automatic data mapping for distributed-memory parallel computers
The performance of a program on a distributed-memory parallel computer depends on the algorithms employed, the structure and speed of the machine's communication network, and the ways in which data are distributed to the processors. This paper addresses the last of these concerns, the problem of data mapping . The paper describes and evaluated a system which automatically determines efficient ways of mapping data onto processors. The system is applicable and effective across a variety of architectures. Simulation results for machine with different interconnection schemes, including linear arrays, two-dimensional meshes, and the hypercubes, and measured running times for the CM-2 show that good data mapping often improves performance by at least 20\% and in some cases by more than a factor of two.
data map distributed parallel computation performance algorithm structure communication networks processor paper systems efficiency effect architecture simulation interconnect scheme mesh hypercube factor memorialized