{"action":"created","issue":{"url":"https://api.github.com/repos/NVIDIA/nccl/issues/56","repository_url":"https://api.github.com/repos/NVIDIA/nccl","labels_url":"https://api.github.com/repos/NVIDIA/nccl/issues/56/labels{/name}","comments_url":"https://api.github.com/repos/NVIDIA/nccl/issues/56/comments","events_url":"https://api.github.com/repos/NVIDIA/nccl/issues/56/events","html_url":"https://github.com/NVIDIA/nccl/issues/56","id":193790264,"number":56,"title":"How can I scale with nccl addoption?","user":{"login":"archenroot","id":553512,"avatar_url":"https://avatars.githubusercontent.com/u/553512?v=3","gravatar_id":"","url":"https://api.github.com/users/archenroot","html_url":"https://github.com/archenroot","followers_url":"https://api.github.com/users/archenroot/followers","following_url":"https://api.github.com/users/archenroot/following{/other_user}","gists_url":"https://api.github.com/users/archenroot/gists{/gist_id}","starred_url":"https://api.github.com/users/archenroot/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/archenroot/subscriptions","organizations_url":"https://api.github.com/users/archenroot/orgs","repos_url":"https://api.github.com/users/archenroot/repos","events_url":"https://api.github.com/users/archenroot/events{/privacy}","received_events_url":"https://api.github.com/users/archenroot/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":1,"created_at":"2016-12-06T14:45:36Z","updated_at":"2016-12-07T01:56:00Z","closed_at":null,"body":"Hi, \r\n\r\nI have single GPU application which I am now trying to extend to work on multiple GPUs, which is offloading data in segments and I would like to let it scale both horizontally and vertically.\r\n\r\nQ1: I am considering adopting nccl for single node multi-gpu task distribution. I think this is the way to go in the moment. Is this where nccl will help me?\r\n\r\nQ2: When it comes to multigpu clusters distribution(for example I have 2x 8GPU systems), is there also work for nccl or better to look into frameworks like rCUDA MPI?\r\n\r\nQ3: Does nccl try to aspirate to become a generic layer into which I could potentially connect any system with any number of GPUs and distribute tasks? \r\n\r\nThanks for suggestions/answers.\r\n\r\nLadislav"},"comment":{"url":"https://api.github.com/repos/NVIDIA/nccl/issues/comments/265332611","html_url":"https://github.com/NVIDIA/nccl/issues/56#issuecomment-265332611","issue_url":"https://api.github.com/repos/NVIDIA/nccl/issues/56","id":265332611,"user":{"login":"nluehr","id":1873655,"avatar_url":"https://avatars.githubusercontent.com/u/1873655?v=3","gravatar_id":"","url":"https://api.github.com/users/nluehr","html_url":"https://github.com/nluehr","followers_url":"https://api.github.com/users/nluehr/followers","following_url":"https://api.github.com/users/nluehr/following{/other_user}","gists_url":"https://api.github.com/users/nluehr/gists{/gist_id}","starred_url":"https://api.github.com/users/nluehr/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/nluehr/subscriptions","organizations_url":"https://api.github.com/users/nluehr/orgs","repos_url":"https://api.github.com/users/nluehr/repos","events_url":"https://api.github.com/users/nluehr/events{/privacy}","received_events_url":"https://api.github.com/users/nluehr/received_events","type":"User","site_admin":false},"created_at":"2016-12-07T01:56:00Z","updated_at":"2016-12-07T01:56:00Z","body":"NCCL is strictly a collective communication library. It provides optimized routines for operations such as broadcast or all-reduce among multiple GPUs, but not any mechanisms for task distribution or control. If you are just starting out with multi-GPU programming, CUDA-aware MPI might be a good place to start. [Here](http://on-demand-gtc.gputechconf.com/gtc-quicklink/6Pg15P1) is a presentation from last year's GTC that may be helpful."}}
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