UPC++: A PGAS Extension for C++

Zheng, Yili; Kamil, Amir; Driscoll, Michael; Shan, Hongzhang; Yelick, Katherine

doi:10.1109/ipdps.2014.115

Cited by 151 publications

(112 citation statements)

References 17 publications

(16 reference statements)

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“…There are a number of different HPC languages [23,14,3,1]. The goal of these languages is to provide appropriate programming idioms specifically for HPC computing to simplify the expression of HPC applications with regard to parallelism and data placement across a cluster of machines or a supercomputer.…”

Section: Hpc Languagesmentioning

confidence: 99%

“…Although there is a strong desire to automatically classify data partitions, most languages leave this task to the developer and provide tools to simplify this process [23]. The extensions by Yan et al [22] build on existing work to support specifying how data should be partitioned between different hardware devices during a computation:…”

Section: Data Partitioningmentioning

confidence: 99%

See 1 more Smart Citation

A Scalable Runtime for the ECOSCALE Heterogeneous Exascale Hardware Platform

Harvey

Bakanov

Spence

et al. 2016

Proceedings of the 6th International Workshop on Runtime and Operating Systems for Supercomputers

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Exascale computation is the next target of high performance computing. In the push to create exascale computing platforms, simply increasing the number of hardware devices is not an acceptable option given the limitations of power consumption, heat dissipation, and programming models which are designed for current hardware platforms. Instead, new hardware technologies, coupled with improved programming abstractions and more autonomous runtime systems, are required to achieve this goal.This position paper presents the design of a new runtime for a new heterogeneous hardware platform being developed to explore energy efficient, high performance computing. By combining a number of different technologies, this framework will both simplify the programming of current and future HPC applications, as well as automating the scheduling of data and computation across this new hardware platform. In particular, this work explores the use of FPGAs to achieve both the power and performance goals of exascale, as well as utilising the runtime to automatically effect dynamic configuration and reconfiguration of these platforms.

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Section: Hpc Languagesmentioning

confidence: 99%

Section: Data Partitioningmentioning

confidence: 99%

A Scalable Runtime for the ECOSCALE Heterogeneous Exascale Hardware Platform

Harvey

Bakanov

Spence

et al. 2016

Proceedings of the 6th International Workshop on Runtime and Operating Systems for Supercomputers

View full text Add to dashboard Cite

show abstract

“…In this section, we give a brief overview of UPC++, focusing on the features used in our miniGMG implementations, including shared objects, dynamic global memory management, communication, and multidimensional arrays. A more complete discussion of UPC++ can be found in [34].…”

Section: Upc++ Overviewmentioning

confidence: 99%

“…Although the tradeoffs could be evaluated in any of the myriad PGAS languages and libraries, we use UPC++ [34] as our vehicle for evaluating different communication paradigms in the context of miniGMG. UPC++ is a librarybased PGAS extension of C++; unlike UPC [5], it does not need special compiler support.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of PGAS Communication Paradigms with Geometric Multigrid

Shan

Kamil

Williams

et al. 2014

Proceedings of the 8th International Conference on Partitioned Global Address Space Programming Models

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Partitioned Global Address Space (PGAS) languages and one-sided communication enable application developers to select the communication paradigm that balances the performance needs of applications with the productivity desires of programmers. In this paper, we evaluate three different one-sided communication paradigms in the context of geometric multigrid using the miniGMG benchmark. Although miniGMG's static, regular, and predictable communication does not exploit the ultimate potential of PGAS models, multigrid solvers appear in many contemporary applications and represent one of the most important communication patterns. We use UPC++, a PGAS extension of C++, as the vehicle for our evaluation, though our work is applicable to any of the existing PGAS languages and models. We compare performance with the highly tuned MPI baseline, and the results indicate that the most promising approach towards achieving performance and ease of programming is to use high-level abstractions, such as the multidimensional arrays provided by UPC++, that hide data aggregation and messaging in the runtime library.

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“…We implement the array library in the context of UPC++ [17], a library for partitioned global address space (PGAS) programs, which allow data to be directly accessed by processors that do not share the physical address space in which the data are located. We also include the ability for the array library to be used separately from UPC++ in standard C++ programs.…”

Section: Introductionmentioning

confidence: 99%

A Local-View Array Library for Partitioned Global Address Space C++ Programs

Kamil

Yelick

2014

Proceedings of ACM SIGPLAN International Workshop on Libraries, Languages, and Compilers for Array Programming

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Multidimensional arrays are an important data structure in many scientific applications. Unfortunately, built-in support for such arrays is inadequate in C++, particularly in the distributed setting where bulk communication operations are required for good performance. In this paper, we present a multidimensional library for partitioned global address space (PGAS) programs, supporting the one-sided remote access and bulk operations of the PGAS model. The library is based on Titanium arrays, which have proven to provide good productivity and performance. These arrays provide a local view of data, where each rank constructs its own portion of a global data structure, matching the local view of execution common to PGAS programs and providing maximum flexibility in structuring global data. Unlike Titanium, which has its own compiler with array-specific analyses, optimizations, and code generation, we implement multidimensional arrays solely through a C++ library. The main goal of this effort is to provide a library-based implementation that can match the productivity and performance of a compiler-based approach. We implement the array library as an extension to UPC++, a C++ library for PGAS programs, and we extend Titanium arrays with specializations to improve performance. We evaluate the array library by porting four Titanium benchmarks to UPC++, demonstrating that it can achieve up to 25% better performance than Titanium without a significant increase in programmer effort.

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UPC++: A PGAS Extension for C++

Cited by 151 publications

References 17 publications

A Scalable Runtime for the ECOSCALE Heterogeneous Exascale Hardware Platform

A Scalable Runtime for the ECOSCALE Heterogeneous Exascale Hardware Platform

Evaluation of PGAS Communication Paradigms with Geometric Multigrid

A Local-View Array Library for Partitioned Global Address Space C++ Programs

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