Cited By
View all- Ma YWu HWang LHuang BRanjan RZomaya AJie W(2015)Remote sensing big data computingFuture Generation Computer Systems10.1016/j.future.2014.10.02951:C(47-60)Online publication date: 1-Oct-2015
Improving UPC productivity via integrated development tools
PGAS '10: Proceedings of the Fourth Conference on Partitioned Global Address Space Programming Model
Article No.: 8, Pages 1 - 9
Abstract
In the world of high-performance computing (HPC), there has been an increased focus in recent years upon the importance of productivity in HPC application development. One crucial aspect of productivity is the programming model used, and the family of partitioned global-address-space (PGAS) models, such as UPC and X10, has served to advance the state of the art in balancing performance and productivity. Also of great importance is the variety of development tools used to support activities such as editing, debugging, and optimizing programs. These tools are often most useful as part of an integrated development environment (IDE). While some progress has been made towards bringing IDE capabilities into the HPC world, in particular by way of Eclipse projects, support has mainly focused on MPI and OpenMP tools.
In this paper, we present research and development activities that are bringing Eclipse-based IDE capabilities to the PGAS developer community. We focus on tools for UPC, giving background on previously existing capabilities to work with UPC programs in Eclipse and then presenting a tool-chain and project wizard for the open-source Berkeley UPC compiler, basic UPC static analysis tools, and integration of our performance analysis tool (Parallel Performance Wizard) supporting UPC. Finally, we conclude by proposing future work and providing recommendations for further integration of UPC and other PGAS tools to enhance overall developer productivity.
References
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The X10 Programming Language, http://x10-lang.org.
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H. Su, M. Billingsley, and A. D. George, Parallel Performance Wizard: A Performance System for the Analysis of Partitioned Global-Address-Space Applications, International Journal of High-Performance Computing Applications, accepted and in press.
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Index Terms
- Improving UPC productivity via integrated development tools
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Published In
October 2010
134 pages
ISBN:9781450304610
DOI:10.1145/2020373
- General Chair:
- José E. Moreira,
- Program Chairs:
- Costin Iancu,
- Vijay Saraswat
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Published: 12 October 2010
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PGAS '10
PGAS '10: Fourth Conference on Partitioned Global Address Space Programming Model
October 12 - 15, 2010
New York, New York, USA
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View all- Ma YWu HWang LHuang BRanjan RZomaya AJie W(2015)Remote sensing big data computingFuture Generation Computer Systems10.1016/j.future.2014.10.02951:C(47-60)Online publication date: 1-Oct-2015
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