Co-array Fortran for parallel programming
ACM SIGPLAN Fortran Forum
Image Indexing Using Color Correlograms
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Spatial Color Indexing and Applications
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Feature Extraction: Foundations and Applications (Studies in Fuzziness and Soft Computing)
Feature Extraction: Foundations and Applications (Studies in Fuzziness and Soft Computing)
Cell broadband engine architecture and its first implementation: a performance view
IBM Journal of Research and Development
Scaling communication-intensive applications on BlueGene/P using one-sided communication and overlap
IPDPS '09 Proceedings of the 2009 IEEE International Symposium on Parallel&Distributed Processing
SHMEM+: A multilevel-PGAS programming model for reconfigurable supercomputing
ACM Transactions on Reconfigurable Technology and Systems (TRETS)
Performance modeling for multilevel communication in SHMEM+
Proceedings of the Fourth Conference on Partitioned Global Address Space Programming Model
SCF: A Framework for Task-Level Coordination in Reconfigurable, Heterogeneous Systems
ACM Transactions on Reconfigurable Technology and Systems (TRETS)
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Reconfigurable computing (RC) systems based on FPGAs are becoming an increasingly attractive solution to building parallel systems of the future. Applications targeting such systems have demonstrated superior performance and reduced energy consumption versus their traditional counterparts based on microprocessors. However, most of such work has been limited to small system sizes. Unlike traditional HPC systems, lack of integrated, system-wide, parallel-programming models and languages presents a significant design challenge for creating applications targeting scalable, reconfigurable HPC systems. In this paper, we introduce and investigate a novel programming model based on Partitioned Global Address Space (PGAS), which simplifies development of parallel applications for such systems. The new multilevel PGAS programming model captures the unique characteristics of these systems, such as the existence of multiple levels of memory hierarchy and heterogeneous computation resources. To evaluate this multilevel PGAS model, we extend and adapt the SHMEM programming language to become what we call SHMEM+, the first known SHMEM library enabling coordination between FPGAs and CPUs in a reconfigurable, heterogeneous HPC system. Our design of SHMEM+ is highly portable and provides peak communication bandwidth comparable to vendor-proprietary versions of SHMEM. In addition, applications designed with SHMEM+ yield improved developer productivity compared to current methods of multi-device RC design and achieve a high degree of portability.