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Daichi Mukunoki

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Journal Articles

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2020
[j1]
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  - journals/jcam/MukunokiO20
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Daichi Mukunoki, Takeshi Ogita:
Performance and energy consumption of accurate and mixed-precision linear algebra kernels on GPUs. J. Comput. Appl. Math. 372: 112701 (2020)

Conference and Workshop Papers

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2024
[c22]
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Stef Graillat, Fabienne Jézéquel, Théo Mary, Roméo Molina, Daichi Mukunoki:
Reduced-Precision and Reduced-Exponent Formats for Accelerating Adaptive Precision Sparse Matrix-Vector Product. Euro-Par (3) 2024: 17-30
2023
[c21]
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Daichi Mukunoki, Masatoshi Kawai, Toshiyuki Imamura:
Sparse Matrix-Vector Multiplication with Reduced-Precision Memory Accessor. MCSoC 2023: 608-615
2022
[c20]
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  - conf/ppam/MukunokiOOI22
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Daichi Mukunoki, Katsuhisa Ozaki, Takeshi Ogita, Toshiyuki Imamura:
Infinite-Precision Inner Product and Sparse Matrix-Vector Multiplication Using Ozaki Scheme with Dot2 on Manycore Processors. PPAM (1) 2022: 40-54
2021
[c19]
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  - conf/hpcasia/MukunokiOOI21
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Daichi Mukunoki, Katsuhisa Ozaki, Takeshi Ogita, Roman Iakymchuk:
Conjugate Gradient Solvers with High Accuracy and Bit-wise Reproducibility between CPU and GPU using Ozaki scheme. HPC Asia 2021: 100-109
[c18]
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  - conf/iccsa/HarayamaKMIT21
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Takeyuki Harayama, Shuhei Kudo, Daichi Mukunoki, Toshiyuki Imamura, Daisuke Takahashi:
A Rapid Euclidean Norm Calculation Algorithm that Reduces Overflow and Underflow. ICCSA (1) 2021: 95-110
[c17]
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Daichi Mukunoki, Katsuhisa Ozaki, Takeshi Ogita, Toshiyuki Imamura:
Accurate Matrix Multiplication on Binary128 Format Accelerated by Ozaki Scheme. ICPP 2021: 78:1-78:11
[c16]
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  - conf/ipps/DomkeVDCO0SMPWM21
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Jens Domke, Emil Vatai, Aleksandr Drozd, Peng Chen, Yosuke Oyama, Lingqi Zhang, Shweta Salaria, Daichi Mukunoki, Artur Podobas, Mohamed Wahib, Satoshi Matsuoka:
Matrix Engines for High Performance Computing: A Paragon of Performance or Grasping at Straws? IPDPS 2021: 1056-1065
[c15]
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Daichi Mukunoki, Yusuke Hirota, Toshiyuki Imamura:
Task Scheduling Strategies for Batched Basic Linear Algebra Subprograms on Many-core CPUs. MCSoC 2021: 234-241
2020
[c14]
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  - conf/supercomputer/MukunokiOOI20
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Daichi Mukunoki, Katsuhisa Ozaki, Takeshi Ogita, Toshiyuki Imamura:
DGEMM Using Tensor Cores, and Its Accurate and Reproducible Versions. ISC 2020: 230-248
[c13]
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  - conf/vstte/JezequelGMII20
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Fabienne Jézéquel, Stef Graillat, Daichi Mukunoki, Toshiyuki Imamura, Roman Iakymchuk:
Can We Avoid Rounding-Error Estimation in HPC Codes and Still Get Trustworthy Results? VSTTE 2020: 163-177
2019
[c12]
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  - conf/parco/TanIM19
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Yiyu Tan, Toshiyuki Imamura, Daichi Mukunoki:
Design of an FPGA-Based Matrix Multiplier with Task Parallelism. PARCO 2019: 241-250
[c11]
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Daichi Mukunoki, Takeshi Ogita, Katsuhisa Ozaki:
Reproducible BLAS Routines with Tunable Accuracy Using Ozaki Scheme for Many-Core Architectures. PPAM (1) 2019: 516-527
2018
[c10]
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Daichi Mukunoki, Toshiyuki Imamura:
Performance Analysis of 2D-compatible 2.5D-PDGEMM on Knights Landing Cluster. ICCS (3) 2018: 853-858
2017
[c9]
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Toshiyuki Imamura, Daichi Mukunoki, Yusuke Hirota, Susumu Yamada, Masahiko Machida:
Design Towards Modern High Performance Numerical LA Library Enabling Heterogeneity and Flexible Data Formats. PARCO 2017: 97-106
[c8]
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Daichi Mukunoki, Toshiyuki Imamura:
Implementation and Performance Analysis of 2.5D-PDGEMM on the K Computer. PPAM (1) 2017: 348-358
2016
[c7]
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Daichi Mukunoki, Toshiyuki Imamura:
Reduced-Precision Floating-Point Formats on GPUs for High Performance and Energy Efficient Computation. CLUSTER 2016: 144-145
[c6]
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Daichi Mukunoki, Toshiyuki Imamura, Daisuke Takahashi:
Automatic Thread-Block Size Adjustment for Memory-Bound BLAS Kernels on GPUs. MCSoC 2016: 377-384
2015
[c5]
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Daichi Mukunoki, Toshiyuki Imamura, Daisuke Takahashi:
Fast Implementation of General Matrix-Vector Multiplication (GEMV) on Kepler GPUs. PDP 2015: 642-650
2013
[c4]
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Daichi Mukunoki, Daisuke Takahashi:
Optimization of Sparse Matrix-Vector Multiplication for CRS Format on NVIDIA Kepler Architecture GPUs. ICCSA (5) 2013: 211-223
[c3]
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Daichi Mukunoki, Daisuke Takahashi:
Using Quadruple Precision Arithmetic to Accelerate Krylov Subspace Methods on GPUs. PPAM (1) 2013: 632-642
2012
[c2]
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  - conf/ipps/MukunokiT12
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Daichi Mukunoki, Daisuke Takahashi:
Implementation and Evaluation of Triple Precision BLAS Subroutines on GPUs. IPDPS Workshops 2012: 1378-1386
2010
[c1]
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Daichi Mukunoki, Daisuke Takahashi:
Implementation and Evaluation of Quadruple Precision BLAS Functions on GPUs. PARA (1) 2010: 249-259

Informal and Other Publications

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2020
[i2]
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  - journals/corr/abs-2004-04628
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Roman Iakymchuk, Daichi Mukunoki, Artur Podobas, Fabienne Jézéquel, Toshiyuki Imamura, Norihisa Fujita, Jens Huthmann, Shuhei Kudo, Yiyu Tan, Jens Domke, Kai Torben Ohlhus, Takeshi Fukaya, Takeo Hoshi, Yuki Murakami, Maho Nakata, Takeshi Ogita, Kentaro Sano, Taisuke Boku:
White Paper from Workshop on Large-scale Parallel Numerical Computing Technology (LSPANC 2020): HPC and Computer Arithmetic toward Minimal-Precision Computing. CoRR abs/2004.04628 (2020)
[i1]
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  - journals/corr/abs-2010-14373
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Jens Domke, Emil Vatai, Aleksandr Drozd, Peng Chen, Yosuke Oyama, Lingqi Zhang, Shweta Salaria, Daichi Mukunoki, Artur Podobas, Mohamed Wahib, Satoshi Matsuoka:
Matrix Engines for High Performance Computing: A Paragon of Performance or Grasping at Straws? CoRR abs/2010.14373 (2020)

Coauthor Index

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