1. Communication Lower Bounds and Optimal Algorithms for Symmetric Matrix Computations
- Author
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Daas, Hussam Al, Ballard, Grey, Grigori, Laura, Kumar, Suraj, Rouse, Kathryn, and Verite, Mathieu
- Subjects
Computer Science - Distributed, Parallel, and Cluster Computing - Abstract
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) ii) adding the result of the multiplication of a matrix with the transpose of another matrix and the transpose of that result, known as a symmetric rank-2k update (SYR2K) iii) performing matrix multiplication with a symmetric input matrix (SYMM). All three computations appear in the Level 3 Basic Linear Algebra Subroutines (BLAS) and have wide use in applications involving symmetric matrices. We establish communication lower bounds for these kernels using sequential and distributed-memory parallel computational models, and we show that our bounds are tight by presenting communication-optimal algorithms for each setting. Our lower bound proofs rely on applying a geometric inequality for symmetric computations and analytically solving constrained nonlinear optimization problems. The symmetric matrix and its corresponding computations are accessed and performed according to a triangular block partitioning scheme in the optimal algorithms., Comment: 43 pages, 6 figures. To be published in ACM Transactions on Parallel Computing
- Published
- 2024