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Power Profiling of GeMTC Many Task Computing

Sean Wallace, Scott Krieder, Ioan Raicu
Illinois Institute of Technology, Chicago, IL, USA
Illinois Institute of Technology, Department of Computer Science, Technical Report, 2013
@article{wallace2013power,

   title={Power Profiling of GeMTC Many Task Computing},

   author={Wallace, Sean and Krieder, Scott and Raicu, Ioan},

   year={2013}

}

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GeMTC allows for Many Task Computing (MTC) workloads to run on hardware accelerators allowing for advantages that come from the many-core architecture. However, presently GeMTC is only written to take advantage of NVIDIA GPUs. Another such hardware accelerator, the Intel Xeon Phi, is also an excellent candidate for MTC workloads. Therefore, the first goal of this project will be to add support to GeMTC to allow it to run on Xeon Phi. While there has been plenty of research on power consumption of hardware accelerators, MTC workloads are a significantly understudied research area. MonEQ, a power profiling library, was primarily developed to measure power consumption of the IBM Blue Gene/Q supercomputer, but has lately evolved to also include profiling of both NVIDIA GPUs as well as the Intel Xeon Phi. As a second goal, this project seeks to profile real MTC workloads running on both NVIDIA GPUs as well as on the Xeon Phi.
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