Cited By
View all- Heldens SHijma PWerkhoven BMaassen JBelloum AVan Nieuwpoort R(2020)The Landscape of Exascale ResearchACM Computing Surveys10.1145/337239053:2(1-43)Online publication date: 20-Mar-2020
Exploiting Hierarchical Exascale Hardware using a PGAS Approach
Pages 48 - 52
Abstract
Hardware architectures that enable Exascale-level performance are expected to break some long-held programmability assumptions on the node level and will come with a plethora of additional challenges that make the productive development of efficient applications difficult. One critical issue is data locality, which will become even more important than it is today. A shift towards data-centric programming models will be required to exploit the full potential of these machines. We present an overview of our work in progress on DASH, a data-structure oriented PGAS library implemented in C++, with which we attempt to address some of the challenges posed by upcoming hardware architectures by focusing on flexible data layout and by supporting a hierarchical locality model.
References
[1]
The UPC consortium: UPC language specification v1.2. June 2005. Technical Report, Lawrence Berkeley National Laboratory.
[2]
J. A. Ang, R. F. Barrett, R. E. Benner, D. Burke, C. Chan, J. Cook, D. Donofrio, S. D. Hammond, K. S. Hemmert, S. M. Kelly, H. Le, V. J. Leung, D. R. Resnick, A. F. Rodrigues, J. Shalf, D. Stark, D. Unat, and N. J. Wright. Abstract machine models and proxy architectures for exascale computing. In Proceedings of the 1st International Workshop on Hardware-Software Co-Design for High Performance Computing, Co-HPC '14, pages 25--32. IEEE Press, 2014. Extended version available online at http://www.cal-design.org/publications/publications2.
[3]
K. Bergman, S. Borkar, D. Campbell, W. Carlson, W. Dally, M. Denneau, P. Franzon, W. Harrod, K. Hill, J. Hiller, et al. Exascale computing study: Technology challenges in achieving exascale systems. Defense Advanced Research Projects Agency Information Processing Techniques Office (DARPA IPTO), Tech. Rep, 15, 2008.
[4]
A. Buss, I. Papadopoulos, O. Pearce, T. Smith, G. Tanase, N. Thomas, X. Xu, M. Bianco, N. M. Amato, L. Rauchwerger, et al. STAPL: standard template adaptive parallel library. In Proceedings of the 3rd Annual Haifa Experimental Systems Conference, page 14. ACM, 2010.
[5]
B. L. Chamberlain, D. Callahan, and H. P. Zima. Parallel programmability and the Chapel language. International Journal of High Performance Computing Applications, 21:291--312, August 2007.
[6]
P. Charles, C. Grothoff, V. Saraswat, C. Donawa, A. Kielstra, K. Ebcioglu, C. Von Praun, and V. Sarkar. X10: an object-oriented approach to non-uniform cluster computing. ACM Sigplan Notices, 40(10):519--538, 2005.
[7]
H. C. Edwards and C. R. Trott. Kokkos: Enabling performance portability across manycore architectures. In Extreme Scaling Workshop (XSW), 2013, pages 18--24. IEEE, 2013.
[8]
K. Fürlinger, C. Glass, A. Knüpfer, J. Tao, D. Hünich, K. Idrees, M. Maiterth, Y. Mhedeb, and H. Zhou. Dash: Data structures and algorithms with support for hierarchical locality. In Euro-Par 2014 Workshops (Porto, Portugal), 2014.
[9]
M. Garland, M. Kudlur, and Y. Zheng. Designing a unified programming model for heterogeneous machines. In Proceedings of the 2012 International Conference for High Performance Computing, Networking, Storage and Analysis (SC'12), Nov. 2012. Salt Lake City, UT, USA.
[10]
GASPI - global adress space programming interface webpage http://www.gaspi.de. Retrieved Jan. 2012.
[11]
T. A. Johnson. Coarray C++. In 7th International Conference on PGAS Programming Models, 2013. Edinburgh, Scotland.
[12]
J. Mellor-Crummey, L. Adhianto, W. N. Scherer, and G. Jin. A new vision for coarray Fortran. In Proceedings of the Third Conference on Partitioned Global Address Space Programing Models (PGAS '09), New York, NY, USA, 2009. ACM.
