Commit Graph

5 Commits

Author SHA1 Message Date
Dom Brown
44fb3c1673
[TRTLLM-5770] feat: Integrate TRT-LLM Gen FP8 block scale MoE with Pytorch workflow kernel autotuner (#5207)
- Adds a new Python custom op (fp8_block_scale_moe_runner) and a FP8BlockScaleMoERunner class for autotuning.
- Updates C++ MoE and batched GEMM kernels to accept a configIndex for workspace sizing and execution.
- Extends the unit test to run both autotuned and non-autotuned code paths.

Signed-off-by: Dom Brown <3886319+DomBrown@users.noreply.github.com>
2025-06-17 21:01:56 +08:00
Anthony Chang
4f9fa9f21d
feat: MoE trtllm backend kernel update (#5183)
Signed-off-by: Anthony Chang <27950904+rosenrodt@users.noreply.github.com>
2025-06-16 14:46:13 +08:00
Dom Brown
9c012d5bf8
[TRTLLM-5589] feat: Integrate TRT-LLM Gen FP8 Batched GEMM with Pytorch workflow kernel autotuner (#4872)
Signed-off-by: Dom Brown <3886319+DomBrown@users.noreply.github.com>
2025-06-09 11:02:48 +01:00
Nikita Korobov
8043d7a03c
feat: update DeepSeek FP8 TRT-LLM Gen cubins (#4643)
Signed-off-by: Nikita Korobov <nkorobov@nvidia.com>
2025-06-03 14:07:54 -07:00
Nikita Korobov
fa3879629e
feat: TRT-LLM Gen integration for BMM and MoE refactoring (#4280)
- Adds BatchedGemm cubins and the respective call interface from TensorRT-LLM Generator. 
- Refactors TRT-LLM Gen MoE runner to call to BMM interface
- The accuracy is verified for DeepSeek R1 FP4 

Signed-off-by: Nikita Korobov <nkorobov@nvidia.com>
2025-05-16 13:31:53 +02:00