Abstract. The fast matrix multiplication algorithm by Strassen is used to obtain the triangular factorization of a permutation of any nonsingular matrix of ordern in operations, and, hence, the inverse of any nonsingular matrix in 1. Introduction. Strassen [3] has given an algorithm using noncom...
Solving many scientific and technical applications entails the use of matrix multiplies somewhere in the algorithm and thus the computer code. With today’s multicore CPUs, proper use of complier directives can speed up matrix multiplies significantly. OpenMP is an API that supports multi-platform sh...
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 ...
For nD cases, the first two dimensions specify the matrix multiply involved. The remaining dimensions are duplicated and specify the number of individual matrix multiplies to perform for the result. i.e., MTIMESX treats these cases as arrays of 2D matrices and performs the operation...
A Heterogeneous Accelerated Matrix Multiplication: OpenCL + APU + GPU+ Fast Matrix MultiplyComputer Science - Mathematical SoftwareG.4As users and developers, we are witnessing the opening of a new computing scenario: the introduction of hybrid processors into a single die, such as an accelerated ...
Estimation of the weighted mean and covariance matrix using an online algorithm (Clarke, 1971). Computation of central moments up to fourth order using an online algorithm (Spicer, 1972). Fast computation of Hadamard product using unrolled loops. ...
src .gitignore LICENSE README.md README MIT license mtimesx Fast Matrix Multiply with Multi-Dimensional Support MTIMESXis a fast general purpose matrix and scalar multiply routine that has the following features: Supports multi-dimensional (nD, n>2) arrays directly ...
identify opportunities on commodity hardware for a single-wide (≥8b) multiply to compute a dot product of two vectors with multiple narrow (<8b) elements propose ULPPACK, an efficient implementation of sub-8-bit GEMM (General Matrix Multiplication) computation, by leveraging efficient packing and...
Implement Int8 matrix multiply operations from ARMv8.6. AArch64 Advanced SIMD and FP Int8 matrix multiply instructions are automatically enabled when has_arm_v8-6 is true. - 0, Not implemented. - 1, AArch64 Advanced SIMD and FP Int8 matrix multiply instructions only (FEAT_I8MM). - 2,...
We present an advanced eigenvalue alorithm - the so-called Jacobi-Davidson algorithm - in combination with an efficient parallel matrix-vector multiplication. This implementation allows the calculation of several specified eigenvalues with high accuracy on modern supercomputers, such as CRAY T3E and NEC...