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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| ICM | 2024-03-22 09:50 |
Okinawa | Okinawa Prefectural Museum and Art Museum (Primary: On-site, Secondary: Online) |
Proposal for Parallel Code Generation and Dynamic Distributed-Cluster Selection in Ray Application Rina Ueno, Nao Nisijima (Hitachi)  ICM2023-53 |
In data analysis systems, a distributed processing infrastructure can be used to increase speed through parallelization ... [more] | ICM2023-53 pp.47-50 |
| EST | 2024-01-26 10:45 |
Kyoto | Kyoto University ROHM Plaza (Primary: On-site, Secondary: Online) |
Domain Decomposition Type Parallel High-Frequency Electromagnetic Finite Element Analysis Code by Applying Direct Methods for Sparse Matrices as Subdomain Solver Kento Ohnaka (Univ. of Miyazaki), Toshio Murayama, Sota Goto (UTokyo), Amane Takei (Univ. of Miyazaki) EST2023-114 |
ADVENTURE_FullWave, an electromagnetic field analysis code being developed by the authors, is implemented using a domain... [more] | EST2023-114 pp.84-89 |
| CPSY, IPSJ-ARC, IPSJ-HPC | 2023-12-05 10:55 |
Okinawa | Okinawa Industry Support Center (Primary: On-site, Secondary: Online) |
Performance improvements of Multi-Platform Parallel Computing System Based on Web Technologies Soki Imaizumi, Kanemitsu Ootsu, Takashi Yokota (Utsunomiya Univ.) CPSY2023-27 |
Web browsers can be used as architecture-independent execution environments, and nowadays they can provide the same func... [more] | CPSY2023-27 pp.1-6 |
| MW, EMCJ, EST, IEE-EMC [detail] | 2023-10-20 14:20 |
Yamagata | Yamagata University (Primary: On-site, Secondary: Online) |
Application of Sparse Direct Solver to Improve Convergence and Speed-up of the High-Frequency Electromagnetic Field Finite Element Analysis Code: ADVENTURE_FullWave Kento Ohnaka (Univ. of Miyazaki), Toshio Murayama, Sota Goto (UTokyo), Amane Takei (Univ. of Miyazaki) EMCJ2023-65 MW2023-119 EST2023-92 |
ADVENTURE_FullWave, an electromagnetic field analysis code being developed by the authors, uses the iterative domain dec... [more] | EMCJ2023-65 MW2023-119 EST2023-92 pp.152-157 |
| CPSY, DC, IPSJ-ARC [detail] | 2023-08-04 14:05 |
Hokkaido | Hakodate Arena (Primary: On-site, Secondary: Online) |
Development of computer cluster system based on Web technologies Soki Imaizumi, Kanemitsu Ootsu, Takashi Yokota (Utsunomiya Univ.) CPSY2023-20 DC2023-20 |
Currently, with the development of Web technology, Web applications with functions equivalent to native OS applications ... [more] | CPSY2023-20 DC2023-20 pp.72-77 |
| NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] | 2020-06-29 13:25 |
Online | Online | A Study on Centralized and Distributed Intelligent Particle Multi-Swarm Optimization Hiroshi Sho (Kyutech) NC2020-3 IBISML2020-3 |
In this paper, we propose a new method of distributed intelligent particle multi-swarm optimization (DIPMSO) contrast to... [more] | NC2020-3 IBISML2020-3 pp.15-20 |
| SAT, SANE (Joint) |
2020-02-20 13:50 |
Okinawa | Performance evaluation of distributed parallel backprojection for stripmap SAR imaging on various accelerators Masato Gocho, Noboru Oishi (Mitsubishi Electric) SANE2019-114 |
This paper presents a performance evaluation of the distributed parallel backprojection for stripmap sar imaging on vari... [more] | SANE2019-114 pp.85-89 |
|
| MoNA | 2017-12-21 15:45 |
Tokyo | Ochanomizu University | Consideration of Parallel Data Processing over an Apache Spark, a large-scale data distributed platform Kasumi Kato (Ocha Univ.), Atsuko Takefusa (NII), Hidemoto Nakada (AIST), Masato Oguchi (Ocha Univ.) MoNA2017-40 |
The Spread of cameras and sensors and cloud technologies enable us to obtain life logs at ordinary homes and transmit th... [more] | MoNA2017-40 pp.65-69 |
| IA, IN (Joint) |
2017-12-14 16:45 |
Hiroshima | Hiroshima City Univ. | Dynamic Partition by Local Calculation in Large Scale Distributed Graph Environment Yuta Yasumura, Kunitake Kaneko (Keio Univ.) IN2017-55 |
In the processing framework in the large scale distributed graph environment, the entire shape of the input graph is fir... [more] | IN2017-55 pp.55-60 |
| CPSY, DC, IPSJ-ARC (Joint) [detail] |
2017-07-26 14:00 |
