PGAS (Partitioned Global Address Space) Languages

Leasure, Bruce; Kuck, David J.; Gorlatch, Sergei; Cole, Murray; Watson, Gregory R.; Darte, Alain; Banerjee, Utpal; Schenk, Olaf; Gärtner, Klaus; Siegel, Howard Jay; Young, Bobby Dalton; Campbell, Roy H.; Çatalyürek, Ümit V.; Aykanat, Cevdet; Ajanovic, Jasmin; Schmid, Stefan; Wattenhofer, Roger; Elnozahy, E. N. Mootaz; Speight, Evan W.; Li, Jian; Rajamony, Ram; Zhang, Lixin; Arimilli, Baba; Gerndt, Michael; Dennis, Jack B.; Smith, Barry; Almási, George; Stamatakis, Alexandros; Sangiorgi, Davide; Gunnels, John A.; Dongarra, Jack; Łuszczek, Piotr; Mohr, Bernd; Eigenmann, Rudolf; Feautrier, Paul; Lengauer, Christian; Bose, Pradip; JáJá, Joseph F.; Gupta, Anshul; Nicola, Rocco De; Padua, David; Armen, Roger S.; May, Eric R.; Taufer, Michela; Geist, Al

doi:10.1007/978-0-387-09766-4_210

Cited by 5 publications

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Both languages (Chapel and X10) are from the so-called PGAS languages family. PGAS is an acronym for Partitioned Global Array Space [21]. Now there can be observed effort to include into this model also heterogeneous systems -clusters with nodes consisting of combination of CPUs and accelerators, as on the newest (and the most powerful) supercomputers.…”

Section: Chapel and X10mentioning

confidence: 99%

The Survey of Object-Oriented Software Programming Language from a Heterogeneous Cluster Programming Viewpoint

Brandejsky

Hrbek

2022

Software Engineering Perspectives in Systems

View full text Add to dashboard Cite

In this paper, the problem of programming language selection is presented from the position of large cluster with heterogeneous accelerators programming in the situations when it is need to apply objectoriented programming like in the case of heterogeneous multi-agent simulations or large data modelling using memetic algorithms. This work was inspired by experience with the Chapel language obtained during complicated conversion of hybrid evolutionary algorithm GPAes from a single node OpenMP C++ implementation onto HPC cluster with nodes equipped by both CPU and GPGPU. The paper consists of discussion of many approaches to parallel programming including not only traditional ways such as OpenMP, MPI and Cuda and their combinations, but also modern extensions of C/C++ as OpenACC, Silk and CYCL. Emerging languages as Chapel and Julia are discussed too. The work concludes with an evaluation of the real state of parallel object-oriented programming on heterogeneous node HPC clusters.

show abstract

Section: Chapel and X10mentioning

confidence: 99%

The Survey of Object-Oriented Software Programming Language from a Heterogeneous Cluster Programming Viewpoint

Brandejsky

Hrbek

2022

Software Engineering Perspectives in Systems

View full text Add to dashboard Cite

show abstract

“…3) Partitioned Global Address Space: The PGAS model is a hybrid of the shared and distributed models. The memory of different nodes are physically separate as in the distributed model but logically contiguous in that any node can access the shared space [11]. Bridging the disparate memories together requires support from hardware or software.…”

Section: A Memory Modelsmentioning

confidence: 99%

Exploring PGAS Communication for Heterogeneous Clusters with FPGAs

Sharma

Chow

2021

The 2021 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays

View full text Add to dashboard Cite

This work presents a heterogeneous communication library for clusters of processors and FPGAs. This library, Shoal, supports the Partitioned Global Address Space (PGAS) memory model for applications. PGAS is a shared memory model for clusters that creates a distinction between local and remote memory access. Through Shoal and its common application programming interface for hardware and software, applications can be more freely migrated to the optimal platform and deployed onto dynamic cluster topologies.The library is tested using a thorough suite of microbenchmarks to establish latency and throughput performance. We also show an implementation of the Jacobi iterative method that demonstrates the ease with which applications can be moved between platforms to yield faster run times. Through this work, we have demonstrated the feasibility of using a PGAS programming model for multi-node heterogeneous platforms.

show abstract

Productivity-Aware Design and Implementation of Distributed Tree-Based Search Algorithms

Carneiro

Melab

2019

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Parallel tree search algorithms offer viable solutions to problems in different areas, such as operations research, machine learning and artificial intelligence. This class of algorithms is highly computeintensive, irregular and usually relies on context-specific data structures and hand-made code optimizations. Therefore, C and C++ are the languages often employed, due to their low-level features and performance. In this work, we investigate the use of Chapel high-productivity language for the design and implementation of distributed tree search algorithms for solving combinatorial problems. The experimental results show that Chapel is a suitable language for this purpose, both in terms of performance and productivity. Despite the use of high-level features, the distributed tree search in Chapel is on average 16% slower and reaches up to 85% of the scalability observed for its MPI+OpenMP counterpart.

show abstract

PGAS (Partitioned Global Address Space) Languages

Cited by 5 publications

References 0 publications

The Survey of Object-Oriented Software Programming Language from a Heterogeneous Cluster Programming Viewpoint

The Survey of Object-Oriented Software Programming Language from a Heterogeneous Cluster Programming Viewpoint

Exploring PGAS Communication for Heterogeneous Clusters with FPGAs

Productivity-Aware Design and Implementation of Distributed Tree-Based Search Algorithms

Contact Info

Product

Resources

About