Abstract
Significant manual design effort is required to implement a software routine on a GPU. This chapter presents an automated approach to partition a software application into kernels (which are executed in parallel) that can be run on the GPU. The software application should satisfy the constraint that it is executed multiple times on different data, and there exist no control dependencies between invocations.
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Gulati, K., Khatri, S.P. (2010). Automated Approach for Graphics Processor Based Software Acceleration. In: Hardware Acceleration of EDA Algorithms. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-0944-2_11
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DOI: https://doi.org/10.1007/978-1-4419-0944-2_11
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