S-Aligner: Ultrascalable Read Mapping on Sunway Taihu Light

Duan, Xiaohui; Xu, Kai; Chan, Yuandong; Hundt, Christian; Schmidt, Bertil; Balaji, Pavan; Liu, Weiguo

doi:10.1109/cluster.2017.16

Cited by 5 publications

(2 citation statements)

References 24 publications

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“…The number and proportion of hybrid architecture building systems in the TOP500 are constantly improving. Five of the top 10 systems have adopted an accelerated component hybrid architecture, ranking first in the world and ranking second in the world in Shenwei Taihu Light supercomputer system (Duan et al, 2017). The computer uses domestic Shenwei multi-core technology, with a total of 10.64 million processor cores.…”

Section: Development Of High Performance Computing Technologymentioning

confidence: 99%

Development of Operational Technology for Meteorological High Performance Computing

Sun¹,

Wang²

2019

GEP

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As an important branch of information technology, high-performance computing has expanded its application field and its influence has been expanding. High-performance computing is always a key area of application in meteorology. We used field research and literature review methods to study the application of high performance computing in China's meteorological department, and obtained the following results: 1) China Meteorological Department gradually established the first high-performance computer system since 1978. High-performance computing services can support operational numerical weather prediction models. 2) The Chinese meteorological department has always used the relatively advanced high-performance computing technology, and the business system capability has been continuously improved. The computing power has become an important symbol of the level of meteorological modernization. 3) High-performance computing technology and meteorological numerical forecasting applications are increasingly integrated, and continue to innovate and develop. 4) In the future, high-performance computing resource management will gradually transit from the current local pre-allocation mode to the local remote unified scheduling and shared use. In summary, we have come to the conclusion that the performance calculation business of the meteorological department will usher in a better tomorrow.

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Section: Development Of High Performance Computing Technologymentioning

confidence: 99%

Development of Operational Technology for Meteorological High Performance Computing

Sun¹,

Wang²

2019

GEP

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“…There are many successful implementations of multi-node alignment algorithms, such as pBWA [10] and mpiBLAST [11], that used MPI (Message Passing Interface) to run BWA and BLAST [12] in multi-node. MerAligner [13] and S-Aligner [14] applied the HPC (High Performance Computing) technique. MerAligner was based on a successful single-node SIMD (Single Instruction Multiple Data) implementation [15] of the Smith–Waterman Algorithm [16], while S-Aligner designed a new algorithm similar to the alignment pipeline of RazerS3 [17].…”

Section: Introductionmentioning

confidence: 99%

PipeMEM: A Framework to Speed Up BWA-MEM in Spark with Low Overhead

Zhang

Liu

Dong

2019

Genes

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(1) Background: DNA sequence alignment process is an essential step in genome analysis. BWA-MEM has been a prevalent single-node tool in genome alignment because of its high speed and accuracy. The exponentially generated genome data requiring a multi-node solution to handle large volumes of data currently remains a challenge. Spark is a ubiquitous big data platform that has been exploited to assist genome alignment in handling this challenge. Nonetheless, existing works that utilize Spark to optimize BWA-MEM suffer from higher overhead. (2) Methods: In this paper, we presented PipeMEM, a framework to accelerate BWA-MEM with lower overhead with the help of the pipe operation in Spark. We additionally proposed to use a pipeline structure and in-memory-computation to accelerate PipeMEM. (3) Results: Our experiments showed that, on paired-end alignment tasks, our framework had low overhead. In a multi-node environment, our framework, on average, was 2.27× faster compared with BWASpark (an alignment tool in Genome Analysis Toolkit (GATK)), and 2.33× faster compared with SparkBWA. (4) Conclusions: PipeMEM could accelerate BWA-MEM in the Spark environment with high performance and low overhead.

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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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S-Aligner: Ultrascalable Read Mapping on Sunway Taihu Light

Cited by 5 publications

References 24 publications

Development of Operational Technology for Meteorological High Performance Computing

Development of Operational Technology for Meteorological High Performance Computing

PipeMEM: A Framework to Speed Up BWA-MEM in Spark with Low Overhead

Sunway supercomputer architecture towards exascale computing: analysis and practice

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