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authorLang Yu <[email protected]>2024-04-26 06:56:35 +0000
committerAlex Deucher <[email protected]>2024-05-08 19:17:04 +0000
commit89773b85599affe89dfc030aa1cb70d6ca7de4d3 (patch)
treea42e90a5eb80e12ae68f01ead7f746be1269e310 /drivers/gpu/drm/amd/amdgpu/mes_v11_0.c
parentdrm/amdgpu: add se registers to ip dump for gfx10 (diff)
downloadkernel-89773b85599affe89dfc030aa1cb70d6ca7de4d3.tar.gz
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drm/amdkfd: Let VRAM allocations go to GTT domain on small APUs
Small APUs(i.e., consumer, embedded products) usually have a small carveout device memory which can't satisfy most compute workloads memory allocation requirements. We can't even run a Basic MNIST Example with a default 512MB carveout. https://github.com/pytorch/examples/tree/main/mnist. Error Log: "torch.cuda.OutOfMemoryError: HIP out of memory. Tried to allocate 84.00 MiB. GPU 0 has a total capacity of 512.00 MiB of which 0 bytes is free. Of the allocated memory 103.83 MiB is allocated by PyTorch, and 22.17 MiB is reserved by PyTorch but unallocated" Though we can change BIOS settings to enlarge carveout size, which is inflexible and may bring complaint. On the other hand, the memory resource can't be effectively used between host and device. The solution is MI300A approach, i.e., let VRAM allocations go to GTT. Then device and host can flexibly and effectively share memory resource. v2: Report local_mem_size_private as 0. (Felix) Signed-off-by: Lang Yu <[email protected]> Reviewed-by: Felix Kuehling <[email protected]> Signed-off-by: Alex Deucher <[email protected]>
Diffstat (limited to 'drivers/gpu/drm/amd/amdgpu/mes_v11_0.c')
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