity. It's a human propensity to unreasonably seek definite patterns in random information and I call it also social pagedolia. Pagedolia is the tendency to perceive or impose a meaningful interpretation, some significance on a stimulus or a series of stimuli, visually usually, but not only, and in order to extract or to come up with some pattern or some meaning when there is none. So pagedolia is a subtype of apophynia and when you combine object apophynia, apophynia that applies to all objects, objects, animate and inanimate. When you combine this with social pagedolia, the tendency to see patterns of behavior, coordinated patterns of behavior when there's none, for example, conspiracy against you. When you combine these two, what you get is all forms of grandiosity, one of which is, of course, paranoia. Paranoid ideation is grandiosity.  They are to get him, they are to destroy him, to incarcerate him, to arrest him. He is the focus of attention. He is the pivot and the axis around which everyone revolves with a malevolent intent, but still revolves. Grandiosity, therefore, is when you see patterns either among objects, animate and inanimate, when you see, when you combine objects in ways that make sense to you, but to nobody else, only to you, or when you see patterns in behaviors of people which make sense, these patterns make sense only to you. So, object apophynia and social pagedolia, these are strong elements, powerful elements of grandiosity because the grandiose person, even when he is not or she is not paranoid, the grandiose person fully believes that objects in the environment, and remember that in psychology, most objects are human beings. Human beings in psychology are called objects. The grandiose person, even the non-paranoid grandiose person, regards objects in the environment as arranging themselves. He believes that objects are arranging themselves in order to send a message to him, to yield the signal, to make sense of his self-perception or self-image, to support and buttress his fantasies, etc., etc. Objects around the narcissist are there to fit into the narcissist's self-idealization and or shared fantasy. That's their role because the narcissist is unable to perceive objects as external. He introjects objects, he internalizes objects, he converts external objects, including people, into internal objects. He then tries to make sense of this zoo of internal objects by imposing on these objects a narrative, a storyline, a piece of fiction which upholds, buttresses, supports and enhances his self-perception and self-image as godlike. This is object apophynia. Another element in grandiosity is social paredolia, when the narcissist attributes motivations, planning, intentions to one or person or a group of people. And these motivations and intentions and plans and actions, they all revolve around the narcissist. Okay, so this all had to do with the narcissist's inability to other, othering failure. Remember that the narcissist, because he, the narcissist has never experienced separation, individuation as a child. The narcissist is unable to perceive other people as external and separate. It does not perceive the externality and separateness of objects, of external objects. Instead, he converts external objects into internal objects in his mind and continues to interact only with internal objects, never with the external objects. This inability to other, inability to regard other people as other, as out there, as external, as independent of the narcissist's existence, perception, cognition and so on and so forth.  And it has to do with a concept introduced by George Herbert Mead. He called it the generalized other. It's part of a larger topic known as symbolic interactionism. Never mind, I will deal with it in some other video, but the generalized other is the general notion that there are expectations that are common to all people, kind of social expectations. So all of us have a generalized other perception. We believe that other people have expectations about actions and thoughts. And so we try to conform to these expectations. We also believe that these common expectations serve to clarify relationships between people. So when you are a member of a social system, you comply with these social, society-wide expectations, and this determines how you relate to other people and how you behave. And in your mind, there's this faceless, anonymous, generalized other. And this imaginary person kind of dictates your behaviors and your faults, your cognitions, in accordance with elements of socialization and acculturation, in accordance with societies, norms and mores and expectations and so on. So all the time we walk around asking ourselves what is expected of me, taking the perspective of the generalized other according to Mead at least. So this is also known as imaginary audience. It's a constructed audience. And this audience doesn't have complete insight or complete information about the individual, but the individual measures himself or herself in accordance with the imagined audience. Imagined audience dictates to some extent who the individual is. Now the narcissist, because he has a problem with othering, does not have a generalized other. The narcissist does not ask himself or cannot ask himself, what are the expectations of others of me? What do others expect of me? How do they expect me to think? How do they expect me to behave? The narcissist is incapable of asking this question because he doesn't perceive others. He doesn't really relate to external objects. So he cannot ask himself, and he does not ask himself, what do others think of me? How do they think I should behave? How do speech acts, anything, actions, choices, decisions, I need to conform. The narcissist doesn't say this because the narcissist is an othering failure. And all the narcissist's objects are never external, they're only internal. The only generalized other in the narcissist's mind is the narcissist. The narcissist is the measure of all things. The narcissist is the source of all expectations about cognitions, about actions, about choices, about decisions, about behaviors. The narcissist is the only law. A law unto himself is the only rule. The only rule book is the rule book written by the narcissist. The narcissist is solipsistic. He is the only person who exists in the entire universe. So the only source of found of expectations is himself. Since he does not perceive other people as out there, they cannot have expectations of the narcissist. They cannot impose on the narcissist, meaning they cannot dictate and direct the narcissist's choices, decisions, and actions. They are not there, out there. There's nobody out there. They're all in here. They're all in the narcissist's mind. So the narcissist self-referes. He is self-referential. He refers to himself in order to derive meaning and sense expectations and directions, behavioral codes and scripts. Everything emanates from inside the narcissist, never from outside, owing to othering failure. This applies even to sex. The narcissist is auto-erotic. He is attracted to his own body.  In short, he is masturbating with someone else's body. So this is a very important thing to realize because the narcissist's referential ideation, the narcissist's social expectations, the narcissist's perceived behaviors, perceived behaviors of other people always come from the inside, never from the outside. So this creates a lot of dissonance. For example, imagine that the narcissist develops a conviction that there is a conspiracy against him. This conspiracy cannot be linked in the narcissist's mind to external objects. It's a conspiracy of the internal objects representing these external objects. It's a conspiracy inside the narcissist's mind. The internal objects that represent the people who want to harm the narcissist, these internal objects are in collusion against the narcissist. It is as if the narcissist is conspiring against himself via the agency of other people, exactly as the narcissist is having sex with himself via the agency of other people's bodies. He is conspiring against himself via the agency of other people's minds. They don't really exist except in his mind. So this creates a lot of internal conflict and a lot of dissonance. And this is the reason the narcissist is compelled to seek narcissistic supply. Narcissistic supply is a compulsion. It's an addiction. It is intended, the narcissistic