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CalHPC - High Performance Computing Cluster Service

SERVICE DESCRIPTION

Description:

CalHPC provides support for high-performance Linux computing clusters hosted in the campus Data Center. Cluster management is provided by the Scientific Cluster Support (SCS) group of the Lawrence Berkeley National Laboratory (LBNL).

For:

faculty, staff, department

Charges:

recharge

Costs:

Cost will vary depending upon the size and complexity of the cluster. Costs for standard components are listed.

Cluster Management:

  • Master node: $465/month
  • Compute node: $18.61/month per node
  • Infiniband (optional): $465/month
  • Myrinet (optional): $155/month
  • Storage array (optional): $465/month
  • Consulting (Time&Materials): $170/hour

Colocation

  • Rack unit: $8/month
  • Full cabinet (40 rack units): $304/month

Network - 1-Gigabit connections

  • Port activation: $301 (one-time charge)for first connection; $56 for additional connections placed at the same time
  • $13.31/month per port

Contact:

TAM Request Form
Introduction

Clusters built using inexpensive, commodity hardware and open-source Linux software have proven to be affordable, reliable, and scalable.

Using cluster-based systems, researchers are able to take advantage of parallel computing applications to perform time- or data-intensive simulations not previously possible. High-performance computing (HPC) is enabling researchers to address complex problems in nearly all disciplines — from science and engineering to humanities and education — that have a direct bearing on society and the quality of life.

Having the appropriate site for hosting the cluster is also a consideration. Large, multinode clusters need sufficient network, bandwidth, and security, along with significant amounts of cooling and electrical infrastructure in order to operate.

Recognizing the need for an affordable cluster support service, LBNL developed a Scientific Cluster Support (SCS) program that has been running successfully since 2003. The service has proven to be very effective and popular with researchers; the SCS group has implemented, and currently manages, 34 production clusters comprising more than 5300 processors.

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