Heterogeneous Exascale Computing

Hluchý, Ladislav; Bobák, Martin; Müller, Henning; Graziani, Mara; Maassen, Jason; Spreeuw, H.; Heikkurinen, Matti; Pancake-Steeg, Jörg; Spahr, Stefan; Felde, Nils Otto vor dem Gentschen; Höb, Maximilian; Schmidt, Jan; Belloum, Adam; Cushing, Reginald; Nowakowski, Piotr; Meizner, Jan; Rycerz, Katarzyna; Wilk, Bartosz; Bubak, Marian; Habala, Ondrej; Seleng, Martin; Dlugolinský, Štefan; Tran, Viet; Nguyen, Giang

doi:10.1007/978-3-030-14350-3_5

Cited by 8 publications

(9 citation statements)

References 13 publications

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“…Owing to the increasing ratio of memory access bandwidth compared to computing performance and the increasing ratio of network bandwidth compared to computing performance, the performance of the irregular applications is improved significantly. This has been well proven by the testing results of HPCG 7) and GRAPH500 8) , which indicates the effective expansion of system performance of the exascale supercomputer. Table 6 lists the scales and performances of ten common large-scale applications implemented on Sunway TaihuLight and estimated on exascale system, respectively.…”

Section: Analysis Of the System Performancementioning

confidence: 73%

“…It is expected that the first exascale supercomputer will be debuted in around 2021, which will open the exascale era for high performance computing (HPC). However, because of the slowdown of both Moore's law [1] and Dennard Scaling law [2], the improvements of system performance and efficiency are becoming increasingly difficult, bringing unprecedented challenges on architecture design for exascale supercomputer [3][4][5][6][7][8][9][10][11][12]. As one of the leading teams of supercomputer research and development in China, Sunway has solid foundations on both theoretical research and engineering practice on the supercomputer design, which has been proven by the successful implementations of Sunway BlueLight [13,14], Sunway TaihuLight [15][16][17][18][19] and Sunway exascale prototype.…”

Section: Introductionmentioning

confidence: 99%

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Sunway supercomputer architecture towards exascale computing: analysis and practice

Gao¹,

Zheng²,

Qi³

et al. 2021

Sci. China Inf. Sci.

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In recent years, the improvements of system performance and energy efficiency for supercomputers have faced increasing challenges, which create more intensive demands on the architecture design for realizing exascale computing. This paper first analyzes the main requirements of exascale computing on the aspects of the parallel computing application and supercomputing center operation. Afterwards, a mapping scheme of "demands-challenges-architecture" is proposed. Then, the major challenges of exascale supercomputer, such as scalability, power consumption, data movement, programming and availability, are thoroughly analyzed, and the corresponding appropriate solutions are proposed. Moreover, this paper proposes the Sunway computer architecture towards exascale computing in which the many-core processor, network chipset and software system are all domestically-designed. The technology roadmap of Sunway supercomputer will hold the comprehensive design methods for the architecture, including the processor, interconnect network, assembly structure, power supply, cooling system, system software, parallel algorithm and application support, promising great advances for exascale supercomputing.

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Section: Analysis Of the System Performancementioning

confidence: 73%

Section: Introductionmentioning

confidence: 99%

Sunway supercomputer architecture towards exascale computing: analysis and practice

Gao¹,

Zheng²,

Qi³

et al. 2021

Sci. China Inf. Sci.

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“…The next direct steps focus on efficient data transfers, also including the model of data transfer nodes as investigated in the EU-funded project PROCESS and published in [12] and [1]. For such a data access also the authentication mechanism needs to be enhanced.…”

Section: Resultsmentioning

confidence: 99%

Enabling EASEY Deployment of Containerized Applications for Future HPC Systems

Höb

Kranzlmüller

2020

Lecture Notes in Computer Science

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The upcoming exascale era will push the changes in computing architecture from classical CPU-based systems towards hybrid GPU-heavy systems with much higher levels of complexity. While such clusters are expected to improve the performance of certain optimized HPC applications, it will also increase the difficulties for those users who have yet to adapt their codes or are starting from scratch with new programming paradigms. Since there are still no comprehensive automatic assistance mechanisms to enhance application performance on such systems, we propose a support framework for future HPC architectures, called EASEY (Enable exASclae for EverYone). Our solution builds on a layered software architecture, which offers different mechanisms on each layer for different tasks of tuning, including a workflow management system. This enables users to adjust the parameters on each of the layers, thereby enhancing specific characteristics of their codes. We introduce the framework with a Charliecloud-based solution, showcasing the LULESH benchmark on the upper layers of our framework. Our approach can automatically deploy optimized container computations with negligible overhead and at the same time reduce the time a scientist needs to spent on manual job submission configurations.

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“…As the MEE is a generic architecture, capable of supporting a wide range of simulations and HPC studies, not necessarily limited to medical sciences, work is underway to extend its usage to applications which call for simultaneous processing of data across a range of HPC centres. This is being done in research investigating the major challenges and the basic architecture of the scalable storage and compute platform for exascale processing of extremely large datasets [30,31], in the context of the PROCESS project [32], and involves developing support for simulation steps encapsulated in application containers (e.g. Docker and Singularity), which can be freely distributed to multiple computing infrastructures for better parallelization of computational tasks.…”

Section: Discussionmentioning

confidence: 99%

The EurValve model execution environment

et al. 2020

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The goal of this paper is to present a dedicated high-performance computing (HPC) infrastructure which is used in the development of a so-called reduced-order model (ROM) for simulating the outcomes of interventional procedures which are contemplated in the treatment of valvular heart conditions. Following a brief introduction to the problem, the paper presents the design of a model execution environment, in which representative cases can be simulated and the parameters of the ROM fine-tuned to enable subsequent deployment of a decision support system without further need for HPC. The presentation of the system is followed by information concerning its use in processing specific patient cases in the context of the EurValve international collaboration.

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Heterogeneous Exascale Computing

Cited by 8 publications

References 13 publications

Sunway supercomputer architecture towards exascale computing: analysis and practice

Sunway supercomputer architecture towards exascale computing: analysis and practice

Enabling EASEY Deployment of Containerized Applications for Future HPC Systems

The EurValve model execution environment

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