supply is intended to ameliorate and mitigate this internal conflict, to reduce it somehow. When the narcissist obtains narcissistic supply from the environment, attention, adulation, admiration, even when he is feared, when he is noticed somehow, when he is seen by the environment, that reduces the internal conflict because this validates his grandiosity. A narcissistic supply is like telling the narcissist, you're not delusional, you're really a genius, you're not crazy, you're really great. The narcissist feels validated via narcissistic supply and begins to trust his internal world and his own cognitive distortions. Narcissistic supply is like telling the narcissist, your cognition is not distorted, it's perfectly okay. You're not wrong about yourself and about the world and about the environment. Your internal working model is in perfect order and this is compulsive because the conflict inside the narcissist is ongoing, it's sempitonal and it needs, it requires quelling and mitigating all the time. Now, of course, grandiosity involves biases, not only cognitive distortions but cognitive biases. For example, a confirmation bias, the tendency to search for, interpret, favor and recall information only in a way that confirms and supports one's prior beliefs and values. So the narcissist's bias, narcissist's belief is that the false self is not false. The narcissist believes that his inflated, fantastic, grandiose self-perception is accurate, reflects reality and so he needs to filter out to deny, to suppress, to eliminate all information and data that may challenge and undermine this belief, this self-image, this self-perception. So he creates his own echo chamber, thought silo, into which he lets in only information that supports his grandiosity.  The narcissist filters out, literally, forgets, dissociates, information that somehow threatens the validity, the cohesion, the coherence and the longevity of his grandiose, inflated self-image and self-perception. Narcissist selects information that supports his views, his interpretation of the environment and of himself. He ignores contrary information. He interprets ambiguous evidence as supporting his existing attitudes. There are desired outcomes for this, emotional outcomes and other outcomes. Confirmation bias is very entrenched even in healthy people, not in the narcissist. It's a precondition for survival. In modification, all these mechanisms collapse. It's a process known as decompensation. So in modification, public humiliation, the narcissist defences, the narcissist biases, the narcissist errors, cognitive errors, they all collapse. They're all deactivated. At that point, the narcissist comes face to face with who he really is, pretty inferior. He understands his narcissism is compensatory and fallacious. It's a lie. The false self is false. It's a horrible feeling. The narcissist becomes essentially a borderline. There are various forms that are fully functional narcissists, various forms that such a narcissist, not a high-functioning narcissist. A high-functioning narcissist is a narcissist who functions well in society, fully functioning narcissist. In other words, a narcissist who is narcissism is in action and unimpeded and unobstructed by anything. Such a narcissist uses several forms of confirmation bias. There is what is known as attitude polarization. When a disagreement becomes more extreme, even though the different parties are exposed to the same evidence, there is belief perseverance when beliefs persist after the evidence is shown to be false. Irrational primacy effect, a greater reliance on information encountered early on than later. And inusory correlation, when people falsely perceive an association between two events and two situations, which is a form of apophynia or paretolia. Now, narcissism is characterized according to the diagnostic, the statistical manual by antagonism. Narcissists hold other people in contempt. Contempt is a precondition both for grandiosity and for sadism. So people, narcissists are hostile, they're antagonistic, they're in your face, they're very low on agreeableness in the five-factor personality model. And so their attribution biases, their cognitive biases are likely to be hostile. And this is known as a hostile attribution bias or a hostile attribution of intent or a hostile attribution error. It's a tendency to interpret other people's behavior as having hostile intent, even when the behavior is benign or ambiguous. So someone with a hostile attribution bias would see two people talking or laughing and he would immediately interpret their behavior as if they were laughing about him, mocking him, gossiping about him, even though the behavior in this particular case is either benign or ambiguous. Now the term hostile attribution bias was first coined in 1980 by Nassby, Hayden and DiPaolo. And together with other scholars such as Kenneth Dodge and so on and so forth, they spotted this kind of defenses, hostile attribution bias, in children. Children are of course highly narcissistic. We cannot diagnose narcissistic personality disorder in children. But as even Freud had observed, children are narcissistic. They have primary narcissism. And so it's not surprising that most children have hostile attribution bias. It's a bias in social information processing. So individuals perceive interpret and select responses to situations. And when they perceive them as hostile, we have this kind of bias. And this is what's happening to the narcissists all the time. And when you have this across the development, across the lifespan, when you don't succeed to get rid of it after childhood, when hostile attribution becomes your style, your personality style, you're likely to be aggressive. You're likely to externalize aggression, either verbally or physically. This would go a long way towards explaining why narcissists are so abusive. In the process of devaluation, the narcissist doesn't only de-idealize you. Devaluation is not only about saying, oh, I made a mistake, oh, you have changed. And now you're not as ideal as I thought you were. No, that's not the case. In the devaluation phase, you're converted into an enemy, a per-secretary object. And that's because the narcissist attribution bias is hostile. It's the world the narcissist engages in a primitive defense mechanism known as splitting. You're either all bad or all good. In the idealization phase, you're all good in the devaluation phase inevitably. Ineluctably, you're all bad. And this has to do with hostile attribution bias. It's founded on splitting in effect. It's an important pathway through which other risk factors, such as peer rejection or harsh parenting, lead to aggression. So we know this is the case with children. And I've been saying all along that narcissists are children. They remain stuck at a very, very early age. And so their hostile attribution bias never goes away. It explains how the narcissist aggression develops. Why is he abusive? Then represents a kind of targeting mechanism, victimizing mechanism, which is totally automated, totally automatic. Back to ideas of reference and delusions of reference. How do they come about? The scholarship is the orthodoxy, what we teach in university and so on and so forth, is that people who experience innocuous events or mere coincidences, and then immediately after that something bad happens, they tend to create a linkage between these innocuous behaviors and coincidences and the bad adverse outcomes. They also begin to develop the conviction that this is personal. It has personal significance. Of course, this should and does happen multiple times.  If a child is exposed to this kind of continuous abuse and trauma, the child is going to create a linkage between behaviors and bad outcome, parental behaviors and bad outcomes. And of course, this is about the child. The child is going to personalize this rule of thumb, this heuristic, the notion that everything one perceives in the world relates to one's own destiny, usually in a negative and hostile manner, because that's what the child, the abused and traumatized child has learned.  