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The second proposes a GPU-based engine for a general hardware/software design space exploration problem.

The first explores the possibility of using GPUs to speedup standard schedulability analysis problems. We demonstrate this idea via two detailed case studies. In this paper we explore the possibility of using commodity graphics processing units (GPUs) to accelerate such tasks that commonly arise in the electronic design automation (EDA) domain. As a result, they involve high running times even for mid-sized problems. Many system-level design tasks (e.g., high-level timing analysis, hardware/software partitioning and design space exploration) involve computational kernels that are intractable (usually NP-hard).