parallelizing L2 cache lookup#3032
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Summary: Pull Request resolved: pytorch#3032 X-link: facebookresearch/FBGEMM#130 Change sets 1. instead of allocate an intermediate tensor to collect the L2 cache miss info, we will do all the embeddings copy inside the originally provided tensor and mark related indices to -1 2. paralizing the cache lookup logic using multiple cachelib pools which helps reduce the LRU contention 3. fix cachelib->UVA tensor data copy bug(wrong offset) Reviewed By: ehsanardestani Differential Revision: D61417947
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This pull request has been merged in c41d676. |
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Differential Revision: D61417947