So it's very common, more common than we know. Now in psychoanalysis, and I will dedicate a special video in the future to the psychoanalysis analytic view of ideas of reference, because it's a very fascinating view. According to Ziemann Freud, delusions of being watched present this power in a regressive form, thus revealing its genesis. Voices as well as the undefined multitude are brought into the foreground again by the paranoid disease, and so the evolution of consciousness is reproduced regressively. So according to Freud, this involves regression, infantalization, and some kind of paranoia, which are both very common and very pertinent and important clinical features of narcissism. Carl Jung, Freud's contemporary disciple and then adversary, wrote in 1928 that ideas of reference have something to do with synchronicity, meaningful coincidences. When people are exposed to synchronicity, some of them develop ideas of reference. Autophynical in 1946 concluded that the projection of the super ego is most clearly seen in ideas of reference and of being influence. Delusions of this kind merely bring to the patient from the outside what his self-observing and self-critical conscious actually tells him. And how can we end without mentioning my doppelgänger, my twin, Jacques Lacan. We look identical by the way, look him up. Jacques Lacan, L-A-C-A-N. He regarded ideas of references linked to the unbalancing of the relation to the capital other, to the big other, and the radical anomaly that it involves, qualified improperly, but not without some approximation to the truth in old clinical medicine is partial delusion. The big other, the other of language, the names of the father, the signifier of words later, which later become the unconscious, actually the realm of the super ego and the unconscious. Okay, I promised a separate video about all this. There are other views of ideas of reference which I will deal with in this video. I'd like to mention a few of them. Anti-psychiatrists such as David Cooper, R. D. Lang and so on, they actually used ideas of reference as a therapeutic tool, as an instrument in the arsenal of healing. They regarded the patient, I'm quoting, the patient's ideas of reference and influence and delusions of persecution are merely descriptions of the patient's parents' behavior towards her. This happens to be my view as well. There is certainly confusion between persecutory fantasies and persecutory realities, but ideas of connection with apparently remote people, or ideas of being influenced by others equally remote, are in fact stating their experience of social influence, albeit in a distorted form, including their network of influence institutions as absurd as Scotland Yard or the Queen of England or the President of the United States or the BBC. So what they are saying, the anti-psychiatrists, is that ideas of reference are an attempt to act within society, to somehow integrate with society or even conform to society, but this attempt fails for two reasons, hyperreflexivity, the tendency to regard the whole universe as relevant to the individual, including the Queen of England or the BBC or the CIA, and on the other hand, a bad parental experience which predisposed the individual to associate behaviors, actions, choices, decisions and language, however innocuous, however benign, with negative adverse hostile outcomes, because this is what the individual has learned in his relationship with his parents. Lang shared David Cooper's view. He said that the person who was saying that his brains have been taken from him, his actions are controlled from outer space, such delusions are partially achieved derealization realizations. He considered how in typical paranoid ideas of reference, the person feels that the murmurings and mutterings that he hears as he walks past the street crowd, they're all about him. In a bar, a burst of laughter behind his back is at some joke cracked about him, but he felt Lang believed that deeper acquaintance with the patient reveals that what torches the patient is not so much the patient's delusions of reference, but his harrowing suspicion that is of no importance to anyone that no one is referring to him at all, which is the bed object core, the empty schizoid core of the narcissist, and to some extent the borderline. This is the driver. The narcissist suspects that he is not being seen the way he has not been seen by his parental figures, so the narcissist is compelled to force people to see him. And if he fails to force people to see him in reality, because they don't exist, that he is incapable of interacting with external objects, then he is going to force people to see him in his own mind because they do exist as internal objects inside his head. So the narcissist enacts a monodrama or a drama where the internal objects inside his mind that represent real people out there, they do see him, they do pay attention to them, they do notice him. However, in most cases in a hostile negative manner, but not always. Again, we must distinguish ideas of reference from delusions of reference. They are similar in content, but the difference is the conviction. Delusions of reference involve utter conviction. The person in the former case, in the case of ideas of reference, has the feeling that strangers are talking about him or her, but if he is challenged, he acknowledges that the people may be talking about something else. The person with delusions of reference would never admit to it. No way they are talking about him. He knows it somehow. You can transition from ideas of reference to delusions of reference, and this happens very frequently in narcissistic modification. After narcissistic modification, the narcissist develops delusions of reference. He becomes delusional, which is much more typical of borderline than of narcissism. And so abortive ideas of reference, I'm quoting, abortive ideas of reference in the beginning of the development or in schizotypal personalities, continuously may remain subject to the patient's criticism. Under adverse circumstances, by minimal economic shifts, however, reality testing may be lost and daydreams of this kind turn into delusions. A person rigidly controlled by his super ego readily forms sensitive ideas of reference. A key experience may occur in his life circumstances, and quite suddenly these ideas become structured as delusions of reference. Within the focus of paranoia, that man crossing his legs, that woman wearing that blouse, it can't just be accidental or coincidental. It's a message. It's a signal. It has particular meaning. It is intended to convey something. In many ways, the narcissist is delusional. He believes the environment and the world organize themselves around him, around his self-perception and self-image, and around his needs. Because he is envious, he projects this envy onto others and assumes that they are as envious of him as he is envious of them, that they are as malevolent as he may be, that they are as, that they're engaged in some conspiracy against him to destroy him. Similarly, the narcissists may group together sources of narcissistic supply, idealize them and convince himself that they spend their time talking about him, admiring him, adulating him, and so on and so forth. Both are types of ideas of reference which base themselves on apophynia, paradolia, and a total utter failure of othering, of perceiving people out there as external, separate individuals. The narcissist enacts a narrative totally confined to his mind. He's a prisoner of his own mind. Everything is happening in his mind. The whole theater production, the whole movie unfolds and unfurls exclusively within his mind. Nobody is out there. This perhaps is the most terrifying thing of all. This perhaps is the cause, root of narcissistic defenses. It's the desperate attempt to have object relations with internal objects rather than with external objects, knowing somewhere unconsciously all the time that you're all alone, that there's nobody out there and there's nobody in there, because if there are no external objects, what do these internal objects represent? Nothing. Nothingness. This is the core and the psychodynamic engine of the narcissists and borderlines emptiness. The inability to recognize external objects in the case of the narcissist leads to the generation of internal objects, which are highly dubious, because again, what do they refer to in the absence of external objects? So suddenly, the narcissist is faced with a compulsion, with the need to generate an entire new world of which he is the ruler and the godhead, so as to avoid the profound existential loneliness of the black hole and the void of the emptiness and the absence that is.


