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dylanyunlong
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2026-08-06
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dylanyunlong
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dylanyunlong/project_6
2026-08-15 13:58:41 +08:00
109d29fa60
Merge remote-tracking branch 'modelhub/main'
045ea5df79
feat: Cu10 TensorOp batched HGEMM via Iluvatar CUTLASS framework
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dylanyunlong
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dylanyunlong/project_6
2026-08-15 13:41:31 +08:00
30f98c0674
data: Cu10 CUTLASS part 2 — tensorop example, arch.h, cutlass.h
dylanyunlong
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dylanyunlong/project_6
2026-08-15 13:41:22 +08:00
f006ab1a01
test: cat tensorop GEMM example + arch.h + cutlass.h from corex-samples
dylanyunlong
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dylanyunlong/project_6
2026-08-15 13:32:13 +08:00
b922d694dc
data: Cu10 CUTLASS headers from corex-samples
dylanyunlong
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dylanyunlong/project_6
2026-08-15 13:31:52 +08:00
1d36754efc
fix: cat_cutlass_cu10.sh writes to cat_files/ directory instead of stdout
4abb4df215
test: cat Cu10 CUTLASS files — mma_cu10.h, iluvatar_mma.hpp, batched_gemm.cu, default_mma_core_cu10.h
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dylanyunlong
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dylanyunlong/project_6
2026-08-15 13:28:05 +08:00
6b9086c3a9
test: probe Cu10 CUTLASS fork — find mma_cu10.h, tensor op files, batched_gemm example
dylanyunlong
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dylanyunlong/project_6
2026-08-15 13:22:52 +08:00
a465dd1d75
fix: use F.silu in test script for old corex torch
a12d070d82
fix: replace torch::silu with x*sigmoid(x) for old corex torch
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dylanyunlong
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dylanyunlong/project_6
2026-08-15 13:20:21 +08:00
c840c9159f
feat: moe_tcu_dispatch.cpp — C++ MoE expert loop via torch::mm (TCU kernel)
dylanyunlong
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dylanyunlong/project_6
2026-08-15 13:17:32 +08:00
9514092980
test: probe torch.matmul backend + ixformer.matmul/linear + Python loop overhead
dylanyunlong
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dylanyunlong/project_6
2026-08-15 13:14:35 +08:00
395b3e4042
test: clean rebuild + debug output for kernel 10 correctness
dylanyunlong
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dylanyunlong/project_6
2026-08-15 13:12:59 +08:00
a8ca42b59c
perf: hgemm_warptiling Config B — beats cublas on MoE-sized GEMM (0.7x)
dylanyunlong
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dylanyunlong/project_6
2026-08-15 13:08:36 +08:00
21417319bc
test: sweep 6 kernel 10 configs + cublas baseline — find best params for warp64
dylanyunlong
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dylanyunlong/project_6
2026-08-15 01:24:15 +08:00
27bb8d28df
test: probe kernel 10 perf with CUDA events — isolate bottleneck
dylanyunlong
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dylanyunlong/project_6
2026-08-15 01:06:28 +08:00
2b12fe687e
feat: hgemm_warptiling.cu — siboehm kernel 10 ported to WARPSIZE=64 FP16
dylanyunlong
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dylanyunlong/project_6
2026-08-15 01:03:23 +08:00
11b8a98eea
test: probe warp_size=64 behavior + kernel 10 warp tiling with WARPSIZE=64 on BI-V100
dylanyunlong
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dylanyunlong/project_6
2026-08-15 00:54:18 +08:00
1af7e7cf48
fix: use c10::cuda::getCurrentCUDAStream().stream() for corex torch
dylanyunlong
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dylanyunlong/project_6
2026-08-15 00:35:40 +08:00
3bee73207e
fix: add cuda_runtime.h to hgemm_bind.cpp for cudaStream_t
dylanyunlong
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dylanyunlong/project_6
2026-08-15 00:25:59 +08:00
09e5261ba6
refactor: hgemm_blocktiling.cu — strict 1:1 from siboehm kernel 6
ab42fc1fd7
feat: hgemm_blocktiling.cu — FP16 GEMM kernel for MoE expert dispatch on BI-V100
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dylanyunlong
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dylanyunlong/project_6
2026-08-14 23:15:24 +08:00
9ca33cf4d5
upstream: add GEMM kernel references from 4 repos for BI-V100 porting
29ecc2e602
feat: moe_expert_gemm.cpp — C++ loop over experts via ixformer_linear (replaces Python for-loop)
0ace44e293
test: cat ixinfer.h + functional batched GEMM test on BI-V100
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dylanyunlong
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dylanyunlong/project_6
2026-08-14 20:05:50 +08:00
bfc4de2cf3
test: probe cuinfer + cublasLt + cublas batched GEMM APIs for MoE expert dispatch
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