{"action":"created","issue":{"url":"https://api.github.com/repos/YunxiaWang/5775FinalProject/issues/1","labels_url":"https://api.github.com/repos/YunxiaWang/5775FinalProject/issues/1/labels{/name}","comments_url":"https://api.github.com/repos/YunxiaWang/5775FinalProject/issues/1/comments","events_url":"https://api.github.com/repos/YunxiaWang/5775FinalProject/issues/1/events","html_url":"https://github.com/YunxiaWang/5775FinalProject/issues/1","id":122005876,"number":1,"title":"excessive bram usage","user":{"login":"zhangzhiru","id":7463279,"avatar_url":"https://avatars.githubusercontent.com/u/7463279?v=3","gravatar_id":"","url":"https://api.github.com/users/zhangzhiru","html_url":"https://github.com/zhangzhiru","followers_url":"https://api.github.com/users/zhangzhiru/followers","following_url":"https://api.github.com/users/zhangzhiru/following{/other_user}","gists_url":"https://api.github.com/users/zhangzhiru/gists{/gist_id}","starred_url":"https://api.github.com/users/zhangzhiru/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/zhangzhiru/subscriptions","organizations_url":"https://api.github.com/users/zhangzhiru/orgs","repos_url":"https://api.github.com/users/zhangzhiru/repos","events_url":"https://api.github.com/users/zhangzhiru/events{/privacy}","received_events_url":"https://api.github.com/users/zhangzhiru/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"milestone":null,"comments":1,"created_at":"2015-12-14T09:38:13Z","updated_at":"2015-12-14T11:54:18Z","closed_at":null,"body":"Let's use github to track the tech issues for this project.\r\n\r\n------------------- Copied from Piazza --------------------\r\nWhen I do the \"source run_bitstream.sh\"  after \"vivado_hls run_pipeline.tcl\" to generate bitstream for FPGA, it shows errors as following. Does that mean our code's memory usage is too big so that it cannot be implemented on FPGA?"},"comment":{"url":"https://api.github.com/repos/YunxiaWang/5775FinalProject/issues/comments/164418803","html_url":"https://github.com/YunxiaWang/5775FinalProject/issues/1#issuecomment-164418803","issue_url":"https://api.github.com/repos/YunxiaWang/5775FinalProject/issues/1","id":164418803,"user":{"login":"zhangzhiru","id":7463279,"avatar_url":"https://avatars.githubusercontent.com/u/7463279?v=3","gravatar_id":"","url":"https://api.github.com/users/zhangzhiru","html_url":"https://github.com/zhangzhiru","followers_url":"https://api.github.com/users/zhangzhiru/followers","following_url":"https://api.github.com/users/zhangzhiru/following{/other_user}","gists_url":"https://api.github.com/users/zhangzhiru/gists{/gist_id}","starred_url":"https://api.github.com/users/zhangzhiru/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/zhangzhiru/subscriptions","organizations_url":"https://api.github.com/users/zhangzhiru/orgs","repos_url":"https://api.github.com/users/zhangzhiru/repos","events_url":"https://api.github.com/users/zhangzhiru/events{/privacy}","received_events_url":"https://api.github.com/users/zhangzhiru/received_events","type":"User","site_admin":false},"created_at":"2015-12-14T11:54:18Z","updated_at":"2015-12-14T11:54:18Z","body":"https://github.com/YunxiaWang/5775FinalProject/issues/1\r\n\r\nJust checked the synthesis report. According to the estimate from Vivado HLS, the BRAM usage is over by 900%. We need to completely partition the 1st dimension of the training data array, like what we did in assignment 2. Note that we didn't do that in assignment 4 since the partitioning happened automatically as I changed training_data.h to a 2D array (but this is change is not reflected in your version).  \r\n\r\nI've pushed in my changes to run_pipeline.tcl. Now the BRAM estimate is down to 255 (92% utilization). \r\n\r\nDue to my travel, I won't have much online time. In case the design still doesn't fit the FPGA, please try to reduce the size of the training data (say 2000 -> 1000 training instances) or even make it a 1-NN design to make trade-off between hardware complexity and recognition accuracy."}}