282 citations · 531 across the 15 of their papers we have counts for
16 papers
Sparsifying the Operators of Fast Matrix Multiplication Algorithms
Gal Beniamini, Nathan Cheng, Olga Holtz +2
Fast matrix multiplication algorithms may be useful, provided that their running time is good in practice. Particularly, the leading coefficient of their arithmetic complexity need…
Network Partitioning and Avoidable Contention
Yishai Oltchik, Oded Schwartz
Network contention frequently dominates the run time of parallel algorithms and limits scaling performance. Most previous studies mitigate or eliminate contention by utilizing one…
High-Performance Algorithms for Computing the Sign Function of Triangular Matrices
Vadim Stotland, Oded Schwartz, Sivan Toledo
Algorithms and implementations for computing the sign function of a triangular matrix are fundamental building blocks in algorithms for computing the sign of arbitrary square real…
Hypergraph Partitioning for Sparse Matrix-Matrix Multiplication
Grey Ballard, Alex Druinsky, Nicholas Knight +1
We propose a fine-grained hypergraph model for sparse matrix-matrix multiplication (SpGEMM), a key computational kernel in scientific computing and data analysis whose performance…
Exploiting Multiple Levels of Parallelism in Sparse Matrix-Matrix Multiplication
Ariful Azad, Grey Ballard, Aydin Buluc +5
Sparse matrix-matrix multiplication (or SpGEMM) is a key primitive for many high-performance graph algorithms as well as for some linear solvers, such as algebraic multigrid. The s…
Improving the numerical stability of fast matrix multiplication
Grey Ballard, Austin R. Benson, Alex Druinsky +2
Fast algorithms for matrix multiplication, namely those that perform asymptotically fewer scalar operations than the classical algorithm, have been considered primarily of theoreti…