Calories in, calories out, aka CECO, is the conventional wisdom, you know, what is generally accepted behind weight loss, and it's the first thing pseudo-intellectuals jump to when discussing weight loss. Whether it's telling you, just count calories, bro. Make a healthy recipe that's just healthy because it's so low in calories. Bodybuilders and keto dieters trying to make cheat meals praising artificial sweeteners. Dude, it's low in calories. You gotta try this. CECO might help some people lose weight, but it will not make you healthy. The only way to be healthy is to optimize all lifestyle factors, and for diet, that involves restoring nutrient deficiencies and removing negative foods. Whatever you want for your appearance, physically, it will come once you become healthy. Don't focus on the goal, focus on how you're getting there. CECO is based around body input and output. Is your body's output, the metabolic rate, activity level exceeding the input, the amount of food you're consuming? And is that really correct? You know, we've seen carnivores improve their body composition without reducing calories, without losing your gaining weight.  People even see people reduce their calories and they'll still gain weight or follow incredibly calorically restricted diets and still have difficulties. So there has to be more to it than calories in versus calories out. In the case of carnivore versus vegan diets in body composition, the absence of animal protein and cholesterol in favor of high carbohydrate estrogenic plant foods are two factors that have absolutely nothing to do with the caloric content of the food. Two factors that will greatly influence your ability to gain or lose weight, fat or muscle mass. CECO is debunked fairly easily on the basis that macronutrient composition in the diet matters just as much as calories. The protein, fat and carbohydrate ratios you're consuming are just as important if not more important than the calories. If it was macronutrients in, macronutrients out, MIMO instead of CECO, we would have a more difficult argument but we can still debunk that later. And keep in mind, I'm not discounting calories as an important component of diet but it's definitely overblown. It's something I've never counted or really seen as a priority. I've never done it myself, I've never recommended it with my clients. And by oversimplifying diets and calories, you're causing people to not think and address their underlying health issues. Comparison of energy restricted, very low carbohydrate and low fat diets on weight loss and body composition in overweight men and women. This study shows a clear benefit of a very low carbohydrate diet over a low fat diet for short term body weight and fat loss especially in men. A preferential loss of fat in the trunk region with a very low carbohydrate diet is novel and potentially clinically significant but requires further validation. These data provide additional support for the concept of metabolic advantage with diets representing extremes in macronutrient distribution. You have two factors when going low carb regardless of caloric restriction. An improvement in insulin resistance as well as a potential die off of negative gut flora. Also, I have to consider that those higher carbohydrate foods have more processed crap and chemicals in them that can further metabolic issues. Calorie intake in relation to body weight changes in the obese. So this study compares three diets, one being 90% fat, one being 90% protein and the final one being 90% carbohydrates, so each of the macronutrients basically on their own. When calorie intake was constant at 1000 per day, however, the rate of weight loss varied greatly on diets of different composition. It was most rapid with high fat diets. It was less rapid with high protein diets and weight could be managed for short periods of time on diets of 1000 calorie value given chiefly in the form of carbohydrate. At a level of 2000 calories per day, weight was maintained or increased in four out of five obese patients. In those same subjects, significant weight loss occurred when calorie intake was raised to 2600 per day provided this intake was given mainly in the form of fat and protein. As the rate of weight loss varied so markedly with the composition of the diets on a constant calorie intake, it is suggested that obese patients must alter their metabolism in response to the contents of their diets. The loss of water weight is from insulin levels reducing. So not only are they losing weight, they're addressing metabolic diseases, improving their hormonal status and you can't discount that the people on the high protein diet probably gained more lean body mass. So the fat loss should be magnified there. It's not just a matter of losing physical pounds. How much muscle are you putting on and how much muscle are you losing in something like the case of a vegan diet? This study shows that calories in versus calories out is incorrect because the person was eating 2000 calories with carbohydrates maintaining if not gaining weight but when the calories were increased to 2600 of fat and protein, they lost weight on more calories. Once this becomes accepted and common knowledge, people will start looking deeper into nutrition, vitamins, minerals, fatty acids, as well as negative aspects such as antibiotic residue and agrochemicals. To address each of these factors on an individual basis and explain why they are concerned to the average person usually falls on deaf ears. You know if the person cannot understand or seek the information in the first place, they typically won't care enough to take action as it's a step out of their comfort zone. Plus, a person usually believes that what they're doing is working just fine. Yeah, let's see if your PP works just fine after a year of estrogenic feedlot beef on the carnivore diet. A good analogy for this is someone following a grass-fed organic local carnivore diet versus a feedlot beef carnivore diet. The person on the feedlot beef diet is going to be getting so much more estrogen, omega-6 fatty acids, their testosterone will tank, various hormonal pathways will dysfunction, endoconibinoid system, and they tend to become insulin resistant and store weight around their guts. Simply due to the estrogenic agrochemicals like the herbicide atrazine found in feedlot meat. This is partially where keto dieters tend to still have signs of insulin resistance because they eat very low-quality foods that have those negative chemicals. The herbicide, the pesticide, insecticides, fungicides, and antibiotic metabolites in the food. Then, when you look at paleo dieters or higher quality carnivore dieters, people who focus on food quality, they tend to have more favorable body compositions. So hopefully this opens up the minds of some people that you shouldn't worry about calories too much. And if you guys do have any further questions, let me know down in the comments. If you guys could please drop a like on the video. And if you can share it on social media. If you do want to support me further, you know how to do so down in the description. Thanks again for joining me today guys. I'll see you for tomorrow's video.


Well hello there, Mark Risen Hopkins here, coming at you once again from Google IO 2013. I'm here with the guys from MapR. We're going to talk about a lot of interesting things that from both this event and last year's event, because last year's event was so awesome, we're still talking about it. And some new things that are kind of in the cloud war space, broadly about Google Compute Engine, which they are a participant in as well. So let's just start off, last year at Google IO, this event, you did this amazing demo in which you demonstrated the difference in cost between deploying on Gridiron or for, I'm sorry, I should say for a MapReduce operation on doing on bare metal versus using Google Compute Engine. And the difference in cost was amazing, very stunning, made lots of headlines. So let's refresh people's memory on that, and then we'll move on to what's coming up this year. Yeah, so one of the things that we showed last year at Google IO was actually our ability to leverage Google Compute Engine in Google's cloud. What we were able to demonstrate last year was the ability to sort a terabyte worth of data and how fast you can sort one terabyte worth of data. The numbers were astonishing. We were able to break the existing world record that was actually there. We were able to crush that record by doing it, I think with a third less cores, half the CPUs that are actually needed. It was an amazing achievement number for us. And really, when you looked at the cost, I think it was like three to $6 million or what it cost you to do it on real equipment. And I think we got it down below $20 to go ahead and do that processing. And so it was pretty amazing. It was a really big buzz as we were really launching and kind of getting computing out out in limited preview and getting customers on it. So in this year, you're kind of demonstrating some stuff with a client of yours named RAP. Very interesting, you've got the demo running behind you, a real-time live demo. So talk about what you're doing there or what you and RAP are doing there. It's very interesting, it's actually very cool to kind of see the little tag clouds form in real-time there. So what are we looking at here? So really what you're taking a look at is real-time data or stream processing of the data. We were looking at it for the MacBook timed out there. We'll talk about it for just a second while we wait for the computer to come back. We're doing real-time processing of the data. So taking real-time from actually a gaming application and what it's doing is it's pulling in user information. What are the actual users doing across the data? Who are the most active users on the game? And what it's pairing it to is what the actual user is doing. So it's an actual online game where there's, people