1 citations · 1 across the 4 of their papers we have counts for
5 papers
Communication Lower Bounds and Algorithms for Sketching with Random Dense Matrices
Hussam Al Daas, Grey Ballard, Laura Grigori +4
Sketching is widely used in randomized linear algebra for low-rank matrix approximation, column subset selection, and many other problems, and it has gained significant traction in…
Minimizing Communication for Parallel Symmetric Tensor Times Same Vector Computation
Hussam Al Daas, Grey Ballard, Laura Grigori +3
In this article, we focus on the parallel communication cost of multiplying the same vector along two modes of a -dimensional symmetric tensor. This is a key computation in the…
Communication Lower Bounds and Optimal Algorithms for Symmetric Matrix Computations
Hussam Al Daas, Grey Ballard, Laura Grigori +3
In this article, we focus on the communication costs of three symmetric matrix computations: i) multiplying a matrix with its transpose, known as a symmetric rank-k update (SYRK) i…
Communication Lower Bounds and Optimal Algorithms for Multiple Tensor-Times-Matrix Computation
Hussam Al Daas, Grey Ballard, Laura Grigori +2
Multiple Tensor-Times-Matrix (Multi-TTM) is a key computation in algorithms for computing and operating with the Tucker tensor decomposition, which is frequently used in multidimen…
Tight Memory-Independent Parallel Matrix Multiplication Communication Lower Bounds
Hussam Al Daas, Grey Ballard, Laura Grigori +2
Communication lower bounds have long been established for matrix multiplication algorithms. However, most methods of asymptotic analysis have either ignored the constant factors or…