Improve CUDA out-of-memory error message #13751
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The new error message now looks like (from Python): RuntimeError: CUDA out of memory. Tried to allocate 16.00 GiB (GPU 0; 11.93 GiB total; 4.00 GiB allocated; 179.00 KiB cached) Summary of terms: "total": total global memory on GPU "allocated": memory allocated by the program using the caching allocator "cached": memory held by the allocator but not used by the program The "allocated" amount does not include memory allocated outside of the caching allocator, such as memory allocated by other programs or memory held by the driver. Note that at this point cuda_malloc_retry has already returned all possible "cached" memory to the driver. The only remaining "cached" memory is split from a larger block that is partially in-use.
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pietern
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Nov 8, 2018
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| Block search_key(device, stream, size); | ||
| auto& free_blocks = small ? large_blocks : small_blocks; | ||
| auto& free_blocks = small ? small_blocks : large_blocks; |
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apaszke
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Nov 9, 2018
aten/src/THC/THCCachingAllocator.cpp
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| cudaGetLastError(); // clear CUDA error | ||
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| cudaDeviceProp prop; | ||
| AT_CUDA_CHECK(cudaGetDeviceProperties(&prop, device)); |
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Nov 9, 2018
Summary:
```
The new error message now looks like (from Python):
RuntimeError: CUDA out of memory. Tried to allocate 16.00 GiB (GPU 0; 11.93 GiB total capacity; 4.00 GiB already allocated; 7.33 GiB free; 179.00 KiB cached)
Summary of terms:
"total capacity": total global memory on GPU
"already allocated": memory allocated by the program using the
caching allocator
"free": free memory as reported by the CUDA API
"cached": memory held by the allocator but not used by the program
The "allocated" amount does not include memory allocated outside
of the caching allocator, such as memory allocated by other programs
or memory held by the driver.
The sum of "allocated" + "free" + "cached" may be less than the
total capacity due to memory held by the driver and usage by other
programs.
Note that at this point cuda_malloc_retry has already returned all
possible "cached" memory to the driver. The only remaining "cached"
memory is split from a larger block that is partially in-use.
```
This also fixes an issue where on out-of-memory could cause an unrelated subsequent CUDA kernel launch to fail because `cudaGetLastError()` was not cleared.
Pull Request resolved: pytorch/pytorch#13751
Differential Revision: D13007177
Pulled By: colesbury
fbshipit-source-id: ea7121461b3f2a34646102959b45bde19f2fabab
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This also fixes an issue where on out-of-memory could cause an unrelated subsequent CUDA kernel launch to fail because
cudaGetLastError()was not cleared.