Gembench: A Platform For Collaborative Development Of Gpu Accelerated Embedded Markov Decision Systems

Markov Decision Processes (MDPs) provide a powerful decision making framework, which is increasingly being used in the design of Embedded Computing Systems (ECSs). This paper presents a detailed accounting of the use of MDPs in this context across research groups, including reference implementations, common datasets, file formats and platforms. Inspired by recent results showing the promising outlook of using embedded GPUs to solve MDPs on ECSs, we detail the many challenges that designers currently face and present GEMBench (the Gpu accelerated Embedded Mdp testBench) in order to facilitate experimental research in this area. GEMBench is targeted to a specific embedded GPU platform, the NVIDIA Jetson platform, and is designed for future retargetability to other platforms. GEMBench is a novel open source software package that is intended to run on the target platform. The package contains libraries of MDP solvers, parsers, datasets and reference solutions, which provide a comprehensive infrastructure for understanding trade-offs among existing embedded MDP techniques, and experimenting with novel techniques.