ログイン 新規登録
言語:

WEKO3

  • トップ
  • ランキング
To
lat lon distance
To

Field does not validate



インデックスリンク

インデックスツリー

メールアドレスを入力してください。

WEKO

One fine body…

WEKO

One fine body…

アイテム

  1. 研究報告
  2. ハイパフォーマンスコンピューティング(HPC)
  3. 2025
  4. 2025-HPC-200

Graphical Ray Casting Representation of Directed Acyclic Graph in Critical Path Detection

https://ipsj.ixsq.nii.ac.jp/records/2003152
https://ipsj.ixsq.nii.ac.jp/records/2003152
9e96b517-b9f0-4a74-bb7a-74f6cac7e7ad
名前 / ファイル ライセンス アクション
IPSJ-HPC25200015.pdf IPSJ-HPC25200015.pdf (921.0 KB)
 2027年7月28日からダウンロード可能です。
Copyright (c) 2025 by the Information Processing Society of Japan
非会員:¥660, IPSJ:学会員:¥330, HPC:会員:¥0, DLIB:会員:¥0
Item type SIG Technical Reports(1)
公開日 2025-07-28
タイトル
言語 ja
タイトル Graphical Ray Casting Representation of Directed Acyclic Graph in Critical Path Detection
タイトル
言語 en
タイトル Graphical Ray Casting Representation of Directed Acyclic Graph in Critical Path Detection
言語
言語 eng
キーワード
主題Scheme Other
主題 Graph / Training
資源タイプ
資源タイプ識別子 http://purl.org/coar/resource_type/c_18gh
資源タイプ technical report
著者所属
RIKEN
著者所属
RIKEN
著者所属
RIKEN
著者所属
RIKEN/Institute of Science Tokyo
著者所属
RIKEN
著者所属
Kyoto University
著者所属
RIKEN/Institute of Science Tokyo
著者所属
RIKEN
著者所属
RIKEN
著者所属(英)
en
RIKEN
著者所属(英)
en
RIKEN
著者所属(英)
en
RIKEN
著者所属(英)
en
RIKEN / Institute of Science Tokyo
著者所属(英)
en
RIKEN
著者所属(英)
en
Kyoto University
著者所属(英)
en
RIKEN / Institute of Science Tokyo
著者所属(英)
en
RIKEN
著者所属(英)
en
RIKEN
著者名 Zhengyang,Bai

× Zhengyang,Bai

Zhengyang,Bai

Search repository
Peng,Chen

× Peng,Chen

Peng,Chen

Search repository
Lingqi,Zhang

× Lingqi,Zhang

Lingqi,Zhang

Search repository
Chen,Zhuang

× Chen,Zhuang

Chen,Zhuang

Search repository
Tenindra,Abeywickrama

× Tenindra,Abeywickrama

Tenindra,Abeywickrama

Search repository
Jing,Xu

× Jing,Xu

Jing,Xu

Search repository
Du,Wu

× Du,Wu

Du,Wu

Search repository
Emil,Vatai

× Emil,Vatai

Emil,Vatai

Search repository
Mohamed,Wahib

× Mohamed,Wahib

Mohamed,Wahib

Search repository
著者名(英) Zhengyang Bai

× Zhengyang Bai

en Zhengyang Bai

Search repository
Peng Chen

× Peng Chen

en Peng Chen

Search repository
Lingqi Zhang

× Lingqi Zhang

en Lingqi Zhang

Search repository
Chen Zhuang

× Chen Zhuang

en Chen Zhuang

Search repository
Tenindra Abeywickrama

× Tenindra Abeywickrama

en Tenindra Abeywickrama

Search repository
Jing Xu

× Jing Xu

en Jing Xu

Search repository
Du Wu

× Du Wu

en Du Wu

Search repository
Emil Vatai

× Emil Vatai

en Emil Vatai

Search repository
Mohamed Wahib

× Mohamed Wahib

en Mohamed Wahib

Search repository
論文抄録
内容記述タイプ Other
内容記述 Directed acyclic graphs (DAGs), where all edges are directed and the graph is cycle-free, play an essential role in various domains, such as phylogenetic networks in biology, causal inference in social science, and cutting-edge technologies like task scheduling in large-scale computer systems. However, most traditional DAG algorithms are complex and difficult to accelerate because of their irregular data access patterns and control-flow divergency that do not align well with GPUs' SIMT (Single Instruction, Multiple Threads) architecture. However, recent advances in GPU architecture offer new opportunities to overcome these issues by ray tracing cores, which were originally designed for rendering tasks but have enhanced GPU's ability to perform divergences that can be efficiently applied to DAG-related problems. In this work, we present a novel approach to modeling DAG problems as rendering tasks. We employ GPU ray tracing cores to efficiently explore the complex relationships within DAGs. In addition, we propose a general workflow for processing this graphical ray casting representation and demonstrate its practical implementation via a case study on critical path detection.
論文抄録(英)
内容記述タイプ Other
内容記述 Directed acyclic graphs (DAGs), where all edges are directed and the graph is cycle-free, play an essential role in various domains, such as phylogenetic networks in biology, causal inference in social science, and cutting-edge technologies like task scheduling in large-scale computer systems. However, most traditional DAG algorithms are complex and difficult to accelerate because of their irregular data access patterns and control-flow divergency that do not align well with GPUs' SIMT (Single Instruction, Multiple Threads) architecture. However, recent advances in GPU architecture offer new opportunities to overcome these issues by ray tracing cores, which were originally designed for rendering tasks but have enhanced GPU's ability to perform divergences that can be efficiently applied to DAG-related problems. In this work, we present a novel approach to modeling DAG problems as rendering tasks. We employ GPU ray tracing cores to efficiently explore the complex relationships within DAGs. In addition, we propose a general workflow for processing this graphical ray casting representation and demonstrate its practical implementation via a case study on critical path detection.
書誌レコードID
収録物識別子タイプ NCID
収録物識別子 AN10463942
書誌情報 研究報告ハイパフォーマンスコンピューティング(HPC)

巻 2025-HPC-200, 号 15, p. 1-7, 発行日 2025-07-28
ISSN
収録物識別子タイプ ISSN
収録物識別子 2188-8841
Notice
SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc.
出版者
言語 ja
出版者 情報処理学会
戻る
0
views
See details
Views

Versions

Ver.1 2025-07-10 01:43:03.810692
Show All versions

Share

Mendeley Twitter Facebook Print Addthis

Cite as

エクスポート

OAI-PMH
  • OAI-PMH JPCOAR
  • OAI-PMH DublinCore
  • OAI-PMH DDI
Other Formats
  • JSON
  • BIBTEX

Confirm


Powered by WEKO3


Powered by WEKO3