Un-nest tensor_copy_chunk dispatch lambdas (#6074) - #6074
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July 25, 2026 13:37
…ytorch#6068) Summary: X-link: facebookresearch/FBGEMM#2968 Speed up the RES C++ streamer's device->host copy by parallelizing it. Previously stream() copied all updated rows to CPU on a single thread and enqueued one item. This replaces that serial copy with a chunked copy across up to `kNumCopyThreads` threads: tensor_copy_chunk() copies a [start, end) row range, and the per-thread tiling is factored into a pure, unit-testable computeChunkRanges(). Differential Revision: D113594180
…eamer (pytorch#6069) Summary: X-link: facebookresearch/FBGEMM#2971 Speed up the RES C++ streamer's ship stage by parallelizing it. Previously a single stream thread drained the queue, so the setEmbeddings RPCs to the PS ran one at a time. This diff replaces it with kNumConsumerThreads consumers on a folly::UMPMCQueue that ship concurrently. Differential Revision: D113599253
…#6075) Summary: X-link: meta-pytorch/torchrec#4464 X-link: facebookresearch/FBGEMM#2976 Make the RES streamer's chunk size and ship/copy thread counts tunable from config instead of compile-time constants. Previously kChunkSize / kNumConsumerThreads / kNumCopyThreads were constexpr in raw_embedding_streamer.cpp, so tuning them meant a base rebuild. This plumbs them as res_chunk_size / res_num_consumers / res_num_copy_threads from TableBatchedEmbeddingConfig through fused_params to the RawEmbeddingStreamer ctor, mirroring the existing res_store_shards. Defaults stay 500000/8/4, so behavior is unchanged until overridden Differential Revision: D113532922
Summary: X-link: facebookresearch/FBGEMM#2975 The four tensor copies in tensor_copy_chunk are independent, so dispatch each under its own sibling FBGEMM_DISPATCH_* instead of nesting weights -> indices -> identities -> runtime_meta. Two wins, no behavior change: 1. Readability: the flat structure drops the value_t / index_t / id_t / rm_t aliases that existed only to dodge scalar_t name-shadowing between the nested lambdas -- each copy now just uses scalar_t and reads top-to-bottom instead of 3 levels deep. 2. Fewer template instantiations: nesting stamps each inner copy once per outer type (multiplicative, ~4 x 2); siblings stamp each once per its own type set (additive, 4 + 2) -> smaller binary, faster compile. Differential Revision: D113533821
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Summary:
X-link: https://github.com/facebookresearch/FBGEMM/pull/2975
The four tensor copies in tensor_copy_chunk are independent, so dispatch each under its own sibling FBGEMM_DISPATCH_* instead of nesting weights -> indices -> identities -> runtime_meta.
Two wins, no behavior change:
Differential Revision: D113533821