Akita | Akita Atorion-Building (Akita) | A Study on Implementation Method of Byzantine Fault Tolerant Systems Takeru Nanao, Yudai Ishikawa, Masashi Imai (Hirosaki Univ.) DC2017-17 |
A fault tolerant system does not cause a failure even if a fault occurs. The algorithm OM has been proposed as a basic B... [more] | DC2017-17 pp.7-12 |
| CCS | 2016-08-10 12:30 |
Hokkaido | Yoichi Chuo kominkan | [Invited Lecture]
Topology-based Approach for Network Sensing and its Applications Kazuki Nakada (Hiroshima City Univ.), Keiji Miura (Kwansei Gakuin Univ.) CCS2016-25 |
In this presentation, we review a topology-based approach for network sensing and its applications. We here explain rece... [more] | CCS2016-25 pp.47-52 |
| NLP | 2016-07-22 10:00 |
Hokkaido | Hokkaido Univ. Centennial Hall | An Artificial Bee Colony Algorithm Suited for Parallel Distributed Processing Yu Isono, Tomoyuki Sasaki, Hidehiro Nakano, Arata Miyauchi (Tokyo City Univ.) NLP2016-40 |
As approximate solutions in large-scale problems are obtained by evolutionary computation algorithms, many search indivi... [more] | NLP2016-40 pp.33-38 |
| IE, IMQ, MVE, CQ (Joint) [detail] |
2016-03-08 09:15 |
Okinawa | Dynamically Assigned Distributed Processing System with SDN Switches Masahiko Kitamura, Hiroyuki Kimiyama, Tomoko Sawabe, Tatsuya Fujii (NTT), Kazunari Kojima, Mitsuru Maruyama (KAIT) CQ2015-134 |
The cloud services that enable us to use computing and networking resources on our demand drive many workflows into dist... [more] | CQ2015-134 pp.147-151 |
|
| SS, MSS | 2016-01-26 13:20 |
Ishikawa | Shiinoki-Geihin-Kan | Implementation of Parallel Distributed Graph Clustering Algorithm on Apache Spark with Node Partition and Aggregation in Large-Scale Graphs Riku Asayama, Kohei Sakurai, Satoshi Yamane (Kanazawa Univ.) MSS2015-60 SS2015-69 |
In this paper, we propose the rapid clustering method with the large-scaled graph structured data. Our approach is a dat... [more] | MSS2015-60 SS2015-69 pp.141-146 |
| R | 2015-10-16 11:00 |
Fukuoka | Irregularity Countermeasures in Massively Parallel BigData Processors Marat Zhanikeev (Kyutech) R2015-53 |
The term Massively Parallel BigData Processor names a recent advance in bigdata processing technology which has advanced... [more] | R2015-53 pp.7-14 |
|
| SC | 2015-03-28 10:55 |
Fukushima | Aizu Univ. | Parallel Processing of Large-Scale Graphs Using Spark on GPGPU Yuki Inamoto, Mikio Aoyama (Nanzan Univ.) SC2014-19 |
We propose a high performance computing method for large-scale graphs using the Spark on GPGPU. RDD, multiple sets of ab... [more] | SC2014-19 pp.31-36 |
| SC | 2015-03-28 11:20 |
Fukushima | Aizu Univ. | Software Infrastructure for Big Data Analysis on Heterogeneous Environment Masahiro Tanaka (NICT), Kenjiro Taura (UTokyo), Kentaro Torisawa (NICT) SC2014-28 |
Recently big data analysis has been attracting attention in a wide variety of domains. However, it is not trivial to run... [more] | SC2014-28 pp.83-88 |
| PRMU, BioX | 2015-03-20 14:00 |
Kanagawa | Training of Random Forests Using Covariate Shift on Parallel Distributed Processing Ryoji Wakayama (Chubu Univ.), Akisato Kimura (NTT), Takayoshi Yamashita, Yuji Yamauchi, Hironobu Fujiyoshi (Chubu Univ.) BioX2014-73 PRMU2014-193 |
Machine learning with big data improves a classification performance but increases computatinal cost for learning. Paral... [more] | BioX2014-73 PRMU2014-193 pp.205-210 |
|
| MSS | 2015-03-05 15:30 |
Ishikawa | IT Business Plaza Musashi | Code clone detection using parallel distributed processing for software revision history Shin Chadani, Kohei Sakurai, Satoshi Yamane (Kanazawa Univ.) MSS2014-94 |
In software development with a version control system, code clones detected from the version history of the code can be ... [more] | MSS2014-94 pp.19-24 |
| MSS | 2015-03-06 13:30 |
Ishikawa | IT Business Plaza Musashi | Parallel Distributed Clustering Algorithm with Node Partition and Aggregation in Large-Scale Graphs Riku Asayama, Kohei Sakurai, Satoshi Yamane (Kanazawa Univ.) MSS2014-101 |
In this paper, we propose the rapid clustering method with the large-scaled graph structured data. Our approach is a dat... [more] | MSS2014-101 pp.59-64 |
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