Coarse Grained Parallel Algorithms

点击翻译按钮获取中文摘要

Various fields of research face barriers created by problems that are computationally hard and/or require processing of large amounts of data. For example, some computational biochemistry methods on protein or gene sequences can not be scaled up to data sets required for human health research because of performance problems. Parallel computing enables new research by increasing the size of solvable problems. In addition to fundamental parallel computing research, this project studies parallel algorithms for structure-based drug design and protein-protein interaction prediction that will enable new biochemistry research, as well as parallel algorithms for data cubes that will help enable the next generation of very large data warehouses.