[AutoScheduler] Remove max_registers_per_block in HardwareParams#7040
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masahi merged 2 commits intoapache:mainfrom Dec 5, 2020
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[AutoScheduler] Remove max_registers_per_block in HardwareParams#7040masahi merged 2 commits intoapache:mainfrom
max_registers_per_block in HardwareParams#7040masahi merged 2 commits intoapache:mainfrom
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cc @jcf94 |
comaniac
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| device_api->GetAttr(ctx, tvm::runtime::DeviceAttrKind::kMaxRegistersPerBlock, &ret); | ||
| int max_registers_per_block = ret; | ||
| int max_local_memory_per_block = INT32_MAX; |
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| // This setting looks working for Metal GPUs later than A10 | ||
| int max_shared_memory_per_block = 32 * 1024; | ||
| int max_registers_per_block = 4 * 1024; | ||
| int max_local_memory_per_block = INT32_MAX; |
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ok I'll update my PR #7038 after we let this in first. |
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@comaniac Comments are addressed. |
masahi
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thanks @merrymercy @comaniac |
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Previously, we use
hardware_params->max_registers_per_blockgot from Cuda device query as the value ofmax_local_memory_per_blockinVerifyGPUCode. This is wrong. They are just not the same thing.Luckily, for NVIDIA GPUs, this bug does not affect the performance. Because
kMaxRegistersPerBlockreturns a very large value. The check inVerifyGPUCodewith this large value almost affects nothing.We have to rename
hardware_params->max_registers_per_blockto a correct namehardware_params->max_local_memory_per_block, so it is more meaningful for other backends.A better way is to set it as
INT32_MAXto simply skip this check. Because there is no hard limitation in the CUDA runtime for this value. Setting it toINT32_MAXcan enlarge the search space while keeping most of the measured schedules still valid.