Add caching allocator for pinned (page-locked) memory#618
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soumith merged 2 commits intotorch:masterfrom Dec 1, 2016
Merged
Add caching allocator for pinned (page-locked) memory#618soumith merged 2 commits intotorch:masterfrom
soumith merged 2 commits intotorch:masterfrom
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Adds a CUDA "sleep" kernel which spins for the given number of iterations. This is useful for testing correct synchronization with streams.
Adds a caching allocator for CUDA pinned (page-locked) memory. This avoid synchronization due to cudaFreeHost or cudaHostUnregister at the expense of potentially higher host memory usage. Correctness is preserved by recording CUDA events after each cudaMemcpyAsync involving the pinned memory. The pinned memory allocations are not reused until all events associated with it have completed.
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Adds a caching allocator for CUDA pinned (page-locked) memory. This avoid synchronization due to cudaFreeHost (or cudaHostUnregister) calls.
To ensure read-after-write and write-after-read consistency, a CUDA event is recorded after every cudaMemcpyAsync between host and device involving pinned memory created by this allocator. Memory allocations are only re-used after they're freed and all associated CUDA events have completed.
Unlike the caching device allocator, allocations are never split. This means that requests for small allocations may be filled by much larger cached buffers. I think this should be OK in practice.
Also, CUDA events are processed in the order in which they're recorded, even though events may occur out-of-order between devices or streams. This does not affect correctness, but means that cached allocations may not be considered "ready" for re-use until a little later. In practice, I don't think this should matter.
To enable the caching pinned memory allocator and caching device allocator, set the environment variable
THC_CACHING_ALLOCATOR=1