國立高雄大學圖資館 |

Language: English

Back

Directive-based general-purpose GPU ...

Han, Tian Yi David.

Directive-based general-purpose GPU programming.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Directive-based general-purpose GPU programming.
Author:	Han, Tian Yi David.
Description:	112 p.
Notes:	Source: Masters Abstracts International, Volume: 48-04, page: 2384.
Contained By:	Masters Abstracts International48-04.
Subject:	Engineering, Computer.
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=MR59180
ISBN:	9780494591802

Directive-based general-purpose GPU programming.
Han, Tian Yi David.

Directive-based general-purpose GPU programming. - 112 p.

Source: Masters Abstracts International, Volume: 48-04, page: 2384.

Thesis (M.Sc.)--University of Toronto (Canada), 2009.

Graphics Processing Units (GPUs) have become a competitive accelerator for non-graphics applications, mainly driven by the improvements in GPU programmability. Although the Compute Unified Device Architecture (CUDA) is a simple C-like interface for programming NVIDIA GPUs, porting applications to CUDA remains a challenge to average programmers. In particular, CUDA places on the programmer the burden of packaging GPU code in separate functions, of explicitly managing data transfer between the host and GPU memories, and of manually optimizing the utilization of the GPU memory. We have designed hiCUDA, a high-level directive-based language for CUDA programming. It allows programmers to perform these tedious tasks in a simpler manner, and directly to the sequential code. We have also prototyped a compiler that translates a hiCUDA program to a CUDA program and can handle real-world applications. Experiments using seven standard CUDA benchmarks show that the simplicity hiCUDA provides comes at no expense to performance.

ISBN: 9780494591802Subjects--Topical Terms:

384375
Engineering, Computer.

Directive-based general-purpose GPU programming.
LDR:01769nmm 2200241 4500 001 280847
005 20110119095009.5
008 110301s2009 ||||||||||||||||| ||eng d
020 $a 9780494591802
035 $a (UMI)AAIMR59180
035 $a AAIMR59180
040 $a UMI $c UMI
100 1 $a Han, Tian Yi David. $3 492990
245 1 0 $a Directive-based general-purpose GPU programming.
300 $a 112 p.
500 $a Source: Masters Abstracts International, Volume: 48-04, page: 2384.
502 $a Thesis (M.Sc.)--University of Toronto (Canada), 2009.
520 $a Graphics Processing Units (GPUs) have become a competitive accelerator for non-graphics applications, mainly driven by the improvements in GPU programmability. Although the Compute Unified Device Architecture (CUDA) is a simple C-like interface for programming NVIDIA GPUs, porting applications to CUDA remains a challenge to average programmers. In particular, CUDA places on the programmer the burden of packaging GPU code in separate functions, of explicitly managing data transfer between the host and GPU memories, and of manually optimizing the utilization of the GPU memory. We have designed hiCUDA, a high-level directive-based language for CUDA programming. It allows programmers to perform these tedious tasks in a simpler manner, and directly to the sequential code. We have also prototyped a compiler that translates a hiCUDA program to a CUDA program and can handle real-world applications. Experiments using seven standard CUDA benchmarks show that the simplicity hiCUDA provides comes at no expense to performance.
590 $a School code: 0779.
650 4 $a Engineering, Computer. $3 384375
690 $a 0464
710 2 $a University of Toronto (Canada). $3 212652
773 0 $t Masters Abstracts International $g 48-04.
790 $a 0779
791 $a M.Sc.
792 $a 2009
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=MR59180