activity
20192022
most citedEffect of Mixed Precision Computing on H-Matrix Vector Multiplication in BEM Analysis

6 citations · 6 across the 2 of their papers we have counts for

collaborators

5 papers

math.NA2022

Convergence Acceleration of Preconditioned CG Solver Based on Error Vector Sampling for a Sequence of Linear Systems

Takeshi Iwashita, Kota Ikehara, Takeshi Fukaya +1

In this paper, we focus on solving a sequence of linear systems with an identical (or similar) coefficient matrix. For this type of problems, we investigate the subspace correction…

cs.DC2021

Accelerating the SpMV kernel on standard CPUs by exploiting the partially diagonal structures

Takeshi Fukaya, Koki Ishida, Akie Miura +2

Sparse Matrix Vector multiplication (SpMV) is one of basic building blocks in scientific computing, and acceleration of SpMV has been continuously required. In this research, we ai…

math.NA2020

An Integer Arithmetic-Based Sparse Linear Solver Using a GMRES Method and Iterative Refinement

Takeshi Iwashita, Kengo Suzuki, Takeshi Fukaya

In this paper, we develop a (preconditioned) GMRES solver based on integer arithmetic, and introduce an iterative refinement framework for the solver. We describe the data format f…

cs.MS20196 cited

Effect of Mixed Precision Computing on H-Matrix Vector Multiplication in BEM Analysis

Rise Ooi, Takeshi Iwashita, Takeshi Fukaya +2

Hierarchical Matrix (H-matrix) is an approximation technique which splits a target dense matrix into multiple submatrices, and where a selected portion of submatrices are low-rank…

cs.DC2019

Hierarchical Block Multi-Color Ordering: A New Parallel Ordering Method for Vectorization and Parallelization of the Sparse Triangular Solver in the ICCG Method

Takeshi Iwashita, Senxi Li, Takeshi Fukaya

In this paper, we propose a new parallel ordering method to vectorize and parallelize the sparse triangular solver, which is called hierarchical block multi-color ordering. In this…