High-Performance Grid Computing for Cummins Vehicle Mission Simulation: Architecture and Applications

Nagesh Belludi; Joshua Receveur; Jeremy Raymond

doi:10.4271/2011-01-2268

This paper presents an extension of our earlier work on Cummins Vehicle Mission Simulation (VMS) software. Previously, we presented VMS as a Windows based analysis tool to simulate vehicle missions quickly and to gauge, communicate, and improve the value proposition of Cummins engines to customers. We have subsequently extended this VMS architecture to build a grid-computing platform to support high volume of simulation needs.

The building block of the grid-computing version of VMS is an executable file that consists of vehicle and engine simulation models compiled using Real Time Workshop. This executable file integrates MATLAB and Simulink with Java, XML, and JDBC technologies and interacts with the MySQL database. Our grid consists of a cluster of twenty Linux servers with quad-core processors. The Sun Grid Engine software suite that administers this cluster can batch-queue and execute 80 simulations concurrently.

The scale and computing power of this platform has enabled us to automate VMS software testing, perform complex analyses to better the product-to-customer fit of Cummins engines, and deploy optimization tools for improving vehicle performance and fuel efficiency.

This paper presents the hardware and software architecture of this high-performance grid-computing platform and application case studies.

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High-Performance Grid Computing for Cummins Vehicle Mission Simulation: Architecture and Applications 2011-01-2268

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