The Tofu Interconnect 2

Ajima, Yuichiro; Inoue, Takahiro; Hiramoto, Shinya; Ando, Shun; Maeda, Masatsugu; Yoshikawa, Toshio; Hosoe, Koji; Shimizu, Toshiyuki

doi:10.1109/hoti.2014.21

Cited by 10 publications

(1 citation statement)

References 6 publications

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“…an in-house interconnection network for cross-node communication. However, our techniques can be easily ported to other high-performance interconnection networks like InfiniBand [14] and Tofu interconnect [15], [16] too. The TH-Express network builds upon two specialized chips, a Network Interface Chip (NIC) and a Network Router Chip (NRC).…”

Section: To Networkmentioning

confidence: 99%

Faster and Scalable MPI Applications Launching

Dai

Dong

Xie

et al. 2024

IEEE Trans. Parallel Distrib. Syst.

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Distributed parallel MPI applications are the dominant workload in many high-performance computing systems. While optimizing MPI application execution is a well-studied field, little work has considered optimizing the initial MPI application launching phase, which incurs extensive cross-machine communications and synchronization. The overhead of MPI application launching can be expensive, accounting for over 200 million processor core hours and 15% of the user core time annually on the production Tianhe-2A supercomputer, which will increase as the number of parallel machines used grows. Therefore, it is critical to optimize the MPI application launching process. This paper presents a novel approach to optimizing the MPI application launch. Our approach adopts a location-aware address generation rule to eliminate the need for address exchange and a topology-aware global communication scheme to optimize cross-machine synchronization. We then design a new application launch procedure to support the proposed optimizations to further reduce the pressure of the shared I/O system. Our techniques have been deployed to production in the Tianhe-2A supercomputer and the Next Generation Tianhe Supercomputer. Experimental results show that our approach scales well and outperforms alternative schemes, reducing the MPI application launching time by over 29% with 320K MPI processes.

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Section: To Networkmentioning

confidence: 99%