Cart (Loading....) | Create Account
Close category search window
 

Can GPGPU Programming Be Liberated from the Data-Parallel Bottleneck?

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)

With the growth in transistor counts in modern hardware, heterogeneous systems are becoming commonplace. Core counts are increasing such that GPU and CPU designs are reaching deep into the tens of cores. For performance reasons, different cores in a heterogeneous platform follow different design choices. Based on throughput computing goals, GPU cores tend to support wide vectors and substantial register files. Current designs optimize CPU cores for latency, dedicating logic to caches and out-of-order dependence control. Heterogeneous parallel primitives (HPP) addresses two major shortcomings in current GPGPU programming models: it supports full composability by defining abstractions and increases flexibility in execution by introducing braided parallelism. Heterogeneous parallel primitives is an object-oriented, C++11-based programming model that addresses these shortcomings on both CPUs and massively multithreaded GPUs: it supports full composability by defining abstractions using distributed arrays and barrier objects, and it increases flexibility in execution by introducing braided parallelism. This paper implemented a feature-complete version of HPP, including all syntactic constructs, that runs on top of a task-parallel runtime executing on the CPU. They continue to develop and improve the model, including reducing overhead due to channel management, and plan to make a public version available sometime in the future.

Published in:

Computer  (Volume:45 ,  Issue: 8 )

Date of Publication:

August 2012

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.