are making moves, getting weapons, et cetera. And what you're able to take from this data is, as a developer, are my seeing errors? Am I seeing lots of logouts of a user? Maybe I have an issue with my gaming application or maybe there's a monetization play. Maybe I want to offer them a new weapon or something that they use as part of the game to kind of entice them to actually use something. So be able to find gaming pain points in real-time. Pain points in real-time and what they're actually doing. So it's a real-time demo as we're really starting to see this shift from a Hadoop standpoint as Hadoop's really kind of been regulated to more batch-based processing. It's now moving more towards real-time and stream-based analysis. And this is one of the demos that we've done to kind of show what we're doing there. Right. So it's very interesting. Maybe we'll get some B-roll here in a second of that and splice it in. But I also want to talk about, and this is a big topic right now kind of in the blogosphere. Everyone likes to use the word cloud wars. And you guys have a foot in a lot of different worlds, different clouds, obviously with Google Compute Engine. Of course you work with the other clouds as well. So talk a little bit about your perspective because first of all, is it a war? Is it not? Is it a war? Is it just new supercomputers coming online at different speeds? Yeah, I think it's really more of a second. I'm not sure if it's a war and really as you look at it, the space is huge. It's really, in some respects, really green-field in a lot of cases. So I'm not sure if it's really kind of hand-to-hand battle. It's really kind of out there. Who can get in front of the most customers fast enough? There's some customers that are going to prefer Google's cloud that are using storage, BigQuery, et cetera. And they're going to prefer other clouds. And I think it's really, for the cloud providers that can provide the most dynamic services and the most sticky services to their end users are going to want to capture the customers. And I'm not sure if you're going to be able to find a de facto winner and loser, but I think really who wins in this is actually the consumer or the business who's actually getting these services. Because as more and more competitors come into the space and as more and more providers, the cost of those services actually come down over time. So it's only going to be a benefit to both the consumer and the business. So Wikibon Analyst, Chief Analyst Dave Vellante, likes to use the phrase, horses for courses to kind of describe a lot of different things in storage and enterprise. And I think what I'm personally gathering, and maybe you can tell me if you agree or disagree from talking to different partners within the Google ecosystem, is that there are certain places where like Amazon is far ahead and shoulders above where Google Compute Engine is. Specifically, I like in areas of maybe like video processing in the cloud or kind of specialized tasks where they've just had Amazon's got a lead, right? They've been around doing it longer and offering it as a service. And then there's other places where Google has focused on hyperscale for web application, mapping MapReduce, obviously a pioneer in that space too. So I guess the question I have for you would be, so how do you feel BigQuery stacks up against the competition in the other hyperscale players? Is it a head and shoulders winner? Is it a comparable like feature set for feature set? Where is it in kind of the hierarchy or the ecosystem? You know, I think it's more of an in-user question. I mean, as a partner, we understand how to interact with BigQuery, but I don't think we see it from that standpoint. So I'm not sure if we're probably the best to comment on kind of whether BigQuery's heads and tails above the rest, but I think one of the things that we've seen with our customers that are actually using us is, having that in-to-in data pipeline really matters. So being able to take services from like Google App Engine, being able to do log file analysis, leveraging MapReduce to go ahead and do that, and then have that being processed from BigQuery, I think makes a lot of sense. And I think in other clouds that have similar type services, providing those high-end services or enriched services to your end users really matters. So I don't know if one's a de facto leader or one's heads and tails above the rest. I think some of it also depends on the customer use case and what they're using and where their data is. One of the things is part of it is your data lives in the cloud, and so some of it could just be where your data lives at the moment and who's providing you the services that you need. And who's your neighbors, right? Which cloud is your neighbor's data in? So last question, because we're running out of time, but I do want to ask, I've got this friend of mine. I go to every once in a while. He works for a very large bank that many of us use. I won't say the name because he doesn't like it when I do that on air. But I talk to him, because he's getting into Hadoop. They've been dabbling with big data for a number of years, but being a large bank, they've got, of course, restrictions and red tape internally. But I showed him the announcement from last year. Look at how much money, because they're building their own, like their own Hadoop servers in-house. Look at this thing, you can save millions of bucks. But it comes down to security, security, security. And being that the public cloud is a nascent field, how do you see the progression for financial sector? Is that their adoption is obviously going to be much slower than perhaps other sectors of the enterprise? Where are we in that? Is that particular very large bank alone in that, or are the other banks kind of coming along more quickly, or is the whole sector going to lag? Well, I think overall security needs to be addressed. And I think that's one of the things that kind of goes back on the shoulders for the big cloud providers, be it Google or any other cloud providers, security's got to be addressed. And especially when you look at financial services or healthcare organizations with HIPAA and PII information, I think those are definitely going to be addressed. And I think there's going to be two ways in which those are addressed. One is they're going to specialize clouds, maybe for financial services, like FISR of clouds, et cetera, same way that some of the cloud providers do for the government, or they may actually have to just put in strict regulations across all of their cloud-based properties and say, come on, come on, but it's going to be super secure. So I really kind of see that playing in strongly with the cloud providers. I think it's a question of kind of where we are in that adoption curve. For those folks, I still think we're early, but for a lot of these new technologies like Hadoop, we're still early in that process, but we're starting to see a lot of interest because having large amounts of data and to be able to have unlimited, or seemingly unlimited processing power to process that data at fractions of the cost, I think could be huge over time. The power is clear. And for my friend and his organization, the hurdle is simply just getting past these 1990s-style bureaucratic regulations about what you can use and what it's considered secure. So I would tend to agree from my experience with your assessment. It's just one of those things that's going to have to come along. So yeah. So yeah, I appreciate your time. There you go. I appreciate your time. And we're going to be bringing you more and more coverage from the floor of Google I-O 2013. Stay with us, and we'll be back soon.


Hey everybody, I'm Lance Goyke. Today, we're discussing the third basic principle of training that I wanna talk about in our how to write a workout playlist thing that we got going on here. And this third principle is individuality. And that just means everybody's different. So, you know, in our first video, I kinda talked about how writing programs can be really complicated if you're a trainer and you work with a bunch of different types of people. Like some people have autoimmune diseases. Some people don't sleep very well. Some people are very type A. Some people are naturally lean and muscular. Some people are naturally not. Everybody kind of responds to things differently. Everybody requires a different diet, responds to different exercise reps and everything differently. People just have, you know, skinny frames versus long frames versus stocky frames. All of that stuff comes into play here.   It's crazy.  And so with my frail little nerd frame, like my soft tissue is gonna buckle, but you give that type of broad area to somebody who's 360 pounds and yeah, that's how they can be 360 pounds and live comfortably or kind of comfortably throughout the day. And that's how they can squat a thousand pounds because they have that surface area to disperse forces. What else? Like you'll notice some people, I'm training one guy who is naturally very athletic. So he does really good at fitness challenges in general, but he is definitely a type two fiber kind of dude. He is definitely a strength and power type of athlete. And right now he's training for a marathon and he's starting to see like, he's really good at doing his trap bar deadlift, especially for being kind of tiny. And his marathon times are very respectable, but he's definitely fighting a different battle, right? He doesn't have the cardiovascular capitalization, blood supply kind of stuff and other associated adaptations that just come naturally to some other people like, for example, Lance Armstrong or somebody else who's really good at doing long distance stuff. I think that's it. That's individuality, everybody's different. That's how we summarize things. Make sure that if you do end up writing programs, not just for yourself, but for other people as well, make sure you take that into account.


