Choi, J.: A new parallel matrix multiplication algorithm on distributed- memory concurrent computers. Concurrency: Practice and Experience 10(8), 655-670 (1998)J. Choi, A new parallel matrix multiplication algo
COSMA is a parallel, high-performance, GPU-accelerated, matrix-matrix multiplication algorithm that is communication-optimal for all combinations of matrix dimensions, number of processors and memory sizes, without the need for any parameter tuning. The key idea behind COSMA is to first derive a ti...
Here we present a hyperparallel quantum algorithm for matrix multiplication with time complexityO(N2), which is better than the best known classical algorithm. In our scheme, anNdimensional vector is mapped to the state of a single source, which is separated toNpaths. With the assistance of ...
Case Study in Matrix Multiplication Based on slides by: Kathy Yelick .cs.berkeley.edu/~yelick/cs194f07 & James Demmel and Horst Simon http://.cs.berkeley.edu/~demmel/cs267_Spr10/ CPE779 Parallel Computing - Spring 2010 * Naïve Matrix Multiply {implements C = C + A*B} for i = ...
It is found that the basic matrix multiplication is far better than the Strassen's matrix multiplication algorithm beacause of higher memory usage. This analysis is important because memory plays more vital role in deciding the efficiency of an algorithm. Additional temporary storage causes increase ...
Tiled matrix multiplication algorithm. For simplicity of illustration, we assumed that matrices A and B are square and the number of tiles in each direction is equal for both matrices (=T). Note that the total compute for the tiled matrix multiplication is the same as that for the elemental...
Algorithm for Strassen's matrix multiplication Algorithm Strassen(n, a, b, d) begin If n = threshold then compute C = a * b is a conventional matrix. Else Partition a into four sub matrices a11, a12, a21, a22. Partition b into four sub matrices b11, b12, b21, b22. ...
1. Background: Matrix-Matrix Multiplication GEMMs (General Matrix Multiplications) are a fundamental building block for many operations in neural networks, for example fully-connected layers, recurrent layers such as RNNs, LSTMs or GRUs, and convolutional layers. In this guide, we describe GEMM...
Matrix-vector multiplication The methods for photonic matrix-vector multiplications (MVMs) mainly fall into three categories: the plane light conversion (PLC) method, Mach–Zehnder interferometer (MZI) method and wavelength division multiplexing (WDM) method. The detailed mechanism of these MVMs can be...
For m≤ n 1.14, the new algorithm performs an almost optimal number of only n 2 + o(1) operations. For m≤ n 1.68, the new algorithm is also faster than the best known matrix multiplication algorithm for dense matrices which uses O(n 2.38) algebraic operations. The new algorithm ...