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Chinese supercomputer makes breakthrough in cosmological N-body simulation

By Phate Zhang
Mar 17, 2020 at 6:25 PM UTC
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Chinese supercomputer makes breakthrough in cosmological N-body simulation-CnTechPost

Recently, Shanghai Jiaotong University's ฯ€2.0 supercomputer system has achieved a new breakthrough in the number of astronomical N-body simulation particles, breaking the world record.

Shanghai Jiaotong University Network Information Center, Department of Astronomy and Xiamen University Astronomy Department, and other units, relying on the Jiaotong University supercomputer platform (ฯ€2.0 cluster), successfully completed the 4.4 trillion particle cosmo-ฯ€ test of the large-scale structure of the universe N-body simulation Node, 20480 core).

They tracked the universe's evolution since 13.7 billion years and broke the previous TianNu numerical simulation world record of 3 trillion particles (using 13824 nodes and 331776 cores), becoming the astronomical N-body simulation with the largest number of particles in the world.

The research result "CUBE-Towards an Optimal Scaling of Cosmological N-body Simulations" was included in CCGRID 2020, the authoritative international conference in the field of high-performance computing and parallel and distributed systems, and became the only one in the world to qualify for the IEEE International Scalable Computing Challenge SCALE 2020. s solution. A preprint of the paper has been published on arXiv.

Supercomputers are made up of hundreds or even thousands of processors, which can process large amounts of data and perform simulations, with a wide range of applications.

Shanghai Jiaotong University has been committed to the construction and investment of supercomputers, from ฯ€1.0 to ฯ€2.0 supercomputer systems participated in the construction of Inspur and entered the global TOP500 supercomputer ranking in June 2013.

This system has been serving teachers and students throughout the school and has provided services to 258 research groups of Shanghai Jiaotong University in 6 years, running more than 2 million assignments.

With the support of this set of supercomputers, many high-quality academic results have appeared. For example, in March 2018, the internationally renowned Science magazine published the latest results centered on Professor Zhao Liping's team at the School of Life Science and Technology of Shanghai Jiaotong University.

Chinese supercomputer makes breakthrough in cosmological N-body simulation-CnTechPost

ฯ€1.0 (left) and ฯ€2.0 (right) supercomputer systems ฯ€1.0 (left) and ฯ€2.0 (right) supercomputer systems

In 2019, Shanghai Jiaotong University's ฯ€2.0 supercomputer system was officially launched. The new supercomputer system uses the latest processors. It is the first of its kind in China. The peak speed of floating-point calculations exceeds 2 trillion times.

At present, the ฯ€ 2.0 cluster has been fully integrated into the teaching and research activities of Shanghai Jiaotong University, helping the teaching of the school curriculum, and each course provides professional teaching assistant support to assist in completing homework calculation tasks, enabling students to experience the "speed and passion" of supercomputers in the classroom.

It covers various disciplines and supports scientific research and engineering applications in the fields of oceanography, biomedicine, materials science, aerospace, mechanical manufacturing, astrophysics, etc., and race against time to accelerate innovation.

In some applications, compared with ฯ€1.0, the computing power of ฯ€2.0 single node is increased by 4.5 times, and the performance of four nodes is increased by 4.7 times.

Test results on astronomy, ocean, material genes and other examples show that these examples achieve 2-5 times performance improvement on ฯ€2.0.

The ฯ€ supercomputer is transforming to a large computing platform. It not only provides computing resources, but also customizes development and optimization services according to user needs. It will continue to help the school's teachers and students improve scientific research efficiency and overcome more scientific problems.

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