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Naoyuki Shida

dblp:129/4310 · DBLP profile ↗
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3ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 2

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Processor architecture and microarchitecture · 67% High-performance computing · 33%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Processor architecture and microarchitecture
instruction set architecture
0.412020
Co-design for A64FX manycore processor and "Fugaku" · SC 2020
High-performance computing
supercomputer architecture
0.412020
Co-design for A64FX manycore processor and "Fugaku" · SC 2020

Methods — techniques the papers use, named apart from their topics

performance analysis · 0.4co-design · 0.4
YearPublicationVenuePosition
2020 Co-design for A64FX manycore processor and "Fugaku"
abstract
We have been carrying out the FLAGSHIP 2020 Project to develop the Japanese next-generation flagship supercomputer, the Post-K, recently named “Fugaku”. We have designed an original many core processor based on Armv8 instruction sets with the Scalable Vector Extension (SVE), an A64FX processor, as well as a system including interconnect and a storage subsystem with the industry partner, Fujitsu. The “co-design” of the system and applications is a key to making it power efficient and high performance. We determined many architectural parameters by reflecting an analysis of a set of target applications provided by applications teams. In this paper, we present the pragmatic practice of our co-design effort for “Fugaku”. As a result, the system has been proven to be a very power-efficient system, and it is confirmed that the performance of some target applications using the whole system is more than 100 times the performance of the K computer.
Mitsuhisa Sato, Yutaka Ishikawa, Hirofumi Tomita, Yuetsu Kodama, Tetsuya Odajima, Miwako Tsuji, Hisashi Yashiro, Masaki Aoki, Naoyuki Shida, Ikuo Miyoshi, Kouichi Hirai, Atsushi Furuya, Akira Asato, Kuniki Morita, Toshiyuki Shimizu
SC9
2019 A Memory Saving Communication Method Using Remote Atomic Operations
abstract
The MPI library for the K computer introduced a memory saving protocol. However, the protocol still requires memory in proportion to the number of MPI processes and a memory shortage can occur when the number of processes reaches millions or tens of millions. In order to solve the problem, we propose the shared receive buffer method which is a new communication protocol using remote atomic operations. This method is easily implemented if an interconnect has remote memory access and remote atomic memory operation. We implemented shared receive buffer method on PRIMEHPC FX100 system and evaluated. The per process memory usage of the proposed method is about one tenth compared to that of existing method.
Masaaki Fushimi, Takahiro Kawashima, Takafumi Nose, Nobutaka Ihara, Shinji Sumimoto, Naoyuki Shida
HPC Asia6
2018 The Tofu Interconnect D
abstract
In this paper, we introduce a new and highly scalable interconnect called Tofu interconnect D that will be used in the post-K machine. This machine will officially be operational around 2021. The letter D represents high “density” node and “dynamic” packet slicing for “dual-rail” transfer. Herein we describe the design and the evaluation results of TofuD. Due to the high-density packaging, the optical link ratio of TofuD has decreased to 25% from the 66% optical link ratio of Tofu2. TofuD applies a new technique called dynamic packet slicing to reduce latency and to improve fault resilience. The evaluation results show that the one-way 8-byte Put latency is 0.49 μs. This is 31% lower than the latency of Tofu2. The injection rate per node is 38.1 GB/s which is approximately 83% of the injection rate of Tofu2. The link efficiency is as high as approximately 93%.
Yuichiro Ajima, Takahiro Kawashima, Takayuki Okamoto, Naoyuki Shida, Kouichi Hirai, Toshiyuki Shimizu, Shinya Hiramoto, Yoshiro Ikeda, Takahide Yoshikawa, Kenji Uchida, Tomohiro Inoue
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