NDLI: accULL: An User-directed Approach to Heterogeneous Programming

Content Provider	IEEE Xplore Digital Library
Author	Reyes, R. Lopez, I. Fumero, J.J. de Sande, F.
Copyright Year	2012
Abstract	The world of HPC is undergoing rapid changes and computer architectures capable to achieve high performance have broadened. The irruption in the scene of computational accelerators, like GPUs, is increasing performance while maintaining low cost per GFLOP, thus expanding the popularity of HPC. However, it is still difficult to exploit the new complex processor hierarchies. To adapt the message passing model to program heterogeneous CPU+GPUs environments is not an easy task. Furthermore, message passing does not seem to be the best choice from the programmer point of view. Traditional shared memory approaches like OpenMP are interesting to ease the popularization of these platforms, but the fact is that GPU devices are connected to the CPU through a bus and have a separate memory space. We need to find a way to deal with this issue at programming language level, otherwise, developers will spend most of their time focusing on low-level code details instead of algorithmic enhancements. The recent advent of the OpenACC standard for heterogeneous computing represents an effort in the direction of leveraging the development effort. This initiative, combined with future releases of the OpenMP standard, will converge into a fully heterogeneous framework that will cope the programming requirements of future computer architectures. In this work we present preliminary results of accULL, a novel implementation of the OpenACC standard, based on a source-to-source compiler and a runtime library. To our knowledge, our approach is the first providing support for both OpenCL and CUDA platforms under this new standard.
Starting Page	654
Ending Page	661
File Size	350187
Page Count	8
File Format	PDF
ISBN	9781467316316
DOI	10.1109/ISPA.2012.97
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-07-10
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	OpenMP Programming code performance Standards GPGPU Graphics processing unit CUDA Runtime Accelerators productivity Computer architecture OpenACC OpenCL compiler Kernel
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Directive-based Programming for GPUs: A Comparative Study

Performance Evaluation of OpenACC Compilers

Programming for GPUs: The Directive-Based Approach

A preliminary evaluation of OpenACC implementations

Benchmarking OpenCL, OpenACC, OpenMP, and CUDA: Programming Productivity, Performance, and Energy Consumption

Accelerating Hydrocodes with OpenACC, OpenCL and CUDA

An OpenMP Compiler for Hybrid CPU/GPU Computing Architecture

Optimize or Wait? Using llc Fast-Prototyping Tool to Evaluate CUDA Optimizations

Source-to-Source Code Translator: OpenMP C to CUDA

accULL: An User-directed Approach to Heterogeneous Programming

Similar Documents

Directive-based Programming for GPUs: A Comparative Study

Performance Evaluation of OpenACC Compilers

Programming for GPUs: The Directive-Based Approach

A preliminary evaluation of OpenACC implementations

Benchmarking OpenCL, OpenACC, OpenMP, and CUDA: Programming Productivity, Performance, and Energy Consumption

Accelerating Hydrocodes with OpenACC, OpenCL and CUDA

An OpenMP Compiler for Hybrid CPU/GPU Computing Architecture

Optimize or Wait? Using llc Fast-Prototyping Tool to Evaluate CUDA Optimizations

Source-to-Source Code Translator: OpenMP C to CUDA

accULL: An User-directed Approach to Heterogeneous Programming