[FusedDense] Set workspace size to 32M for Hopper and 4M for others

csrc/fused_dense_lib/fused_dense_cuda.cu

@@ -122,7 +122,9 @@ int gemm_bias_act_lt(
     reinterpret_cast<cublasLtHandle_t>(at::cuda::getCurrentCUDABlasHandle());
   // See https://github.com/pytorch/pytorch/issues/73328 for reasoning behind
   // setting this to 1M.
-  size_t workspaceSize = 1024 * 1024;
+  // However, Apex sets it to 4M and TransformerEngine sets to 32M for Hopper and 4M for other GPUs
+  // https://github.com/NVIDIA/TransformerEngine/blob/a0f0065498bbcfc1da78cf9e8b166f5381613fbc/transformer_engine/pytorch/module.py#L91
+  size_t workspaceSize = 1024 * 1024 * (at::cuda::getCurrentDeviceProperties()->major >= 9 ? 32 : 4);
   void* workspace = at::empty(
     {static_cast<int64_t>(workspaceSize)},
     at::device({at::kCUDA, at::cuda::current_device()}).dtype(at::kByte)).data_ptr();
@@ -296,7 +298,8 @@ int gemm_bgradb_lt(
     reinterpret_cast<cublasLtHandle_t>(at::cuda::getCurrentCUDABlasHandle());
   // See https://github.com/pytorch/pytorch/issues/73328 for reasoning behind
   // setting this to 1M.
-  size_t workspaceSize = 1024 * 1024;
+  // However, Apex sets it to 4M and TransformerEngine sets to 32M for Hopper and 4M for other GPUs
+  size_t workspaceSize = 1024 * 1024 * (at::cuda::getCurrentDeviceProperties()->major >= 9 ? 32 : 4);
   void* workspace = at::empty(
     {static_cast<int64_t>(workspaceSize)},
     at::device({at::kCUDA, at::cuda::current_device()}).dtype(at::kByte)).data_ptr();
@@ -449,7 +452,8 @@ int gemm_dact_bgradb_lt(
     reinterpret_cast<cublasLtHandle_t>(at::cuda::getCurrentCUDABlasHandle());
   // See https://github.com/pytorch/pytorch/issues/73328 for reasoning behind
   // setting this to 1M.
-  size_t workspaceSize = 1024 * 1024;
+  // However, Apex sets it to 4M and TransformerEngine sets to 32M for Hopper and 4M for other GPUs
+  size_t workspaceSize = 1024 * 1024 * (at::cuda::getCurrentDeviceProperties()->major >= 9 ? 32 : 4);
   void* workspace = at::empty(
     {static_cast<int64_t>(workspaceSize)},
     at::device({at::kCUDA, at::cuda::current_device()}).dtype(at::kByte)).data_ptr();