Attention

ShARC will be decommissioned on the 30th of November 2023, after which time users will no longer be able to access that cluster and any jobs running or queueing at that time will be cancelled.

Please see our page of important info about ShARC’s decommissioning.

Bede (Tier 2 GPU cluster)

Bede is a EPSRC-funded ‘Tier 2’ (regional) GPU-equipped HPC cluster. The system is available for use by researchers from N8 Research Partnership institutions (Durham, Lancaster, Leeds, Liverpool, Manchester, Newcastle, Sheffield and York).

NB the system was previously known as NICE-19.

Suitable workflows

This system is particularly well suited to supporting:

  • Jobs that benefit from distributing work between multiple GPUs and possibly multiple nodes.

  • Jobs that require much movement of data between CPU and GPU memory.

  • In particular deep learning and machine learning workflows that meet either of the above criteria.

Status

Academics/researchers can apply for access to the system (see Further Information) but note that some aspects of the system plus the registration and support mechanisms are still being refined.

Noteworthy features of the system

  • 32x GPU nodes (IBM AC922 nodes) each with

    • 2x IBM POWER9 CPUs

    • 2x NVIDIA V100 GPUs per CPU

    • Each CPU is connected to its two GPUs via high-bandwidth, low-latency interconnects (NVLink), which helps if you need to move lots of data to/from GPU memory

    • 512 GB RAM

  • 4x ‘inference’ nodes (IBM IC922 nodes) each with

  • High-bandwidth, low-latency networking between nodes (100 Gb/s EDR Infiniband)

  • High-performance parallel file system (Lustre)

  • Slurm job scheduler

  • Installed software

    • IBM Watson Machine Learning Community Edition

      • Includes Conda packages for helping transparently distribute Deep Learning training and inference tasks over multiple GPUs and/or nodes when using e.g. TensorFlow, IBM Caffe and Pytorch.

      • Includes conda packages for accelerating the training of generalized linear models (e.g. in scikit-learn and Apache Spark) using GPUs and multiple nodes

    • Standard GNU toolkit via the IBM Advanced Toolchain for Linux

      • Inc. IBM-optimised GNU compilers, BLAS/LAPACK, glibc, gdb, valgrind, itrace, Boost, Python, Go and more

    • NVIDIA profilers and debuggers

Further information

See the N8 CIR’s Bede site for:

  • Documentation on how to use the system

  • Information on per-institution RSE support (including the contact for Sheffield)

  • How to register a project

  • Hardware specifications

  • Available software

  • How to acknowledge Bede and the N8 CIR in publications

  • Bede and N8 CIR logos

Please contact tier-2-hpc-support-group@sheffield.ac.uk if you have any questions regarding Bede in general and the application process.