This project performs operations on matrices, including multiplication and calculating the sum of the smallest elements in each row of the resulting matrix. Users can input matrices manually or ...

Matrices are stored dynamically using a pointer to structures. Memory allocation and deallocation are handled efficiently. Operations are optimized for performance ...

ログインして、InfoQのすべての体験をアンロックしましょう！お気に入りの著者やトピックの最新情報を入手し、コンテンツと交流し、限定リソースをダウンロードできます。 MITのComputer Science & Artificial Intelligence Lab(CSAIL)に所属する研究者たちが、AMM ...

The most widely used matrix-matrix multiplication routine is GEMM (GEneral Matrix Multiplication) from the BLAS (Basic Linear Algebra Subroutines) library. And these days it can be found being used in ...

Abstract: Sparse Matrix-Matrix Multiplication (SpMM) is a widely used algorithm in Machine Learning, particularly in the increasingly popular Graph Neural Networks (GNNs). SpMM is an essential ...

Abstract: Matrix multiplication serves as a critical operation in neural networks and scientific computing, where algorithmic improvements can significantly impact execution speed. Existing optimized ...

This paper addresses the problem of rectangular matrix multiplication on bidirectional linear systolic arrays (SAs). We analyze all bidirectional linear SAs in terms of efficiency. We conclude that ...