Comments (1)
CUTLASS uses CUDA streams to launch GEMM kernels and can be used in a multi-GPU application.
The kernels CUTLASS launches are, however, single-GPU operations that an application would need to compose to compute larger computations distributed across multiple GPUs and multiple nodes.
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Related Issues (20)
- [QST] TMA copy dependency on `cuTensorMapEncodeTiled` HOT 1
- [BUG] rs_op_selector does not allow to use mixed FP8 types for A and B HOT 6
- [QST]Could not find compiler set in environment variable CUDACXX: HOT 2
- [BUG] Sparse GEMM seems to produce wrong results for `F32` datatype and specific inputs HOT 3
- [BUG] Copy_Atom with DefaultCopy cause misaligned address HOT 5
- [BUG] [Triage] Several potential Cutlass illegal memory access violations related to SM90 EVT HOT 2
- [QST] What is the canonical method to remap the coordinate in CuTe? HOT 6
- [FEA] Support SM90 Grouped GEMM HOT 2
- [BUG] make_tiled_copy should not assume 2d data, Thr and Val layouts HOT 11
- [BUG] right_inverse with 1d layout results "#2700-D: attempt to access expired storage" on constexpr return value. HOT 4
- [QST]question about cutlass epilogue customization HOT 14
- [BUG] About the rounding mode of TF32 HOT 3
- [QST] How do I do a matrix multiply inside a Cuda kernel? HOT 24
- [QST] Cosize and Complement HOT 4
- [QST] How to use splitk in cutlass python? HOT 4
- [QST]serial splitK gemm, semaphore deadlock。 HOT 9
- [QST] What is the difference between make_shape and make_tile? HOT 3
- [QST] How to make the performance of cutlass kernel achieve what cutlass_profiler claims? HOT 12
- [QST] Shapes of `partition_fragment_{A,B}` HOT 6
- [QST] Question on customize epilogue reduction HOT 5
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