Today's unboxing is really fun. This is the Visconti Devena Daria Argento limited edition fountain pin release it comes with two full-size bottles of ink and They're in beautiful ink balls with the Daria Argento signature on the top of the cap there in red and it's going to be a red ink and a black ink and this Limited edition collection is inspired and in celebration of the career of Daria Argento He's an Italian cinematic maestro, and he's best known for his works of deep red Suspiria and the bird with the crystal plumage He's basically known around the world as the master of thrill his movies are full of mystery and terror and they're Known for presenting reality as being deceptive with depths that reach far below the surface anyway, so that is what they're trying to bring to life here in this pin release and I think they did a good job They've got this beautiful Devena pin model design as the base, and then they went ahead and incorporated these different shades of really really deep red and mauve the Visconti's in-house 18 karat Gold ruthenium plated nib is partnered with a pull-in-turn piston filling system and hope you're able to get a good look at how well they did combining the iconic Davino with that shimmery bardo and the black acrylic swirled resin that is Said to resemble a puddle of blood fading into darkness. You have red carnelian stone in the finial there You also have the pins sterling silver threads that are applied by hand One by one along those twisting edges of the pin design the pins finished with sterling silver and ruthenium plated trim And it's limited to 50 pieces visit pinch lay calm for more info


sso with the GPU. You already know how to do this because we are doing exactly the same operations that we did for CPU. So we go to the Cineca scratch directory. We go inside exercise four directory. We download this version of quantum espresso. You see that in this case, we are downloading the GPU version of quantum espresso. For this answer, we use the version 6.7 in which the CPU and GPU repositories were still kept separated. But in the newer releases, you will find that the code has been merged. So there will be in the future time, there will be one repository and you will download one unique source code that can be compiled with both GPUs and CPUs. But at the moment we still rely on deep quantum espresso 6.7. So you can download this version of QE. You can start this file here. This is the same operations you have done for CPU installation. You change name to directory for your convenience because here the name is more clear.  We see that we are still loading the same modules as before up to here. So HP CSDK where Mv4 is included. Spectrum MPI for MPI parallelism, FFTW because these are the FFTs we are using. Here a question called the rise. Let's see. And a CUDA here because this is the real difference between CPU and GPU environment setup because CUDA allows us to really use GPUs. So once you have done it, you have loaded these module files, you can run configure. And we see that in this case, the configure command is a bit more complex because we still have this PGII filter and basically we are telling to use the import for the inter compiler. But here we also enable OpenMP which we did not do it before. And we are specifying that we are using CUDA. We are using CUDA 11.0 because this is the module that we loaded here. And we are using our GPUs here have a compute capability of 70. This number is given depends on the hardware. And so it depends on the GPU you have the underlying GPU core that you have. In this case, Marconi is provided with the Volta 100 GPUs and they have a computational capability of 70. So maybe older versions of GPUs might have lower values 60 for that. And then the following newer version, I guess they will have a higher compute capability. You run the configure and you check here again that all values have been taken. I can do this now. So we I go in exercise four here. I first purge module purge. So now I ensure that I have no modules here that would interfere. Then I copy the modules here. So HPCSDK, spectrum, FFTW CUDA module load. If I list them now, I see that they have been loaded. I run configure in this way. And I'm configuring my version of GPU. Yes, my version of GPU version of Quantum Express. So I think, yeah, here we have a good question. I didn't find the FFT leaves. So is that because cool FFT is not in Marconi and will be internally compiled? Yes, we will talk a little bit now about this. I guess it is going slow because everyone is doing this configure now, I hope. So could you please raise your hand? Now many of you are now configuring the GPU version of QE. Could you please raise your hand so I can say I can see. Okay, so 15, 17, good. Okay, we have about 20 people configuring. That's great. So I can, usually it is much faster now. Of course, we are many people running on the same node. So okay, now my configure has finished. So you can see blast leaves here because of course it found the blast leaves. And here we see again that LAPAX. So these two together are for linear algebra. And here we see that these LAPAX leaves have been taken from HPCSDK. So we are using internal libraries from MV Fortran, which is good because we need the version for GPU. And the GPU version of these libraries is included in MV Fortran. So it is good that here we see HPCSDK. We don't find FFT leaves here just because as it was pointed out in that question before. Because of course now FFTs are done by the GPUs and it is true that we loaded the FFTW3, but those libraries are for CPU. So the FFTW3 has been overwritten by the fact that MV Fortran has a zone version of FFT libraries. Indeed the FFTW3 in this case they do not appear here because we will be using libraries for GPU now and they are internal for MV Fortran. And so that's why they are not recognized here. So this is the configure. You should have found something similar to this. I think we can skip the compilation step, which of course is just a mechanical procedure now. I don't send this comment because we are too late. But of course you can try later on. Make minus J4PW it will compile your version of QE4GPU with these settings that we have just set here. So let's move to exercise five. So you can see how to run calculations. So this is just the same as we did before. We compile and finally we test the version and you will find this error, which means that the compilation is working. So let's do now this exercise five in which we see how to run a GPU calculation on the cluster. So this is the batch script. You can take it from exercise five. So here I can go back to exercise five and you see here again the readme, which is where all instructions are reported and the job share. Sorry, the job script. In this job script is the same that I have pasted here. You will see again two parts, the batch part where we ask resources for running calculations. So in this case we are running one node again, but two tasks per node because we are asking two GPUs. So in the architecture here each node is provided with four GPUs, but each of you will use two of them because otherwise there is no room for all other people. So you will ask two GPUs per node and for this reason we will be using two MPIs for two GPUs. So this is the main thing to keep in mind. Again we have the Quantum Express executable here. If you have your own compiled version of QE, you can put your path here, otherwise you can just leave it untouched because it will point to this folder where we compiled the version yesterday so you can use it. And here we have again the OpenMP setting. In this case we have one thread and here the MPI run with the usual common, one pool, one deck and let's go. The cool thing now is that if I run this, if I submit this job instead, so you can do of course, you can submit the job shell as is. The input file is just exactly the same we run in the previous exercise for CPU. So the cool thing now is that if I now this is running, remember that before this input file took 10 minutes. So in my case it was nine minutes and something. So let's see how much time it takes now. You can do this of course. So 25 people. So I guess you are trying. I think some of you, we still have previous calculations running from the CPU exercise but I think that many people are trying the new one. So in my case the calculation has already finished. So if I check the output file now, one minute, seven seconds. Let me open here also the other. So it was exercise two and one. Yes, it was this one. So here on the left you have the CPU test and on the right you have exactly the same calculation run with GPU. And you can see of course first of all here when you run with GPU, you can find this spring GPU acceleration is active and it confirms that the calculation has effectively used deployed GPUs. And if I search the same string here of course I don't find anything. So you can check GPU here. You also find here the times, the execution times on GPU. But the most important thing is that here it is one minutes and here it is 10 minutes. So we have just using GPUs. We have used two GPUs. So let's go up here. So in this case we use 16 processors. So MPI processes. And here we use two MPI processes. But since on the in the case using GPUs, these two MPI processes have loaded the calculation to the GPUs which are much faster. And for this reason here we have one minute instead of nine minutes here. So I guess it is now it is much easier to accomplish this exercise. What you can do now is to add open MP thread. So you can try them. Because the point here is that, let me show. Okay, if you change