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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 49  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
IE, CS, IPSJ-AVM [detail] 2023-12-11
15:30
Fukuoka Kyushu Institute of Technology
(Primary: On-site, Secondary: Online)
[Special Invited Talk] High-Performance Image Processing Utilizing Hardware
Norishige Fukushima (nitech) CS2023-83 IE2023-25
High-speed image signal processing is important to realize applications in various environments.
To complete image proc... [more]
CS2023-83 IE2023-25
p.16
COMP, IPSJ-AL 2023-05-11
14:20
Hokkaido Hokkaido University Enumeration of Minimal Induced Steiner Subgraph in a Series-Parallel Graph
Shun Onogi (TUT), Kunihiro Wasa (Hosei Univ.) COMP2023-5
Given a graph $G = (V, E)$ with a terminal set $W subseteq V$,
a vertex subset $S subseteq V$ is an emph{induced Stein... [more]
COMP2023-5
pp.22-28
SDM, ICD, ITE-IST [detail] 2021-08-18
13:45
Online Online Performance Evaluation of Serial-Parallel Montgomery Multipliers for RNS
Hiroyuki Tsubouchi, Mitsunaga Kinjo, Katsuhiko Shimabukuro (Univ. of the Ryukyus) SDM2021-40 ICD2021-11
Modulo operations are required in RNS (Residue Number System) which enables to perform highly parallel computation. Also... [more] SDM2021-40 ICD2021-11
pp.54-57
COMP 2018-09-18
15:20
Fukuoka Kyusyu Institute of Technology Enumeration and Random Sampling of Nonisomorphic Two-Terminal Series-Parallel Graphs
Shuhei Denzumi (UTokyo), Takashi Horiyama (Saitama Univ.), Kazuhiro Kurita (Hokudai), Yu Nakahata (NAIST), Hirofumi Suzuki (Hokudai), Kunihiro Wasa (NII), Kazuaki Yamazaki (JAIST) COMP2018-17
A graph $G$ is a two-terminal series-parallel graph if (1) $G$ consists of two vertices and an edge between them or (2) ... [more] COMP2018-17
pp.55-62
CPSY 2017-11-19
15:00
Aomori Aomori Tourist Information Center, ASPAM [Poster Presentation] GPU Applications with Single Kernel Synchronization Technique
Shunji Funasaka, Koji Nakano, Yasuaki Ito (Hiroshima Univ.) CPSY2017-56
A task array is a 2-dimensional array of tasks with dependency relations.
Conventional CUDA implementations repeatedly ... [more]
CPSY2017-56
pp.33-38
MI 2017-01-18
14:15
Okinawa Tenbusu Naha GPU Programming for MIST Library
Hirohisa Oda, Masahiro Oda (Nagoya Univ.), Takayuki Kitasaka (Aichi. Inst. Tech.), Kensaku Mori (Nagoya Univ.) MI2016-106
In recent years, there is a trend toward the development of high-speed computation techniques due to the improvement in ... [more] MI2016-106
pp.133-136
CPSY, IPSJ-ARC 2016-10-06
10:00
Chiba Makuhari-messe [Poster Presentation] A Loss-Less Data Compression Algorithm for GPUs
Shunji Funasaka, Koji Nakano, Yasuaki Ito (Hiroshima Univ.) CPSY2016-46
There is no doubt that data compression is very important in computer engineering. However, most lossless data compressi... [more] CPSY2016-46
pp.19-24
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
SIS 2015-12-03
17:00
Fukui Matsuya-sensen (Awara city, Fukui) Processing Time Reduction of Iterative Shrinkage Smoothing Using Parallel Processing
Seijiro Imai, Dabwitso Kasauka, Takashi Imagawa, Hiroshi Tsutsui (Hokkaido Univ.), Hiroyuki Okuhata (Synthesis Co.), Yoshikazu Miyanaga (Hokkaido Univ.) SIS2015-39
Iterative shrinkage smoothing algorithm can perform image smoothing with
eliminating fine details and preserving princi... [more]
SIS2015-39
pp.57-60
NLP 2014-07-01
11:25
Miyagi Tohoku Univ. Implementation of Parallel Processing of Chaos Hybrid Optimization for Quadratic Assignment Problem
Keisuke Kanamaru, Hiroyuki Yasuda, Mikio Hasegawa (TUS) NLP2014-30
Effectiveness of chaotic dynamics for combinatorial optimization has been shown by many previous researches. In this pap... [more] NLP2014-30
