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feat: Support for BLAS methods on AMD GPUs, CPU libraries, and improvements on CUDA APIs - #9

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sanjibansg wants to merge 28 commits into
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feat: Support for BLAS methods on AMD GPUs, CPU libraries, and improvements on CUDA APIs#9
sanjibansg wants to merge 28 commits into
mainfrom
dev

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@sanjibansg sanjibansg commented Mar 21, 2026

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This PR adds configurable leading dimensions for the matrix-mul functions targeted for cuBLASLt

@sanjibansg sanjibansg linked an issue Mar 21, 2026 that may be closed by this pull request
Configurable Leading dimensions in Gemm functions for cublaslt #7
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sanjibansg and others added 13 commits April 17, 2026 12:50
@sanjibansg
fix: use explicit data type for signatures with pointer arguments
c995464
@sanjibansg
fix: non transpose axis for matmul method
75f75a4
@sanjibansg
fix (experimental): layout shape order
ed303fb
@sanjibansg
feat: cuda cleanup and cpu blas api
54a9401
@sanjibansg
feat: matmul method on raw cuda pointers
066fdae
@sanjibansg
fix: remove extra template parameter in cuda matmul method on raw poi…
1f1c4c7 
…nters
@sanjibansg
fix: method signature for matmul on cuda raw pointers
a867939
@sanjibansg
fix: dimension order for checkAddLayout method in cuda
ad41e99
@sanjibansg
fix: correct transpose values while adding layouts for cuda gemm methods
f86d299
@sanjibansg
feat: gemm apis for alpaka views
7b2133c
@sanjibansg
feat: gemm functions for cublas using raw pointers
6f2a9e1
@sanjibansg
feat: strided batch computation for gemm in cublaslt
fa108fb
@sanjibansg
feat: support for gemm functions on AMD hardware using hipBLASLt and …
97c12bc 
…cpu blas methods from different libraries
@sanjibansg sanjibansg changed the title feat: Configurable leading dimensions for Gemm functions with cuBLASLt feat: Support for BLAS methods on AMD GPUs, CPU libraries, and improvements on CUDA APIs Aug 11, 2026
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sanjibansg commented Aug 17, 2026

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/runtest h100

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sanjibansg commented Aug 17, 2026

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/runtest h100

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/runtest h100

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/runtest (h100): triggered - view run

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/runtest (h100): GPU Unit Tests ❌ failed - view run

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/runtest h100

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/runtest (h100): triggered - view run

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/runtest (h100): GPU Unit Tests ❌ failed - view run

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/runtest h100

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/runtest (h100): triggered - view run

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/runtest mi300x

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/runtest (mi300x): triggered - view run

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/runtest (mi300x): GPU Unit Tests ✅ passed - view run

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/runtest h100

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/runtest (h100): triggered - view run

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/runtest (h100): GPU Unit Tests ✅ passed - view run

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/runtest h100

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/runtest (h100): triggered - view run

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/runtest (h100): GPU Unit Tests ✅ passed - view run

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/runbenchmark h100-47gb

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/runbenchmark (h100-47gb): triggered - view run

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Benchmark results (mi300x)

main does not yet support the benchmark harness - showing PR results only.

── PR ──────────────────────────────────────────────────────────────
sofieBLAS benchmark  (warmup=5, iterations=20)

Backend        M=N=K      avg (ms)       GFLOP/s
------------------------------------------------
hip              256         0.008       4305.66
hip              512         0.007      41122.20
hip             1024         0.024      87740.31
hip             2048         0.179      96138.75
hip             4096         1.681      81782.96

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/runbenchmark (h100-47gb): Benchmark ✅ completed - view results

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/runbenchmark mi300x

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/runbenchmark (mi300x): triggered - view run

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/runbenchmark (mi300x): Benchmark ✅ completed - view results

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Configurable Leading dimensions in Gemm functions for cublaslt

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