The experience of GPU calculations at Lunarc

Details The experience of GPU calculations at Lunarc The experience of GPU calculations at Lunarc

Sep 2011

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011spie.8336e..34s&link_type=abstract

Integrated Modeling of Complex Optomechanical Systems. Edited by Andersen, Torben; Enmark, Anita. Proceedings of the SPIE, Volu

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To meet the ever increasing demand for computational speed and use of ever larger datasets, multi GPU instal- lations look very tempting. Lunarc and the Theoretical Astrophysics group at Lund Observatory collaborate on a pilot project to evaluate and utilize multi-GPU architectures for scientific calculations. Starting with a small workshop in 2009, continued investigations eventually lead to the procurement of the GPU-resource Timaeus, which is a four-node eight-GPU cluster with two Nvidia m2050 GPU-cards per node. The resource is housed within the larger cluster Platon and share disk-, network- and system resources with that cluster. The inaugu- ration of Timaeus coincided with the meeting "Computational Physics with GPUs" in November 2010, hosted by the Theoretical Astrophysics group at Lund Observatory. The meeting comprised of a two-day workshop on GPU-computing and a two-day science meeting on using GPUs as a tool for computational physics research, with a particular focus on astrophysics and computational biology. Today Timaeus is used by research groups from Lund, Stockholm and Lule in fields ranging from Astrophysics to Molecular Chemistry. We are investigating the use of GPUs with commercial software packages and user supplied MPI-enabled codes. Looking ahead, Lunarc will be installing a new cluster during the summer of 2011 which will have a small number of GPU-enabled nodes that will enable us to continue working with the combination of parallel codes and GPU-computing. It is clear that the combination of GPUs/CPUs is becoming an important part of high performance computing and here we will describe what has been done at Lunarc regarding GPU-computations and how we will continue to investigate the new and coming multi-GPU servers and how they can be utilized in our environment.

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