Compress-and-conquer for optimal multicore computing

We propose a programming paradigm called compress-and-conquer (CC) that leads to optimal performance on multicore platforms. Given a multicore system of p cores and a problem of size n, the problem is first reduced to p smaller problems, each of which can be solved independently of the others (the compression phase). From the solutions to the p problems, a compressed version of the same problem of size O(p) is deduced and solved (the global phase). The solution to the original problem is then derived from the solution to the compressed problem together with the solutions of the smaller problems (the expansion phase). The CC paradigm reduces the complexity of multicore programming by allowing the best-known sequential algorithm for a problem to be used in each of the three phases. In this paper we apply the CC paradigm to a range of problems including scan, nested scan, difference equations, banded linear systems, and linear tridiagonal systems. The performance of CC programs is analy...

• Type: Conference
• Year: 2010
• Where: POPL
• Authors: Zhijing G. Mou, Hai Liu, Paul Hudak
• Keywords: CC Paradigm, Nested Scan, POPL 2010, Programming Languages, Smaller Problems