東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Novel Techniques for Graph Algorithm...

Liu, Hang.

FindBook

Google Book

Amazon

博客來

Novel Techniques for Graph Algorithm Acceleration.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Novel Techniques for Graph Algorithm Acceleration./
作者:	Liu, Hang.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2017,
面頁冊數:	167 p.
附註:	Source: Dissertation Abstracts International, Volume: 79-08(E), Section: B.
Contained By:	Dissertation Abstracts International79-08B(E).
標題:	Computer engineering. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10621649
ISBN:	9780355828474

Novel Techniques for Graph Algorithm Acceleration.
Liu, Hang.

Novel Techniques for Graph Algorithm Acceleration. - Ann Arbor : ProQuest Dissertations & Theses, 2017 - 167 p.

Source: Dissertation Abstracts International, Volume: 79-08(E), Section: B.

Thesis (Ph.D.)--The George Washington University, 2017.

The concept of graph has been around since Euler brought up the Seven Bridges of Knigsberg problem in 1736. Recent years have seen graph computing regains its momentum because of many emerging graph relevant applications, e.g., World-Wide-Web (WWW) networks, social and computer networks, metabolic interactions and chemical compound design graphs. This dissertation strives to provide graph computing systems which are able to quickly compute very large graph datasets with relatively low cost and expose easy programming interface to programmers..

ISBN: 9780355828474Subjects--Topical Terms:

621879
Computer engineering.

Novel Techniques for Graph Algorithm Acceleration.
LDR:03007nmm a2200337 4500 001 2166142
005 20181203094031.5
008 190424s2017 ||||||||||||||||| ||eng d
020 $a 9780355828474
035 $a (MiAaPQ)AAI10621649
035 $a (MiAaPQ)gwu:13796
035 $a AAI10621649
040 $a MiAaPQ $c MiAaPQ
100 1 $a Liu, Hang. $3 2097822
245 1 0 $a Novel Techniques for Graph Algorithm Acceleration.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2017
300 $a 167 p.
500 $a Source: Dissertation Abstracts International, Volume: 79-08(E), Section: B.
500 $a Advisers: H. Howie Huang; Ahmed Louri.
502 $a Thesis (Ph.D.)--The George Washington University, 2017.
520 $a The concept of graph has been around since Euler brought up the Seven Bridges of Knigsberg problem in 1736. Recent years have seen graph computing regains its momentum because of many emerging graph relevant applications, e.g., World-Wide-Web (WWW) networks, social and computer networks, metabolic interactions and chemical compound design graphs. This dissertation strives to provide graph computing systems which are able to quickly compute very large graph datasets with relatively low cost and expose easy programming interface to programmers..
520 $a The first part of this dissertation introduces the Graphics Processing Units (GPUs) accelerated graph traversal which consists of two projects---Enterprise and iBFS. Particularly, Enterprise is the first work that achieves atomic operation free Breadth-First Search (BFS) on GPUs and iBFS is the first to conduct multiple traversals together on GPUs. Both projects achieve orders of magnitude speedup over state-of-the-art.
520 $a The second part introduces SIMD-X, a graph framework that supports a variety of graph algorithms on GPUs. SIMD-X not only provides a simple Active-Compute-Combine (ACC) programming model for end users to express graph algorithms on Single Instruction Multiple Data (SIMD) GPUs, but also creates opportunities for system-level optimizations. Together, SIMD-X allows programmers to develop a typical graph algorithm with less than 100 Lines Of Code (LOCs) and achieve an order of magnitude speedup over Gunrock.
520 $a Finally, this dissertation describes Graphene which can tackle trillion-edge graphs on a single machine with an array of Solid State Drives (SSDs). To enhance the bandwidth utilization of such an array of SSDs, we introduce a bitmap based IO request management component that improves bandwidth efficiency by 4--8x and a row-column 2D graph partition approach to balance the graph data access across the disks. Notably, Graphene achieves comparable performance to in-memory systems, e.g., Galois with merely 10% of memory consumption.
590 $a School code: 0075.
650 4 $a Computer engineering. $3 621879
650 4 $a Engineering. $3 586835
690 $a 0464
690 $a 0537
710 2 $a The George Washington University. $b Computer Engineering. $3 1678827
773 0 $t Dissertation Abstracts International $g 79-08B(E).
790 $a 0075
791 $a Ph.D.
792 $a 2017
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10621649