Long Yixing 0ff1115a46 [CUDA] Implement BlockMaskedMM (#3299) ...

Co-authored-by: Cheng <git@zcbenz.com>

2026-03-27 06:57:26 +09:00

..

blas

Add Masked Scatter (#2663)

2025-11-19 14:53:32 -08:00

comparative

refactor: use time.perf_counter for consistent and accurate benchmarking (#2943)

2025-12-28 06:16:13 -08:00

batch_matmul_bench.py

Add isort pre-commit and run (#68)

2023-12-08 11:31:47 -08:00

block_masked_mm_bench.py

[CUDA] Implement BlockMaskedMM (#3299)

2026-03-27 06:57:26 +09:00

compile_bench.py

Add softmin, hardshrink, hardtanh (#1180)

2024-06-04 15:48:18 -07:00

conv1d_bench.py

Add groups to Conv1d (#948)

2024-04-27 06:24:57 -07:00

conv2d_bench_cpu.py

Conv cpu improvements (#1410)

2024-09-15 18:45:10 -07:00

conv2d_train_bench_cpu.py

Conv cpu improvements (#1410)

2024-09-15 18:45:10 -07:00

conv2d_transpose_bench_cpu.py

Conv cpu improvements (#1410)

2024-09-15 18:45:10 -07:00

conv3d_bench_cpu.py

Conv cpu improvements (#1410)

2024-09-15 18:45:10 -07:00

conv3d_bench.py

[Metal] Add implicit matmul pathway for mx.conv3d (#3147)

2026-02-23 17:52:50 -08:00

conv3d_train_bench_cpu.py

Conv cpu improvements (#1410)

2024-09-15 18:45:10 -07:00

conv3d_transpose_bench_cpu.py

Conv cpu improvements (#1410)

2024-09-15 18:45:10 -07:00

conv_bench.py

Add softmin, hardshrink, hardtanh (#1180)

2024-06-04 15:48:18 -07:00

conv_transpose_bench.py

Transposed Convolution (#1245)

2024-09-06 19:52:38 -07:00

conv_unaligned_bench.py

Add load_safe to the general conv loaders (#2258)

2025-06-10 20:58:16 -07:00

distributed_bench.py

MPI ops in GPU stream for faster comms (#1356)

2024-08-26 15:12:50 -07:00

einsum_bench.py

Einsum (#1269)

2024-07-25 09:36:44 -07:00

fft_bench.py

Feature complete Metal FFT (#1102)

2024-06-06 12:57:25 -07:00

gather_bench.py

Remove unused modules (#1949)

2025-03-10 06:05:26 -07:00

gather_mm_bench.py

Gather qmm batched kernel and refactoring of quantized (#2078)

2025-04-17 13:53:11 -07:00

gather_qmm_bench.py

Gather qmm batched kernel and refactoring of quantized (#2078)

2025-04-17 13:53:11 -07:00

hadamard_bench.py

Fast Hadamard Transform (#1249)

2024-07-09 20:39:01 -07:00

large_gemm_bench.py

Add NAX Split-K GEMM for large-K matmuls to improve performance (#3018)

2026-01-26 11:23:20 -08:00

layer_norm_bench.py

Change layernorms to two pass algorithm (#2246)

2025-06-06 13:34:56 -07:00

masked_scatter.py

[CUDA] Implement MaskedScatter (#3151)

2026-03-15 10:33:55 +09:00

rms_norm_bench.py

RMS norm without scaling (#1915)

2025-02-28 20:26:57 -08:00

rope_bench.py

Fix copy donation and add partial rope (#881)

2024-03-22 17:28:26 -07:00

scatter_bench.py

improvements to scatter / gather (#1541)

2024-10-30 19:30:54 -07:00

sdpa_bench.py

Support fused masking in Attention (#1924)

2025-03-20 11:01:32 -07:00

sdpa_vector_bench.py

Allow different value dimensions in sdpa_vector (#1811)

2025-01-31 20:58:59 -08:00

segmented_mm_bench.py

[CUDA] Implement SegmentedMM (#3238)

2026-03-11 13:31:43 -07:00

single_ops.py

Align mlx::core::min op nan propagation with NumPy (#2346)

2025-07-10 06:20:43 -07:00

slice_update_bench.py

Slice update with operation (#3266)

2026-03-18 06:18:02 -07:00

synchronize_bench.py

Faster synchronization Fence primitive (#1773)

2025-01-17 18:42:19 -08:00

time_utils.py

refactor: use time.perf_counter for consistent and accurate benchmarking (#2943)

2025-12-28 06:16:13 -08:00