# 'Zhores' -- Petaflops supercomputer for data-driven modeling, machine   learning and artificial intelligence installed in Skolkovo Institute of   Science and Technology

**Authors:** Igor Zacharov, Rinat Arslanov, Maxim Gunin, Daniil Stefonishin, Sergey, Pavlov, Oleg Panarin, Anton Maliutin, Sergey Rykovanov, Maxim Fedorov

arXiv: 1902.07490 · 2019-02-21

## TL;DR

The 'Zhores' supercomputer at Skoltech, utilizing advanced processors, enhances data-driven research and AI applications across various scientific fields, achieving high performance and supporting scientific discovery.

## Contribution

This paper introduces the 'Zhores' supercomputer, detailing its hardware, performance, and usage, highlighting its role in advancing scientific research at Skoltech.

## Key findings

- Placed 6th in Russian supercomputer rankings (2018)
- Supports diverse scientific fields with high computational performance
- Enables new opportunities in data-driven modeling and AI

## Abstract

The Petaflops supercomputer "Zhores" recently launched in the "Center for Computational and Data-Intensive Science and Engineering" (CDISE) of Skolkovo Institute of Science and Technology (Skoltech) opens up new exciting opportunities for scientific discoveries in the institute especially in the areas of data-driven modeling, machine learning and artificial intelligence. This supercomputer utilizes the latest generation of Intel and NVidia processors to provide resources for the most compute intensive tasks of the Skoltech scientists working in digital pharma, predictive analytics, photonics, material science, image processing, plasma physics and many more. Currently it places 6th in the Russian and CIS TOP-50 (2018) supercomputer list. In this article we summarize the cluster properties and discuss the measured performance and usage modes of this scientific instrument in Skoltech.

## Full text

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## Figures

11 figures with captions in the complete paper: https://tomesphere.com/paper/1902.07490/full.md

## References

46 references — full list in the complete paper: https://tomesphere.com/paper/1902.07490/full.md

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Source: https://tomesphere.com/paper/1902.07490