Infinite-precision inner product and sparse matrix-vector multiplication using Ozaki scheme with Dot2 on manycore processors

DOI10.1007/978-3-031-30442-2_4OpenAlexW4367294087MaRDI QIDQ6135463

Toshiyuki Imamura, Katsuhisa Ozaki, Takeshi Ogita, Daichi Mukunoki

Publication date: 25 August 2023

Published in: Parallel Processing and Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-031-30442-2_4

zbMATH Keywords

reproducibleinner productaccurateconjugate gradient (CG)sparse matrix-vector multiplication (SpMV)infinite-precision

Mathematics Subject Classification ID

Parallel algorithms in computer science (68W10) Parallel numerical computation (65Y05)

Cites Work

• Error-free transformations of matrix multiplication by using fast routines of matrix multiplication and its applications
• Implementing exact real arithmetic in python, C++ and C
• Reproducibility strategies for parallel preconditioned conjugate gradient
• Performance and energy consumption of accurate and mixed-precision linear algebra kernels on GPUs
• Efficiency of Reproducible Level 1 BLAS
• The university of Florida sparse matrix collection
• RealLib: An efficient implementation of exact real arithmetic
• MPFR
• Accurate Floating-Point Summation Part II: Sign, K-Fold Faithful and Rounding to Nearest
• High-precision division and square root
• Algorithms for Efficient Reproducible Floating Point Summation
• Design, implementation and testing of extended and mixed precision BLAS
• Accurate Sum and Dot Product
• Unnamed Item
• Unnamed Item

This page was built for publication: Infinite-precision inner product and sparse matrix-vector multiplication using Ozaki scheme with Dot2 on manycore processors