[13]
J. Nieplocha, R. J. Harrison, and R. J. Littlefield. Global arrays: A nonuniform memory access programming model for high-performance computers. The Journal of Supercomputing, 10:169--189, 1996.
[14]
R. W. Numrich and J. Reid. Co-array fortran for parallel programming. SIGPLAN Fortran Forum, 17(2):1--31, Aug. 1998.
[15]
S. W. Poole, O. Hernandez, J. A. Kuehn, G. M. Shipman, A. Curtis, and K. Feind. Openshmem - toward a unified rma model. In D. Padua, editor, Encyclopedia of Parallel Computing, pages 1379--1391. Springer US, 2011.
[16]
A. Tate, A. Kamil, A. Dubey, A. Größlinger, B. Chamberlain, B. Goglin, C. Edwards, C. J. Newburn, D. Padua, D. Unat, E. Jeannot, F. Hannig, T. Gysi, H. Ltaief, J. Sexton, J. Labarta, J. Shalf, K. Fürlinger, K. O'Brien, L. Linardakis, M. Besta, M.-C. Sawley, M. Abraham, M. Bianco, M. Pericàs, N. Maruyama, P. H. J. Kelly, P. Messmer, R. B. Ross, R. Cledat, S. Matsuoka, T. Schulthess, T. Hoefler, and V. J. Leung. Programming Abstractions for Data Locality. Research report, PADAL Workshop 2014, April 28--29, Swiss National Supercomputing Center (CSCS), Lugano, Switzerland, Nov. 2014.
[17]
Y. Yan, J. Zhao, Y. Guo, and V. Sarkar. Hierarchical Place Trees: A portable abstraction for task parallelism and data movement. In Proceedings of the 22nd international conference on Languages and Compilers for Parallel Computing, LCPC'09, pages 172--187. Springer-Verlag, 2010.
[18]
Y. Zheng, A. Kamil, M. B. Driscoll, H. Shan, and K. Yelick. UPC++: A PGAS extension for C++. In 28th IEEE International Parallel & Distributed Processing Symposium, 2014.
Index Terms
- Exploiting Hierarchical Exascale Hardware using a PGAS Approach
Recommendations
Porting scientific libraries to PGAS in XSEDE resources: practice and experience
XSEDE '15: Proceedings of the 2015 XSEDE Conference: Scientific Advancements Enabled by Enhanced CyberinfrastructureThe next generation of supercomputers presents new and complex challenges that might require a change in the current paradigm of how parallel applications are developed. Hybrid programming is usually described as the best approach for exascale ...
The UPC++ PGAS library for Exascale Computing
PAW17: Proceedings of the Second Annual PGAS Applications WorkshopWe describe UPC++ V1.0, a C++11 library that supports APGAS programming. UPC++ targets distributed data structures where communication is irregular or fine-grained. The key abstractions are global pointers, asynchronous programming via RPC, and futures. ...
OpenSHMEM as a Portable Communication Layer for PGAS Models: A Case Study with Coarray Fortran
CLUSTER '15: Proceedings of the 2015 IEEE International Conference on Cluster ComputingLanguages and libraries based on the Partitioned Global Address Space (PGAS) programming model have emerged in recent years with a focus on addressing the programming challenges for scalable parallel systems. Among these, Coarray Fortran (CAF) is unique ...
Comments
Information & Contributors
Information
Published In
Publisher
University of Edinburgh
United Kingdom
Publication History
Published: 21 April 2015
Author Tags
Qualifiers
- Tutorial
- Research
- Refereed limited
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- View Citations1Total Citations
- 71Total Downloads
- Downloads (Last 12 months)14
- Downloads (Last 6 weeks)3
Reflects downloads up to 30 Aug 2024
Other Metrics
Citations
Cited By
View all- Heldens SHijma PWerkhoven BMaassen JBelloum AVan Nieuwpoort R(2020)The Landscape of Exascale ResearchACM Computing Surveys10.1145/337239053:2(1-43)Online publication date: 20-Mar-2020
View Options
Get Access
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in