Case Study - A*STAR - The Agency for Science, Technology and Research
Customer
The Agency for Science, Technology and Research (A*STAR)
Industry
Scientific research
Challenges
- There were high levels of user discontent and not enough computational resources for the population of users or the number of research projects
- A*STAR needed a world-class scheduler which would increase utilization across its entire computing platform, providing support for computationally intensive research at the agency
Solution
Platform LS
Results
- Platform LSF enabled A*STAR’s systems to maximize compute resources and reach 100 percent utilization
- A*STAR was able to run a single workload scheduler across its entire computing platform, meaning it was easier for users to schedule jobs and move them between machines, addressing user discontent
Supporting Singapore’s Economic Clusters
The Agency for Science, Technology and Research (A*STAR) has a mission to drive and sustain world-class scientific research that will be meaningful and impactful for Singapore. As the largest government-funded research organization in South East Asia, A*STAR oversees 14 biomedical sciences, physical sciences and engineering research institutes and supports Singapore’s key economic clusters by providing intellectual, human and industrial capital to its partners in industry. It also supports research in universities, hospitals, research centres, and with other local and international partners.
Addressing High Levels of User Discontent
Before implementing Platform Computing’s LSF product, A*STAR suffered from high levels of user discontent. There were simply not enough computational resources for the population of users and the vast number of research projects being undertaken at the organization. In order to resolve this, A*STAR spent two years increasing its hardware capability and making its software environment uniform, but needed to maximize its existing resources further in order to address user dissatisfaction. “One of our main objectives was to find the best workload scheduler on the market,” said Dr. Marek Michalewicz, director of A*STAR’s computational research centre. “Previously, we had a number of different machines, each with a different operating system and scheduler. Our desire was to install a single workload scheduler uniformly across all computer platforms, meaning that jobs could be managed and moved quickly and easily.”
The Most Optimal Solution
A*STAR looked at a number of different options before selecting Platform LSF. “We decided that Platform LSF would be the most optimal solution,” continued Dr. Marek Michalewicz. “Platform LSF is the scheduler of choice for many organizations in Singapore, so we were aware of the benefits it could offer to A*STAR.”
Approaching 100% Utilization
With Platform LSF acting as the single unifying workload scheduler across its computing platforms, A*STAR very rapidly saw an increase in terms of resource utilization. “Platform LSF was the perfect fit for our user community,” continued Dr. Marek Michalewicz. “Not only did it make it incredibly easy to move and schedule jobs, but it also meant that we could very quickly increase the utilization of new resources as and when they were needed. This could be up to as much as 100 per cent in just five or six weeks.” With Platform LSF, Dr. Michalewicz and his team were able to ensure that the right resources were allocated to the right users for maximum efficiency. Similarly, simplified job submission equated to a significant reduction in setup time and far fewer operation errors, meaning less time spent on administration, more on research.
Platform Computing
Platform Computing, an IBM Company, is a leader in cluster, grid, and cloud management software - serving more than 2,000 of the world’s most demanding organizations. Since 1992 its workload and resource management solutions have delivered optimized IT infrastructures, ease of management, and lower costs for enterprise, HPC, and technical computing clients. Visit www.platform.com. Twitter: @Platform_Tweets. For more information about IBM Technical Computing: http://www.ibm.com/deepcomputing.
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