Implementing a GPU-Enhanced Cluster for Large-Scale Simulations

Robert Lucas, Gene Wagenbreth, Dan Davis
Information Sciences Institute, Univ. of So. Calif., Marina del Rey, California
The Interservice/Industry Training, Simulation & Education Conference (I/ITSEC), Vol. 2007, No. -1. (1 January 2007)


   title={Implementing a GPU-enhanced cluster for large-scale simulations},

   author={Lucas, R.F. and Wagenbreth, G. and Davis, D.M.},

   booktitle={The Interservice/Industry Training, Simulation & Education Conference (I/ITSEC)},






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The simulation community has often been hampered by constraints in computing: not enough resolution, not enough entities, not enough behavioral variants. Higher performance computers can ameliorate those constraints. The use of Linux Clusters is one path to higher performance; the use of Graphics Processing Units (GPU) as accelerators is another. Merging the two paths holds even more promise. The authors were the principal architects of a successful proposal to the High Performance Computing Modernization Program (HPCMP) for a new 512 CPU (1024 core), GPU-enhanced Linux Cluster for the Joint Forces Command’s Joint Experimentation Directorate (J9). In this paper, the basic theories underlying the use of GPUs as accelerators for intelligent agent, entity-level simulations are laid out, the previous research is surveyed and the ongoing efforts are outlined. The simulation needs of J9, the direction from HPCMP and the careful analysis of the intersection of these are explicitly discussed. The configuration of the cluster and the assumptions that led to the conclusion that GPUs might increase performance by a factor of two are carefully documented. The processes that led to that configuration, as delivered to JFCOM, will be specified and alternatives that were considered will be analyzed. Planning and implementation strategies are reviewed and justified. The presentation will then report in detail about the execution of the actual installation and implementation of the JSAF simulation on the cluster in August 2007. Issues, problems and solutions will all be reported objectively, as guides to the simulation community and as confirmation or rejection of early assumptions. Lessons learned and recommendations will be set out. Original performance projections will be compared to actual benchmarking results using LINPACK and simulation performance. Early observed operational capabilities of interest are proffered in detail herein.
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