Implementing Lattice QCD Application with XcalableACC Language on Accelerated Cluster

Proceedings of the International Conference on High Performance Computing in Asia-Pacific Region

Murai

Sato

2019

Self Cite

Many systems used in HPC field have multiple accelerators on a single compute node. However, programming for multiple accelerators is more difficult than that for a single accelerator. Therefore, in this paper, we propose an OpenMP extension that allows easy programming for multiple accelerators. We extend existing OpenMP syntax to create Partitioned Global Address Space (PGAS) on separated memories of several accelerators. The feature enables users to perform programming to use multiple accelerators in ease. In performance evaluation, we implement the STREAM Triad and the HIMENO benchmarks using the proposed OpenMP extension. As a result of evaluating the performance on a compute node equipped with up to four GPUs, we confirm that the proposed OpenMP extension demonstrates sufficient performance.

Section: Discussionmentioning

confidence: 99%

“…Nakao et el. [10,26] develop an XcalableACC directive-based language for accelerated clusters. XACC is a new language in which XMP and OpenACC are vertically integrated, using XMP for host side programming and OpenACC for accelerator side programming.…”

Section: Related Workmentioning

confidence: 99%

Multi-accelerator extension in OpenMP based on PGAS model

Proceedings of the International Conference on High Performance Computing in Asia-Pacific Region

Murai

Sato

2019

Self Cite

“…The implementation in XACC is basically the same procedure as in the previous study (Nakao et al, 2017) but differs as follows to improve productivity and performance.…”

Section: Methodsmentioning

confidence: 99%

“…Moreover, we also propose TCA/IB hybrid communication, which is a combination of low-latency communication with TCA and high bandwidth with IB (Matsumoto et al, 2015;Odajima et al, 2015). In addition, in order to improve productivity on accelerated clusters, we also develop XcalableACC (XACC), which is a directivebased parallel language (Nakao et al, 2014(Nakao et al, , 2017Xcala-bleACC Specification, 2018). Since the directives can deal with TCA/IB hybrid communication internally, XACC enables users to develop high performance applications at a low programming cost on accelerated clusters (Odajima et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of XcalableACC with tightly coupled accelerators/InfiniBand hybrid communication on accelerated cluster

The International Journal of High Performance Computing Applica

Odajima

Murai

et al. 2019

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Accelerated clusters, which are cluster systems equipped with accelerators, are one of the most common systems in parallel computing. In order to exploit the performance of such systems, it is important to reduce communication latency between accelerator memories. In addition, there is also a need for a programming language that facilitates the maintenance of high performance by such systems. The goal of the present article is to evaluate XcalableACC (XACC), a parallel programming language, with tightly coupled accelerators/InfiniBand (TCAs/IB) hybrid communication on an accelerated cluster. TCA/IB hybrid communication is a combination of low-latency communication with TCA and high bandwidth with IB. The XACC language, which is a directive-based language for accelerated clusters, enables programmers to use TCA/IB hybrid communication with ease. In order to evaluate the performance of XACC with TCA/IB hybrid communication, we implemented the lattice quantum chromodynamics (LQCD) mini-application and evaluated the application on our accelerated cluster using up to 64 compute nodes. We also implemented the LQCD mini-application using a combination of CUDA and MPI (CUDA + MPI) and that of OpenACC and MPI (OpenACC + MPI) for comparison with XACC. Performance evaluation revealed that the performance of XACC with TCA/IB hybrid communication is 9% better than that of CUDA + MPI and 18% better than that of OpenACC + MPI. Furthermore, the performance of XACC was found to further increase by 7% by new expansion to XACC. Productivity evaluation revealed that XACC requires much less change from the serial LQCD code to implement the parallel LQCD code than CUDA + MPI and OpenACC + MPI. Moreover, since XACC can perform parallelization while maintaining the sequential code image, XACC is highly readable and shows excellent portability due to its directive-based approach.

“…Because the use of PGAS languages is familiar in one-sided communication, applications in PGAS languages can sometimes exhibit higher performance than those using MPI library by directly using a communication layer close to hardware [5,6]. Examples of PGAS languages include XcalableMP (XMP) [5,7,8]; XcalableACC [9][10][11]; Coarray Fortran [12], PCJ [13], Unified Parallel C, 1 UPC++ [14], HabaneroUPC++ [15], X10 [16], Chapel [17], and DASH [18].…”

Section: Introductionmentioning

confidence: 99%

Mixed-Language Programming with XcalableMP

XcalableMP PGAS Programming Language

2020

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This chapter presents the mixed-language programming with XcalableMP and other programming languages. It is supported by the linkage functions between XcalableMP and MPI library. We also demonstrate how to call XcalableMP program from Python program (M. Nakao et al., Linkage of XcalableMP and Python languages for high productivity on HPC cluster system, Proceedings of Workshops of HPC Asia, No .9, pp.39–47, 2018).