now what you can do is to change this export here. So here you can put two and run the calculation. You can put four and run the calculation. If you do this, what is happening here? Because let me compare again. So here we use a 60. So we have 16 processors. Each of us has 16 processors. Because this is the amount of resources that we ask that we ask in the job shell. But we are not using all of them because we are bounded by the number of GPUs. So in this case we have 16 cores available, but CPU cores available. But we are using only two of them because we have only two GPUs. So in this case what you can do is to use open MP to use the remaining part of the CPU cores that have not been employed in this case. Because in this case we cannot use 16 cores here because we would mess up with communications because we have only two GPUs. So we have to use two MPIs. Maybe you can try with four, but if you use too many MPIs you will mess up things with communications. So you have to keep the number of MPI bounded to the number of GPUs or approximately. But still we have 16 cores here. So in order to exploit the remaining part of the cores here it is a good idea to use open MP. So what you can do now is to run, since these calculations are also quite fast, you can change these open MP settings here and you can ask two, four, eight threads. Remember to change the output here. So if you change, for example, two threads here, remember to change two here, number of threads. I send this calculation again. So I think if you are, I hope that each one of you at least tried to run the calculation with GPUs because it is, I think it is very interesting if you compare the time between CPU and GPU execution. So now my calculation has finished. So I can compare one thread with two threads. Of course here, the first thing we see here is that here we were with one thread, we were running on two processor cores, two MPIs, one thread per MPI. So we are using two GPUs and two CPU cores and the CPU cores are deployed with two MPI processes. Here we are using four cores with two MPIs and two threads. So the number of MPIs is the same here and here because this number is bounded by the number of GPUs. So I repeat it again, two GPUs is better to use two MPIs or you can try four, but you cannot go too much part. But you can actually do the rest of the CPUs using threads and open MP. Okay, in this case, it was even, it took more time than using one thread. The test system is small, so I can show you here the final plot. So here I did it, we compare the computational times with CPU black bars and with GPUs a different number of pools and different number of threads. Of course, this test system is small. So as I said at the beginning, you are not seeing any significant, significant, of course, weight. You can observe a great advantage from using GPUs in general because with GPUs, whatever configuration, you are almost one order of magnitude lower with computational execution time. Otherwise, of course, we see that from one pool to two pools, we see some improvement here because all these bars are a bit smaller than the calculation with one pool. And with threads, we are not able to see significant advantages while maybe here with four pools, with four pools, we see that the red bar with one thread is higher than the other, so they're using two, four, eight. So maybe here we can see something, but honestly, in this case, the speed up from threads is very small and it's something that you can see using very large systems. So I think, yes, again, what I said regarding pools is through even for GPUs because if you distribute the wave function along plane weights, then the MPI processes will need to communicate with each other using pools, the communications are produced. So this is the end of the end zone. I would like, since so far I've said many times, oh, you should see with large systems or you should see with large systems, I think that it could be useful to show you some batch, some benchmark as cases on large systems to show the performances. And so this is quite a large system is 500 electrons. This is Tallium oxide or Tantallium oxide, I don't remember. And here we see the scaling with the number of nodes using more GPUs. So here we used one, two and four nodes. And each node is provided here with four GPUs. And we see that the time to solution is drastically reduced, increasing number of nodes. And here the same with pools. So the pool parallelism, again, we use one pool, two pools, but here since we have 26, sorry, here we have four pools and we are running our four nodes here. So when we use four pools with four nodes, communications are really lower. And for this reason here, we see a significant speed up using pools. So what we, so with CPUs, it is true with GPUs as well. And here we have an even larger system. So in this case, we have 500 electrons. And here we have four thousands electrons. And again, we see a very impressive computer speed up passing from two nodes to six nodes. We have to remember that in this, sorry, these nodes have eight GPUs per node. So here maybe I said four, but okay, it's so each node here has eight GPUs per node. I have to say that these calculations have been done with the newest version of the GPUs and per family, which has been very recently released by media. And these are very, very, they have very, very good performances on double precision floating points. So here again, we see the scaling, varying MPIs and pools using six nodes. If you use a good combination of pools and MPIs, you can really drastically reduce the computation of time. And here we see another test case. This is a very interesting molecule, is a carbon nanotube with porphyrins, functionalized with porphyrins. So this is a molecular system that is really for production. It's something which you can really use for publishing articles for doing interesting science. And we have five thousands electrons here. And this is gamma only. So in this case, we cannot exploit pooled parallelism, but we can exploit GPUs of course. And one SCF iteration on this giant molecule from our benchmark, from our test cases, it took 90 seconds, run on more than 3,000 cores. So running on CPU, if you want to do an SCF on this very, very large molecule with using only regular CPU nodes. With 3,000 cores, CPU cores, it took 90 seconds per iteration. So 90 seconds, if you need, I don't know, 10, 20 iteration is a 900 seconds. The same one iteration you can do in 30 seconds using 144 volt GPUs. These are the same GPUs of the cluster, Marconi 100 that we are using now for this and so on. And the same time, so about 30 seconds using 24 GPUs of this new ampere family. So here you are using 3,000 cores. Here you are using 144 volt GPUs. And here you are using 24 ampere GPUs. So this, I think this can give you an idea of what can be done when all these parallelization strategies of quantum espresso are used properly in a smart way. I hope to have given you a few hints about how to use quantum espresso and how to exploit as PC hardware and CPU. And I really thank you for the attention. And yes, if you have questions, yes, thank you. Yes, so I think now you can. Okay, I don't know now whether that raised and are for questions or because you did the exercise. But I think I messed up myself because I used it. So if those raised and are for because you have done exercise, please lower and whereas if you want to do questions, keep them raised. So okay. So I guess that we have two questions here. Uh, maybe, uh, chump and lean. Is it okay? I, I, okay, chump and link maybe want to use this a question. Sorry, actually, I raise hand because I was doing the GPU calculation. Oh, okay. Yeah, yeah. Sorry. Yeah, sorry. Sorry. It was my fault because I messed up things because I use these raised and even we have a question from the chat of zoom. Yes. And it's a nice one. What would the CPU do if the linear algebra and FFT are done by GPU libraries? So what is the CPU doing? Yeah, good. This is a good question. Now I have to say that there are a small part, small there are actually small parts of the code that have not yet or have not been ported to GPUs because what we did was to port the most in most computational intensive parts of the code to GPU. But there are still other parts of the code which remain on the CPU. So when, so there are two cases when the GPU is working because the code is processing a part of the code that has been ported to GPU. I think nobody knows what the GPU is, what the CPU is doing. I don't know. I think I don't know whether it is just running idle or it is waiting. But it is not important because the main computational part, not all the computational part then is done by GPU. But for those parts of the code that have not been completely ported to GPU, maybe or maybe there are also part of the cost for which is not very important to GPUs because we are happy with the CPU performances. So in that case, the CPU is still working and if you link some linear algebra or FFT library, they will be used for that part. Yes, there are a few portions and one of them is the FFT. We have been telling that the FFT has done so many times. So a lot of eyes focused on the FFT and that is one of the few portions of code where while the GPU is computing, the CPU is doing other things and is basically actually taking care of communication. So this is one portion of code where the CPU and the GPU overlap doing some useful work at the same time. But then, as Ivan already said, sometimes it's just waiting idle for the GPU to finish. And this is, of course, you may want in general to exploit the best both the CPU and the