White Paper from the Workshop on Large-scale Parallel Numerical Computing Technology (LSPANC 2020): HPC and Computer Arithmetic toward Minimal-Precision Computing
| Autor: | Iakymchuk, Roman, Mukunoki, Daichi, Podobas, Artur, Jézéquel, Fabienne, Imamura, Toshiyuki, Fujita, Norihisa, Huthmann, Jens, Kudo, Shuhei, Tan, Yiyu, Domke, Jens, Ohlhus, Kai, Fukaya, Takeshi, Hoshi, Takeo, Murakami, Yuki, Nakata, Maho, Ogita, Takeshi, Sano, Kentaro, Boku, Taisuke |
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| Přispěvatelé: | Iakymchuk, Roman, Fraunhofer Institute of Industrial Mathematics (Fraunhofer ITWM), Fraunhofer (Fraunhofer-Gesellschaft), Performance et Qualité des Algorithmes Numériques (PEQUAN), LIP6, Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), RIKEN Center for Computational Science [Kobe] (RIKEN CCS), RIKEN - Institute of Physical and Chemical Research [Japon] (RIKEN), Université Panthéon-Assas (UP2), Université de Tsukuba = University of Tsukuba, Tokyo Woman's Christian University (TWCU), Hokkaido University [Sapporo, Japan], Tottori University, University of Aizu [Japan] (UoA), Tokyo Woman's Christian University, Department of Mathematics |
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
[INFO.INFO-MS] Computer Science [cs]/Mathematical Software [cs.MS]
[INFO.INFO-AO]Computer Science [cs]/Computer Arithmetic [INFO.INFO-DC] Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC] [INFO.INFO-AO] Computer Science [cs]/Computer Arithmetic [INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC] [MATH.MATH-NA] Mathematics [math]/Numerical Analysis [math.NA] [MATH.MATH-NA]Mathematics [math]/Numerical Analysis [math.NA] [INFO.INFO-MS]Computer Science [cs]/Mathematical Software [cs.MS] |
| Popis: | In numerical computations, precision of floating-point computations is a key factor to determine the performance (speed and energy-efficiency) as well as the reliability (accuracy and reproducibility). However , precision generally plays a contrary role for both. Therefore, the ultimate concept for maximizing both at the same time is the minimal-precision computing through precision-tuning, which adjusts the optimal precision for each operation and data. Several studies have been already conducted for it so far (e.g. Precimoniuos and Verrou), but the scope of those studies is limited to the precision-tuning alone. Hence, we aim to propose a broader concept of the minimal-precision computing system with precision-tuning, involving both hardware and software stack. In 2019, we have started the Minimal-Precision Computing project to propose a more broad concept of the minimal-precision computing system with precision-tuning, involving both hardware and software stack. Specifically, our system combines (1) a precision-tuning method based on Discrete Stochastic Arithmetic (DSA), (2) arbitrary-precision arithmetic libraries, (3) fast and accurate numerical libraries, and (4) Field-Programmable Gate Array (FPGA) with High-Level Synthesis (HLS). In this white paper, we aim to provide an overview of various technologies related to minimal-and mixed-precision, to outline the future direction of the project, as well as to discuss current challenges together with our project members and guest speakers at the LSPANC 2020 workshop; https://www.r-ccs.riken.jp/labs/lpnctrt/lspanc2020jan/. |
| Databáze: | OpenAIRE |
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