This paper offers a solution to overcome the complexities of production system I/O performance monitoring. We present Beacon, an end-to-end I/O resource monitoring and diagnosis system for the 40960-node Sunway TaihuLight supercomputer, currently the fourth-ranked supercomputer in the world. Beacon simultaneously collects and correlates I/O tracing/profiling data from all the compute nodes, forwarding nodes, storage nodes, and metadata servers. With mechanisms such as aggressive online and offline trace compression and distributed caching/storage, it delivers scalable, low-overhead, and sustainable I/O diagnosis under production use. With Beacon’s deployment on TaihuLight for more than three years, we demonstrate Beacon’s effectiveness with real-world use cases for I/O performance issue identification and diagnosis. It has already successfully helped center administrators identify obscure design or configuration flaws, system anomaly occurrences, I/O performance interference, and resource under- or over-provisioning problems. Several of the exposed problems have already been fixed, with others being currently addressed. Encouraged by Beacon’s success in I/O monitoring, we extend it to monitor interconnection networks, which is another contention point on supercomputers. In addition, we demonstrate Beacon’s generality by extending it to other supercomputers. Both Beacon codes and part of collected monitoring data are released.1

/pdf/end-to-end-i-o-monitoring-on-leading-supercomputers-24ck8api.pdf

End-to-end I/O Monitoring on Leading Supercomputers

Julich Supercomputing Centre (JSC) started running (extreme) scaling workshops with its first IBM Blue Gene supercomputer, finally spanning three generations each seeing an increase in the number of cores and available threads. Over the years, this workshop series attracted numerous international code teams and resulted in many applications capable of running on all available cores of each system. This article reviews some of the knowledge gained with running and tuning highly-scalable applications, focussing on JUQUEEN, the IBM Blue Gene/Q at JSC. The ability to execute successfully on all 458752 cores with up to 1.8 million processes or threads may qualify codes for the High-Q Club, which serves as a showcase for diverse codes scaling to the entire 28 racks, effectively defining a collection of the highest scaling codes on JUQUEEN. The intention was to encourage other developers to invest in tuning and scaling their codes while identifying the necessary key aspects for that goal. As this era closes, it is timely to compare the characteristics of the 32 High-Q Club member codes, considering their strong and/or weak scaling, exploitation of hardware threading, and whether/how intra-node multi-threading is employed combined with message-passing. We also identify the obstacles for scaling such as inefficient use of limited compute node memory and file I/O as key governing factors. Overall, the analysis provides guidance as to how applications may (need to) be designed in future to exploit expected exa-scale computer systems.

https://superfri.org/superfri/article/download/163/260

The High-Q Club: Experience with Extreme-scaling Application Codes

Remote Memory Access (RMA) enables direct access to remote memory to achieve high performance for HPC applications. However, most modern parallel programming models lack schemes for the remote process to detect the completion of RMA operations. Many previous works have proposed programming models and extensions to notify the communication peer, but they did not solve the multi-NIC aggregation, portability, hardware-software co-design, and usability problems. In this work, we proposed a Unified Notifiable RMA (UNR) library for HPC to address these challenges. In addition, we demonstrate the best practice of utilizing UNR within a real-world scientific application, PowerLLEL. We deployed UNR across four HPC systems, each with a different interconnect. The results show that PowerLLEL powered by UNR achieves up to a 36% acceleration on 1728 nodes of the Tianhe-Xingyi supercomputing system.

UNR: Unified Notifiable RMA Library for HPC

The ibm® Blue Gene®/q (bg/q) supercomputer system was developed in partnership between ibm, the Argonne National Laboratory, and the Lawrence Livermore National Laboratory. Blue Gene/Q is a bright example of the United States Department of Energy and IBM's capability and seamlessly brings together science and technology and the people that make this possible. Mira is a system, due in large part to the insights gained through years of partnership on the Blue Gene family among Argonne, Lawrence Livermore, and ibm. The ibm®Blue Gene®/l supercomputer debuted in November 2004, followed by the second generation three years later. Indeed, the second and third generations, called Blue Gene®/p and Blue Gene®/q, respectively, were conceived before Blue Gene/L was formally announced. With the deployment of Sequoia in Livermore, and the Mira 48-rack system in Argonne, Blue Gene/Q began to accumulate its trophies. The system software objectives on Blue Gene/Q are ultra-scalability, high reliability, and delivering the full performance capability of the hardware to applications.

Blue Gene/Q: Sequoia and Mira

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Blue Gene/Q: Sequoia and Mira