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Matrix Multiplication Kernel Specification

Version: v1.2.3 | Status: Active | Last Updated: March 2026

Overview

Provides a tiled (cache-efficient) matrix multiplication kernel in pure Python/NumPy. Implements BLAS-style blocked matmul for improved cache locality, plus batched multiplication and FLOP counting.

Functional Requirements

  1. Tiled matrix multiplication with configurable block size for cache efficiency
  2. Batched matrix multiplication support for 3D tensor inputs
  3. FLOP counting via matmul_flops(M, K, N) = 2MK*N

Interface

from codomyrmex.matmul_kernel import tiled_matmul, batched_matmul, matmul_flops

C = tiled_matmul(A, B, tile_size=32)
flops = matmul_flops(M=128, K=64, N=256)

Exports

tiled_matmul, batched_matmul, matmul_flops

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