hipBLASLt provider operation support#
2026-03-31
1 min read time
The hipBLASLt provider plugin integrates with the ROCm hipBLASLt library that provides optimized GEMM operations.
Operation support#
The hipBLASLt provider plugin supports standalone Matmul (GEMM, general matrix multiplication) operations with these features and constraints:
Input and output data types:
FP32: Single-precision floating point (32-bit)FP16: Half-precision floating point (16-bit)BFP16: Brain floating point (16-bit).
Compute data type:
FP32.Transposed inputs: Supported.
Batched matmuls: Only equal batch sizes are supported, along with broadcasting when one input has a single batch (batch=1).
Fused operations: Matmul supports fused bias, forward activation (ReLU, clamp, GELU with tanh approximation, and Swish with unit beta), and fused bias + forward activation (same supported activations).