Abstract
Graphics processing units (GPUs) have become increasingly popular accelerators in supercomputers, and this trend is likely to continue. With its disruptive architecture and a variety of optimization options, it is often desirable to understand the dynamics between potential application transformations and potential hardware features when designing future GPUs for scientific workloads. However, current codesign efforts have been limited to manual investigation of benchmarks on microarchitecture simulators, which is labor-intensive and time-consuming. As a result, system designers can explore only a small portion of the design space. In this paper, we propose SESH framework, a model-driven codesign framework for GPU, that is able to automatically search the design space by simultaneously exploring prospective application and hardware implementations and evaluate potential software-hardware interactions.
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Lee, J.H., Meng, J., Kim, H. (2014). SESH Framework: A Space Exploration Framework for GPU Application and Hardware Codesign. In: Jarvis, S., Wright, S., Hammond, S. (eds) High Performance Computing Systems. Performance Modeling, Benchmarking and Simulation. PMBS 2013. Lecture Notes in Computer Science(), vol 8551. Springer, Cham. https://doi.org/10.1007/978-3-319-10214-6_9
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DOI: https://doi.org/10.1007/978-3-319-10214-6_9
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