Details
metal : few-row MMA mat-mul for the remaining src0 types (#30065)
The generic few-row MMA kernel works for any type with a 16-weight
dequantizer, so it now also takes BF16, Q1_0, Q2_0, MXFP4, Q2_K, Q3_K,
TQ2_0 and the IQ types. Each type starts at the row count where it beats
the current kernels on an M3 Ultra: 5 rows for TQ2_0, 4 for BF16, 3
for MXFP4, Q2_0, Q2_K and IQ4_NL, and 2 for the others.
test-backend-ops perf -o MUL_MAT, m=4096, k=14336, M3 Ultra, time of this
change over master (mean of two interleaved runs each): 0.23 to 0.98 from
the threshold to 8 rows, 0.24 to 0.33 at 9 to 16 rows, and 0.99 to 1.01 at
1 and 512 rows.
Website:
Attestations:
macOS/iOS:
- macOS Apple Silicon (arm64)
- macOS Apple Silicon (arm64, KleidiAI enabled) DISABLED
- macOS Intel (x64)
- iOS XCFramework
Linux:
- Ubuntu x64 (CPU)
- Ubuntu arm64 (CPU)
- Ubuntu s390x (CPU)
- Ubuntu x64 (Vulkan)
- Ubuntu arm64 (Vulkan)
- Ubuntu x64 (CUDA 12) - CUDA 12.8 libraries
- Ubuntu x64 (CUDA 13) - CUDA 13.4 libraries
- Ubuntu arm64 (CUDA 13) - CUDA 13.4 libraries
- Ubuntu x64 (ROCm 10.0)
- Ubuntu x64 (OpenVINO)
- Ubuntu x64 (SYCL FP32)
- Ubuntu x64 (SYCL FP16)
- Linux arm64 (Snapdragon: CPU, Adreno GPU, Hexagon NPU) - setup guide
Android:
Windows:
- Windows x64 (CPU)
- Windows arm64 (CPU)
- Windows arm64 (OpenCL Adreno)
- Windows x64 (CUDA 12) - CUDA 12.4 DLLs
- Windows x64 (CUDA 13) - CUDA 13.4 DLLs
- Windows arm64 (CUDA 13) - CUDA 13.4 DLLs
- Windows x64 (Vulkan)
- Windows arm64 (Vulkan)
- Windows x64 (OpenVINO)
- Windows x64 (SYCL)
- Windows x64 (ROCm 10.0)
openEuler:
- DISABLED
- openEuler x86 (310p)
- openEuler x86 (910b, ACL Graph)
- openEuler aarch64 (310p)
- openEuler aarch64 (910b, ACL Graph)
UI: