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Akira Yamaoka

dblp:60/2199 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 1996
—ORCID · unresolved

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
2 papers
Processor architecture and microarchitecture · 73% Parallel and multicore computing · 12% Performance modeling and evaluation · 11%

Topics — the 7 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Processor architecture and microarchitecture › pipelining
pipeline interlock
0.011996
Hierarchical Execution to Speed Up Pipeline Interlock in Mainframe Computers · IEEE Trans. Computers 1996
Processor architecture and microarchitecture › superscalar processor
superscalar pipeline
0.011996
Hierarchical Execution to Speed Up Pipeline Interlock in Mainframe Computers · IEEE Trans. Computers 1996
Performance modeling and evaluation › benchmarking
benchmark evaluation
0.011996
Hierarchical Execution to Speed Up Pipeline Interlock in Mainframe Computers · IEEE Trans. Computers 1996
Parallel and multicore computing
parallel architecture
0.011983
PACS: A Parallel Microprocessor Array for Scientific Calculations · ACM Trans. Comput. Syst. 1983
Parallel and multicore computing › parallel computing
parallel scientific computing
0.011983
PACS: A Parallel Microprocessor Array for Scientific Calculations · ACM Trans. Comput. Syst. 1983
High-performance computing › numerical linear algebra › linear solver
poisson solver
0.011983
PACS: A Parallel Microprocessor Array for Scientific Calculations · ACM Trans. Comput. Syst. 1983
High-performance computing › scientific computing
scientific computing application
0.011983
PACS: A Parallel Microprocessor Array for Scientific Calculations · ACM Trans. Comput. Syst. 1983

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

barrier synchronization · 0.0
YearPublicationVenuePosition
1996 Hierarchical Execution to Speed Up Pipeline Interlock in Mainframe Computers
abstract
This paper introduces a methodology, called hierarchical execution, which reduces stalls caused by pipeline interlocks such as data and control dependencies. Since a lot of software has been accumulated in mainframe computer systems as object code, it is important to improve performance without having to recompile the code for optimization. Our methodology consists of a simple pre-ALU that generates results, with shorter latency than the main ALU, asynchronously, which reduces the overhead especially for address generation interlocks and branch instructions. This method was implemented in Hitachi's mainframe processors, M-680 and M-880. In M-680, the pre-ALU, together with the instruction decoder, processes instructions in superpipelined fashion, which further improves performance. The aggregate effect of hierarchical execution on CPU time, for evaluated benchmarks, is 10% on average, with only a 1.6% increase in hardware. Therefore, we can roughly say that the hierarchical execution method improved cost performance by 8%.
Yooichi Shintani, Toru Shonai, Hiroshi Kurokawa, Kazunori Kuriyama, Akira Yamaoka
IEEE Trans. Computers5
1983 PACS: A Parallel Microprocessor Array for Scientific Calculations
abstract
PACS-32 is a prototype supercomputer used for a broad range of scientific calculations.It has a synchronizable MIMD processor array, and on the basis of this facility, it provides efficient nearest neighbor communication.Processors are combined into a rectangular array with endaround connections, and can synchronize at user-specified points with little overhead.The hardware has been constructed with 32 processors, and the operating software includes a highlevel language.The PACS-32 system has performed in a number of applications, such as Poisson equation solving, nuclear reactor calculation, aerodynamics, Monte Carlo simulation of plasma particles, and molecular dynamics modeling in solid state physics.The processor efficiency measure ranges from 78 percent through 99 percent in these applications.
Tsutomu Hoshino, Toshio Kawai, Tomonori Shirakawa, Jun'ichi Higashino, Akira Yamaoka, Hachidai Ito, Kazuo Sawada
ACM Trans. Comput. Syst.5