pp.53-58
NLP 2014-03-11
11:15
Tokyo Sophia University Basic performances of PSO networks
Tomoyuki Sasaki, Hidehiro Nakano, Arata Miyauchi (Tokyo City Univ.) NLP2013-180
Recently, systems have been large scale and complicated with the development of technology. Optimization algorithms such... [more] NLP2013-180
pp.91-96
IPSJ-SLDM, CPSY, RECONF, VLD [detail] 2014-01-29
08:30
Kanagawa Hiyoshi Campus, Keio University An Experimental Bit-Parallel Solution to Accelerate Smith-Waterman Algorithm
Saori Sudo, Masato Yoshimi, Hidetsugu Irie, Tsutomu Yoshinaga (UEC) VLD2013-119 CPSY2013-90 RECONF2013-73
The Smith-Waterman (SW) algorithm is a computational method to obtain well accorded subsequences between two strings, an... [more] VLD2013-119 CPSY2013-90 RECONF2013-73
pp.103-108
RCS, AP
(Joint)
2013-11-20
17:15
Shimane Matsue Terrsa A Study on BP-based Signal Detection for a Massive MIMO system in Spatially Correlated Channels
Wataru Fukuda, Takashi Abiko, Toshihiko Nishimura, Takeo Ohgane, Yasutaka Ogawa (Hokkaido Univ.), Yusuke Ohwatari, Teruo Kawamura, Yoshihisa Kishiyama (NTT DOCOMO) RCS2013-183
The easiest way to improve the throughput performance of multiple-input multiple-output (MIMO) systems is increasing the... [more] RCS2013-183
pp.55-60
SIP, RCS 2013-02-01
13:00
Hiroshima Viewport-Kure-Hotel (Kure) Complexity Reduction Approaches for Signal Detection Based on Belief Propagation in a Large Scale MIMO System
Wataru Fukuda, Takashi Abiko, Toshihiko Nishimura, Takeo Ohgane, Yasutaka Ogawa (Hokkaido Univ.), Yusuke Ohwatari, Yoshihisa Kishiyama (NTT DOCOMO) SIP2012-119 RCS2012-276
The easiest way to improve the throughput performance of multiple-input multiple-output (MIMO) systems is to increase th... [more] SIP2012-119 RCS2012-276
pp.225-230
NC, NLP 2013-01-24
12:50
Hokkaido Hokkaido University Centennial Memory Hall Study of qusai-Newton training algorithm on parallel distributed environment
Makoto Saiki, Yoshihiko Sakashita, Hiroshi Ninomiya (Shonan Inst. of Tech.) NLP2012-111 NC2012-101
This paper describes the feasibility of quasi-Newton method for training feedforward neural networks on the parallel dis... [more] NLP2012-111 NC2012-101
pp.43-48
ICD 2012-12-17
15:55
Tokyo Tokyo Tech Front [Poster Presentation] A Hardware-Friendly Object Recognition Algorithm Using Log Polar Coordinate Transformation
Makoto Wada, Tadashi Shibata (UT) ICD2012-96
SIFT and SIFT-based algorithms are widely used in a variety of image recognition problems. However
they present the fol... [more]
ICD2012-96
p.35
COMP 2012-10-31
16:45
Miyagi Tohoku University A Novel Computation Model for GPU
Atsushi Koike, Kunihiko Sadakane (NII) COMP2012-42
We propose a novel computation model for GPU. Known parallel computation models such as the PRAM model are not appropria... [more] COMP2012-42
pp.53-60
SR, AN, USN, RCS
(Joint)
2012-10-17
09:25
Fukuoka Fukuoka univ. A Study on Signal Detection in a Large Scale MIMO System -- Concept and BER Performance --
Wataru Fukuda, Takashi Abiko, Toshihiko Nishimura, Takeo Ohgane, Yasutaka Ogawa (Hokkaido Univ.), Yusuke Ohwatari, Yoshihisa Kishiyama (NTT DOCOMO) RCS2012-126
The easiest way to improve the throughput performance of multiple-input multiple-output (MIMO) systems is increasing the... [more] RCS2012-126
pp.7-12
COMP 2012-09-03
10:05
Tokyo Hosei University Bit-Parallel Algorithms for Finding All Substrings Matching a Regular Expression
Hiroaki Yamamoto (Shinshu Univ.), Takashi Miyazaki (Nagano National College of Tech.) COMP2012-27
This paper is concerned with the following regular expression searching
problem which, given a regular expression $r$ ... [more]
COMP2012-27
pp.9-16
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