NAG Enables Significant Multicore Performance Improvements on HECToR
SC ’09, November 14, 2009
(Stand 1210, SC09, Portland Convention Center, Portland Oregon) The Numerical Algorithms Group (NAG) announces new HPC performance milestones including up to 4 times better performance with multicore optimization for materials science and quantum Monte Carlo applications and reductions of up to 25% in runtimes with I/O tuning for an ocean modelling application. These are the early results of NAG's distributed Computational Science and Engineering (dCSE) support program for HECToR (UK's national supercomputing facility), which now consists of over 30 dedicated application optimization projects complementing the traditional HPC user support provided by NAG.
In the first project to complete, a key materials science code, CASTEP, used by academic researchers and industry was enhanced with band-parallelism to allow the code to scale to more than 1,000 cores. The speed of CASTEP on a fixed number of cores was also improved by up to 4x on the original, representing a potential saving of around $3M of computing resources over the remainder of the HECToR service. The CASTEP project showed the collaborative nature of the dCSE program, with the University of York undertaking the core development (8 person months) in conjunction with NAG HPC staff and the Science and Technology Facilities Council.
In another project, an ocean modeling application known as NEMO (Nucleus for European Modelling of the Ocean) underwent optimization including I/O techniques and variable resolution approaches to run 25% faster on relevant use cases. This represents a $600,000 saving in computing resources for that project with potentially multi-million dollar savings across all NEMO users. The 6 person-month project was performed by a collaboration of the National Oceanography Centre and the University of Edinburgh working with NAG HPC staff.
A third project optimized a quantum Monte Carlo code (CASINO) for better performance on multicore nodes by introducing shared memory techniques and hierarchical parallelism. This resulted in performance gains of up to 4x on quad-core nodes and further performance gains from I/O optimizations for simulations using more than 10,000 cores. Following NAG's work, the scientists were able to run on 40,000 cores of the Jaguar Petaflops supercomputer at Oak Ridge National Laboratory. This 12 person-month dCSE project was undertaken by NAG HPC staff working with users at University College London, and is estimated to have saved the researchers around $1M in computing resources on HECToR.
“These three examples of HPC software projects show the real performance advantages – and cost savings – to researchers from enhancing applications to run optimally on the latest HPC machines”, said Andrew Jones, Vice-President of HPC Consulting at NAG. “Investment in application performance and algorithms appropriate to the computer architecture has now become critical for efficient use of HPC resources and users’ time.”
NAG’s dCSE projects enhance the performance of dozens of community HPC applications used on HECToR and all performance improvements are fed back into the community so that non-HECToR users can benefit too. Further examples can be found on the NAG website (www.https://nag.com//Market/casestudies.asp) or the HECToR website (http://www.hector.ac.uk/cse/).
NAG provides worldwide HPC Consulting and Services for academic, government and commercial organizations (www.https://nag.com//hpc). Enquiries can be directed to NAG's HPC Consulting team through www.https://nag.com//contact_us.asp. HECToR is a Research Councils UK High End Computing Service.
The Numerical Algorithms Group (NAG is an Oxford, UK headquartered not-for-profit numerical software development organization founded nearly four decades ago that collaborates with world-leading researchers and practitioners in academia and industry. With offices in Manchester, Chicago, Tokyo and Taipei, and a worldwide distributor network, NAG provides high-quality computational software and high performance computing services to tens of thousands of users, from Global 500 companies, major learning academies, the world’s leading supercomputing centers, numerous independent software vendors and many others.
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