GPU at the same time. But it's not always so easy and also not always really useful because have you seen, for example, from Marconi 100, the CPU is very weak, but the GPU is very fast. So it doesn't would really contribute very little. There is a second very important questions, I think, and it's probably some misleading number that I gave during my presentation. So please, Ivan, correct me. About the end pull on GPUs, should we be careful on picking an integer fraction of the number of cores of the GPU this time, or should it still be an internal CPU cores? Now, I made it clearly made some confusion, managed in GPU cores. So I had to clarify this point, which is very important. Yeah. Well, yes, it's not when you saw the point is when you are using pools, what you have to care is about MPIs. And if you are using GPUs, the number of MPIs is kind of bounded by the number of GPUs. So you start from how many GPUs can I use? And so let's fix the number of MPIs. Okay, then I checked the number of K points. Let's see how many pools can I use in order to exploit this, my architecture. So when you think about how to run calculation with pools, you just have to think about MPIs. So pools, when you run when you use pools, think about the number of MPIs you are using. But if you have GPUs, the number of MPIs must be equal to the number of GPUs at the first glance, at the first approximation. So the number of cores, which was a GPU cores, is something that is more in depth inside the hardware. So the number of CPUs, you never see the GPU cores, because the GPU cores are inside the GPU and they are the reason why the GPU is that fast. So from your perspective, you as a user, but even from our perspective as developers, the most important point is the GPU as a whole. Then inside the GPUs, you will find cores that are usually organized in multiprocessor or in their ways, but we never work explicitly with cores inside the GPUs, especially where you are running calculations. So from your point of view, you just have to see how many GPUs you have and then you check it and then you check how many MPI processes to run. Pietro, if you want to add anything else, please. No, it was just perfect and sorry for the confusion. Mentioning the number of workers on the GPU was just to highlight the fact that in general, GPUs to run efficiently require more data than CPU. So sometimes for a small input, you don't gain much from the GPU acceleration. That was the whole point. Then forget about GPU cores, please. Yes, there is a final question probably. I don't know if we still have time. Maybe we're a bit late. Can we? Well, maybe we have time. Yeah, maybe one or two questions more. Well, I think you are the expert in this field. So this question is really for you. I'm curious regarding band parallelization. I've never obtained speedup from using it on my system. Could you comment on what type of calculation this kind of parallelization is using on? Yeah, there are two points. There are two main aspects. The first point is that in order to see real advantages from band parallelization, you need to have a huge number of conscious states. Otherwise, it is worthless. The second point is there are actually, there is a band parallelization actually in quantum espresso, but it is, I think it is not implemented in the, it is not really distributing the memory among the band groups, but it is only using, it is dividing only the workload and not the memory. So it is, I think it has a suboptimal efficiency at the moment. And it is used for exact exchange, right? I think band parallelism becomes very convenient with exact exchange. Yes, because at that time, you have to process many, a couple pairs of bands to compute the exchange integrals. And yes, as much as I know, even in that case, you will see that if you run with proper big architectures and large molecular systems. Let me add a few things. So if you want, you can keep doing the exercises on the Marconi 100 cluster until 130, half past one, chest central European time. So you still have 45 minutes more. You can just take the readme files and you read them and you are able, you are allowed to submit jobs until half past one. So if you want to do again the exercises, you want to do them slower or you want to do even those exercises that we had to skip or which I went fast, you can do that. And if you have problems, I will answer you on Slack channel. So you can do this. And regarding the data, if you want to save the data you're working directly from there, you should, you have your account is available until Sunday. So in the next one, two days, or maybe it is better if you do now, you better copy the wall directory to your local machine, laptop or a virtual machine. In order to do this, I don't know if you know, maybe I forgot to write this, the common in the readme files, but I can write you on chat. It is enough that you do this common SCP minus R, then you, let me do it. So if you go here in, I think you can, okay. So I wrote you in the chat, the common is SCP, which means that you are copying the other activity, but CP is for copying your local machine from one point to another point, SCP. Sorry, I forgot it. Obviously, this is missing something, SCP minus R user. Okay, sorry. This is the right common.  Then at login next to Chinneca, and this is, you give the host name here. And then you copy this directory, day nine, which is the directory in which you did the exercises and dot it means here. Yes, I will, yes, I will put it on Slack as soon as we close. So you have time until Sunday to, to copy all your files. So you can keep working until half past one. And then you have two days more to copy back all your directory and files on your local machine. So you can keep that. I don't see any other questions. Yeah, maybe we can close. Well, no, there is another one maybe. I don't know if we're running out of time, actually, how to run similar job on the GPU. In my institution, they use their, suggest something to the person in charge. Well, I'm not sure, but certainly, if you have, so this means that your, your institute, they can help writing down a job script that allocates and starts a number of MPI processes. And, and also activates, so allocates for your job a number of GPUs. So I think that if you tell your CIS admin, so the people in charge of the class that you need to run a job with, I don't know, four MPI to use the four GPUs that you have, they will, they can help setting it up. And by the way, for those who asked about GPUs performance for Quantum Express, so I linked things like a Wikipedia page where you have the, I think it's the entire list of old cards, of NVIDIA cards. And on one of the columns on the right, there is the performance in single and double precision. And those two numbers are the ones that we want to check. You can compare the performance with single and double and immediately realize that there are two groups of cards. Those where this ratio is about one third and those where this ratio is much larger and double performance is much weaker. Those are the cards where you will not get much out of the GPU. This was a question asked before. Yes, I don't know if we have, I see two questions to raise then maybe. Yes, thank you. I have this question. I've been working recently with this code, Banier Berry, from written by Stefan Serkin. And he says that he used a combination of slow Fourier transform and fast Fourier transforms. I would like to ask you, I don't know if it is the place, why is it better than use only fast Fourier transform and also is this kind of machine implemented in Quantum Espresso or? I didn't get the alternative of fast Fourier transforms. He says that he used a combination of Fourier FFT and DFT. Yeah, this great Fourier transform, which is this low one. Why he used this combination? Perhaps I just wanted to ask you because maybe you know. Well, honestly, what I can tell you is that this is not done inside Quantum Espresso. I don't know exactly the peculiar problem that is optimised with this approach. So I would prefer not to give a precise answer probably because I don't really know the answer now. What is sure is that sometimes even the best optimised libraries and approaches may not be the best option depending on the problem that you want to perform. Let me give you an example in different contexts like you know, matters multiplication is something that everybody is doing and this course is something that has been optimised like for so many years, but so many people. And eventually we have a number of libraries that, depending on the system that you are considering, can do a matters multiplication very well. So basically with the matters multiplication, you get basically the peak performance, so the theoretical performance of your CPU, for example. But if your problem is as a peculiar size, I don't know that you are very tall matrices, very thin, so the skinny matrices. Well, you may gain something from avoiding the general implementation and use some peculiar implementation for your peculiar problem. Now honestly, I cannot comment more because I don't know the details of this task. Something more about this, or maybe someone who knows this. Okay, I was just curious because this code is a thousand times faster than the post-processing of 19. So I was curious why it's so fast. Thank you, thank you very much. It was very, very helpful, very helpful. Thank you. Maybe we have to close now. If you have more questions, you can write us luck, we will answer there. And yeah, that's all. So I think we can close the Zoom connection now. Thank you and bye-bye. Thank you. Bye-bye. Bye. Thank you.