GitHub

03-matrix-multiplication.py

* Program re-ordering for improved L2 cache hit rate. * Automatic performance tuning. # Motivations # Matrix multiplications are a key building block of most modern high-performance computing systems.
IEEE

Vectorization of Narrow Matrix Multiplication for Ascend AI Inference Acceleration

Abstract: This research proposes and evaluates a novel approach to optimizing matrix multiplication (MatMul) on Huawei Ascend NPUs, motivated by a key insight: during matrix-vector multiplication ...
GitHub

02_matrix_multiply.py

Naive matrix multiply: C = A * B. Each thread computes one element of C: C[row, col] = sum_k A[row, k] * B[k, col] # 2D indexing: derive global row/col from block and thread indices. # blockIdx.y, ...
IEEE

Energy Efficient Exact and Approximate Systolic Array Architecture for Matrix Multiplication

Abstract: Deep Neural Networks (DNNs) require highly efficient matrix multiplication engines for complex computations. This paper presents a Systolic Array (SA) architecture incorporating novel exact ...