[release/3.4] fix: use ThrustAllocator in argsort 1D path to avoid implicit cudaStr…#78733
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PaddlePaddle#78726) * fix: use ThrustAllocator in argsort 1D path to avoid implicit cudaStreamSynchronize The 1D argsort path uses thrust::sort_by_key / thrust::stable_sort_by_key with the default execution policy (thrust::cuda::par.on(stream)), which causes thrust to allocate temporary workspace via cudaMalloc/cudaFree. These are synchronous CUDA API calls that implicitly trigger cudaStreamSynchronize, draining all pending GPU work on the stream. This creates a false data dependency: if any prior kernels (e.g. backward weight gradient GEMMs) are still executing on the same stream, argsort blocks until they complete — adding ~2ms of unnecessary stall per call. The fix passes phi::memory_utils::ThrustAllocator to the thrust execution policy, routing temporary allocations through Paddle's caching allocator (which is async and does not synchronize). This is consistent with other Paddle kernels that use thrust (e.g. unique_kernel.cu, shuffle_batch_kernel.cu). nsys evidence (500K int32 argsort after a 4096x4096 matmul): Before: 3x cudaStreamSynchronize + 1x cudaMalloc + 1x cudaFree per call wall time = 2.5ms (steady state) After: 0x cudaStreamSynchronize, 0x cudaMalloc (caching allocator hit) wall time = 0.07ms (expected, matching the 2D CUB path) Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * polish --------- Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
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PR Category
Operator Mechanism
PR Types
Performance
Description
修复argsort算子在1D case下的低效malloc路径，使其调用框架内存管理机制，避免裸malloc带来的额外同步
pcard-91067
是否引起精度变化
否
Cherry-pick of #78726 (authored by @A-nnonymous) to
release/3.4.devPR:#78726