Platform LSF

Platform Load Sharing Facility (or simply LSF) is a workload management platform, job scheduler, for distributed high performance computing. It can be used to execute batch jobs on networked Unix and Windows systems on many different architectures.[2][3] LSF was based on the Utopia research project at the University of Toronto.[4]

LSF
Developer(s)IBM (current)
Platform Computing (former)
Stable release
10.2.0 (10.2.0.7[1]) / October 2017 (January 16, 2018)
Operating systemUnix, Linux, Windows
TypeJob scheduler
LicenseProprietary
WebsiteIBM Platform Computing

In 2007, Platform released Platform Lava, which is a simplified version of LSF based on an old version of LSF release, licensed under GNU General Public License v2.[5] The project was discontinued in 2011, succeeded by OpenLava.

In January, 2012, Platform Computing was acquired by IBM.[6]

The product is now called IBM Spectrum LSF.


LSF add-on products
  • IBM Platform Application Center: Web interfaces for job submission, management and remote visualization.
  • IBM Platform RTM: A real-time dashboard for monitoring global workloads and resource.
  • IBM Platform License Scheduler: License management tool with policy-driven allocation and tracking of software licenses.
  • IBM Platform Analytic : Analytic tool for visualizing and analyzing workload data.
  • IBM Platform Process Manager: An interface for designing complex engineering computational processes
  • IBM Platform Session Scheduler: Scheduling for LSF
  • IBM Platform Dynamic Cluster: Cloud management software to change static cluster into dynamic share cloud resources

LSF Extensions and integrations

LSF extensions include:

DRMAA
The Distributed Resource Management Application API handles job management in a range of distributed resource management systems.
HPC Profile Basic
This describes how JSDL, Basic Execution Service (BES) and existing web services security mechanisms can be used interoperable to address batch job scheduling use case.
LSF Perl API
This comprises two modules, Base and Batch, allowing Platform's LSF APIs to be called by Perl.
  • Base module allows Perl applications to link the Load Information Manager (LIM) and Remote Execution Server (RES) daemons for LSF services e.g. retrieving system configuration and dynamic load information for distributed clusters hosts, task placement advice via LIM, and other related functions, thereby improving application performance and resources accessibility.
  • Batch module allows Perl applications to retrieve information as well as the submission of information about the hosts, queues, users, jobs and configuration of the batch system.
SAGA (Simple API for Grid Applications)
The SAGA C++ Reference Implementation provides an LSF plug-in (adaptor) for its standardized job submission, control and monitoring API. The API is available for C++ and Python.
Python LSF wrappers
LSF's API written in C can be easily accessed using Python. Several implementations of LSF Python APIs exist.[7]

LSF is one of the job scheduler mechanisms supported by the Grid Resource Allocation Manager (GRAM) component of the Globus Toolkit.

References
  1. "IBM Spectrum LSF Process Manager V10.2.0 Fix Pack 7 (509662) Readme". Retrieved 2019-04-17.
  2. Michael R. Ault, Mike Ault, Madhu Tumma, and Ranko Mosic (2004). Oracle 10g Grid & Real Application Clusters. Rampant TechPress. p. 24. ISBN 9780974435541.CS1 maint: multiple names: authors list (link)
  3. Goering, Richard (March 8, 1999). "Load sharing brings kudos". EE Times Online. Retrieved 2007-11-12. LSF ... enables load sharing by distributing jobs to available CPUs in heterogeneous networks ... but don't tell them that; they'll just want to raise their prices
  4. "Utopia: A Load Sharing Facility for Large, Heterogeneous Distributed Computer Systems". John Wiley & Sons. CiteSeerX 10.1.1.121.1434. Cite journal requires |journal= (help)
  5. "Platform Lava". Archived from the original on 2011-04-21. Retrieved 2011-03-25.
  6. IBM Closes on Acquisition of Platform Computing
  7. pylsf on GitHub

Further reading
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