Russian company's presence in the list of the world's best performing storage systems has increased by 33%
Moscow, July 5 2021 — Four storage systems have been installed by RSC, the leading Russian developer and worldwide well-known integrator of innovative high-dense energy-efficient solutions for HPC (high-performance computing), data centers, cloud platforms and storage-on-demand, are the only Russian systems in the new global IO500 rating of the best performing HPC-grade storage (announced at ISC 2021, the largest European supercomputer exhibition). RSC has increased its presence in this prestigious list by 33% (from three systems in the previous rating).
The current IO500 list includes a new segment based on RSC Storage on-Demand solution with support of Intel’s DAOS open source storage system, which has been implemented at the Joint Institute for Nuclear Research (JINR, Dubna). It is the leading Russian system in the rating on the 27th position. This pilot project with DAOS support has been created for data processing purposes within the scope of NICA mega project. JINR's Lustre based storage system is also a part of IO500 on 31st place. Storage system of MVS-10P OP2 supercomputer (Joint Supercomputer Center of the Russian Academy of Sciences, JSCC RAS) holds 27th position in the list, and the storage system of Polytechnic RSC Tornado supercomputer (Saint Petersburg State Polytechnic University, SPbPU) stays on 36th place.
These excellent results in all projects were achieved by using unique distributed composable RSC Storage on-Demand systems supporting DAOS and Lustre file systems based on Intel SSD and Intel Optane SSD with NVMe interfaces. Supercomputer of JSCC RAS also features new storage nodes based on high-speed Intel SSD drives in E1.S form-factor (nicknamed “rulers”).
When Govorun supercomputer was just deployed at JINR in June 2018, it occupied the high 9th place in the global IO500 rating.
DAOS support in RSC Storage-on-Demand solutions
In addition to NFS and Lustre file systems, RSC's Storage on-Demand solutions now support Intel's distributed open-source object storage system, DAOS (Distributed Asynchronous Object Storage). It provides highest processing speeds for various types of data in the distributed storage system.
This solution is optimal for AI (ML/DL) segment. It enables multi-layered storage systems based on Lustre file system within Disaggregated Composable Infrastructure and flexible management of NVMe drive pools as well as DAOS-based storage systems with external distributed NVMe drive pool. This approach to DAOS realization enables high-performance storage with flexible capacity ratios between Intel Optane DC Persistent Memory modules and NVMe drives connected to DAOS server. This effectively provides flexible “on-demand” configurations for specific user workloads. RSC's specialists used their experience in composable disaggregated solutions for DAOS management. It is now possible to use convenient RSC BasIS orchestration platform's user interface (UI) for DAOS-based systems.
DAOS provides significant performance increase with a number of architectural principles:
• Maximum efficiency of CPU / OS core resources, interrupts, context switching when data is moved from storage to the point of processing;
• Storage of data with on-demand availability (metadata and data caches) on Storage Class Memory devices with efficient support of Byte Level Access;
• Most transparent streaming of continuous and block-based R/W operations in NVMe-based devices.
New RSC Storage on-Demand user interface
RSC’s specialists have developed new RSC Storage on-Demand user interface that enables on-demand creation of complex multi-layered composable storage systems. This UI supports creation of parallel NFS, Lustre file systems, distributed DAOS storage systems and their combinations.
These approaches have been described in JINR's, RSC’s and Intel's keynote at ISC 2021 on June 29th.
Supercomputer named after N. N. Govorun in JINR
Govorun supercomputer of the Joint Institute for Nuclear Research is a joint project of the Theoretical Physics Laboratory (TPL) named after N.N. Bogolyubov and Laboratory of IT (LIT) supported by JINR board. It was deployed in 2018 with help of specialists from RSC Group and Intel Corporation.
The initial installation the Govorun supercomputer in 2018 enabled a lot of complex and resource-intensive simulations in the field of quantum chromodynamics patterns for research of hadronic matter properties at high energy density and barion charge and in presence of extra strong electromagnetic fields/ It also accelerated generation and reconstruction of events for planned experiments for coming NICA ion collider. Supercomputer boosted calculation speed of radiation safety of experimental JINR units; significantly accelerated radiation biology research and other applied science problems at JINR; supported in international collaborations. Research results were published in over 50 leading global science journals, including Nature Physics.
JINR supercomputer was upgraded in 2019. The new hyper-converged and software-defined system has total theoretical peak performance of 860 TFLOPS with double precision. It’s novel approach has unique features to make it adaptable for specific user workloads and maximize utilization of supercomputer's resources.
Hyper-converged approach resulted in unique high-speed storage system for “Govorun” with leading characteristics and cost-efficiency.
An implementation of “storage-on-demand” approach in JINR supercomputer enables re-configuration of a specific storage system for each user or application with all required properties (capacity, speed, file system, persistence, reliability and security), which would also be impossible to achieve with standard, monolithic approach to HPC storage.
MVS-10P OP2 supercomputer at JSCC RAS
The Joint Supercomputer Center of the Russian Academy of Sciences is one of the powerful Russian supercomputing centers in the field of science and high education. Over 150 research groups use HPC resources of JSCC RAS for solving fundamental and applied tasks.
Total peak performance of JSCC RAS systems deployed by RSC based on ultrahigh-dense and energy efficient RSC Tornado and RSC PetaStream solutions with 100% ‘hot water’ liquid cooling is currently 1.7 Petaflops.
MVS-10P OP2 supercomputer at JSCC RAS had undergone another scheduled upgrade in 2020. Its peak performance has been increased by almost two times by 93% and is currently 823.91 Teraflops.
‘Polytechnic – RSC Tornado’ supercomputer at SPbPU
St. Petersburg Polytechnic State University named after Peter the Great started creating one of the most powerful and innovative supercomputer centers (SCC) in Russia with peak performance over 1.1 Petaflops back in 2014, and ‘Polytechnic’ SCC has been commissioned successfully in 2015.
SPbPU supercomputer center is focused on solving inter-disciplinary natural science research tasks and design of complex technical systems for hi-tech segments of local industries and science. The overall peak performance of SPbPU supercomputers has been increased by 23% in 2020 and currently amounts 1.6 Petaflops.
After scheduled upgrade of ‘Polytechnic - RSC Tornado’ supercomputer in 2020 its peak performance has increased by 29% to 1.309 Petaflops.
