Parallelizing fundamental algorithms such as sorting on multi-core processors for EDA acceleration

Fundamental algorithms should be parallelized to accelerate EDA software on multi-core architecture. In this paper, we introduce scalable algorithms that have scalability on multi-cores. As an example, a sorting algorithm, called Map Sort, is presented. This algorithm uses a map from subsets of input data to intervals on data range. Experimental results show that, in comparison with quick sort on a single CPU, processing time of Map Sort is comparable on a CPU and three times faster on four CPUs.