Systems 1

Key features at a glance:

    * 20 Compute nodes with dual AMD EPYC 7502 CPUs (32 cores / 64
      threads, 2.5 MHz Base), 256 GB 8-channel DDR4-2933 RAM, CentOS 7.9
    * 4 Compute nodes with dual AMD EPYC 7452 CPUs (32 cores / 64
      threads, 2.3 MHz Base), 256 GB 8-channel DDR4-2933 RAM, dual NVidia
      Tesla V100 GPUs 32GB HBM2 RAM, CentOS 7.9
    * 1 interactive login node with AMD EPYC 7502P CPU (32 cores / 64
      threads, 2.5 MHz Base), 256 GB 8-channel DDR4-2933 RAM, Red Hat
      Enterprise Linux 7.9
    * EDR Infiniband 100 Gb/s interconnect for compute traffic
    * 16TB internal NVMe SSD Storage (HPE Clustered Extents File System)
    * 144TB HPE MSA 2050 SAS HDD Array
    * Theoretical peak CPU performance of the system is 60 TFlops (double
      precision)
    * Theoretical peak GPU performance of the system is 65 TFlops (double
      precision)
    * SLURM job scheduler
  Schematic view of Shabyt
  Scheme
  The system is assembled in a two-rack configuration and is physically
  located at NU Data Center
  Racks

Other NU research computing clusters

  Cluster name Short description Contact details
  High-performance bioinformatics cluster “Q-Symphony” Hewlett-Packard
  Enterprise – Apollo (208 Cores x Intel Xeon, 3.26 TB RAM, 258 ТB RAID
  HDD, RedHat Linux) – max computing performance 7.5 TFlops: specifically
  designed architecture optimized for bioinformatics research and
  analysis of big genomics datasets (whole-genome/whole transcriptomes
  datasets and genomics bulk datasets with more than 100 samples
  simultaneously) Ulykbek Kairov (Head of Laboratory - Leading
  Researcher, Laboratory of bioinformatics and systems biology, Private
  Institution National Laboratory Astana)
  Email: [11]ulykbek.kairov@nu.edu.kz
  Intelligence-Cognition-Robotics GPUs 8X NVIDIA Tesla V100
  Performance (Mixed Precision): 1 petaFLOPS
  GPU Memory: 256 GB total system
  CPU: Dual 20-Core Intel Xeon, E5-2698 v4 2.2 GHz
  NVIDIA CUDA Cores: 40,960
  NVIDIA Tensor Cores (on Tesla V100 based systems): 5,120
  System Memory: 512 GB 2,133 MHz DDR4 RDIMM
  Storage: 4X 1.92 TB SSD RAID 0
  Network: Dual 10 GbE, 4 IB EDR
  Operating System Canonical Ubuntu, Red Hat Enterprise Linux Zhandos
  Yessenbayev (Senior Researcher, Laboratory of Computational Materials
  Science for Energy Application, Private Institution National Laboratory
  Astana)
  Email: [12]zhyessenbayev@nu.edu.kz
  Computational resources for AI infrastructure at NU NVIDIA DGX-1 (1
  supercomputer):
  GPUs:8 x NVIDIA® Tesla® V100
  GPU Memory 256 GB
  CPU Dual 20-Core Intel Xeon E5-2698 v4 2.2 GHz
  System Memory 512 GB, 2,133 MHz DDR4 RDIMM
  Storage 4X 1.92 TB SSD RAID 0
  Performance: 1PF
  NVIDIA DGX-2 (2 supercomputers):
  GPUs: 16 x NVIDIA® Tesla® V100
  GPU: Memory 512 GB total
  CPU: Dual Intel Xeon Platinum 8168, 2.7 GHz, 24-cores
  System Memory: 1.5TB DDR4 RDIMM
  Storage: 2 x 960GB NVME SSDs
  Internal Storage: 30TB (8X 3.84TB) NVME SSDs
  Performance: 4PF
  NVIDIA DGX A100 (4 supercomputers):
  DGX A100 (01,02,03,04)
  GPUs: 8 x NVIDIA A100 40 GB GPUs
  GPU: Memory 320 GB total
  CPU: Dual AMD Rome 7742, 128 cores total, 2.25 GHz (base), 3.4 GHz (max
  boost)
  System Memory: 1TB DDR4 RDIMM
  Storage: 2 x 1.92TB M.2 NVME drives
  Internal Storage: 15 TB (4x 3.84 TB) U.2 NVMe drives
  Performance: 20PF
  Total:
  NVIDIA DGX (580 Cores x Intel,AMD, 3 TB RAM, 128 ТB RAID HDD, Ubuntu) –
  max computing performance 25 PFlops: specifically designed architecture
  optimized for Deep Learning,Machine Learning,Natural Language
  Processing,Computer Vision. Yerbol Absalyamov (Technical Project
  Coordinator, Office of the Provost - Institute of Smart Systems and
  Artificial Intelligence, Nazarbayev University)
  Email: [13]yerbol.absalyamov@nu.edu.kz
  Makat Tlebaliyev (Computer Engineer, Office of the Provost - Institute
  of Smart Systems and Artificial Intelligence, Nazarbayev University)
  Email: [14]makat.tlebaliyev@nu.edu.kz����le to do so outside of the official workdays and hours.