TY - GEN
T1 - Multi-dimensional dynamic loop scheduling algorithms
AU - Chronopoulos, Anthony T.
AU - Ni, Lionel M.
AU - Penmatsa, Satish
PY - 2007
Y1 - 2007
N2 - Distributed Computing Systems are a viable and less expensive alternative to parallel computers. However, a serious difficulty in concurrent programming of a distributed system is how to deal with scheduling and load balancing of such a system which may consist of heterogeneous computers. Loop scheduling schemes for parallel computers and computer clusters have been proposed in the past. A11 these schemes are one-dimensional because they partition only the outermost loop of a nested loop construct. In this work, we consider scheduling nested loops with many dimensions. We propose a new methodology which partitions many levels (or dimensions) of nested loops. These new schemes show superior performance over the existing schemes. We implement our new schemes on a network of computers and make performance comparisons with other existing schemes. We expect the new schemes to be particularly useful for multi-core systems because of the fine granularity of the generated tasks.
AB - Distributed Computing Systems are a viable and less expensive alternative to parallel computers. However, a serious difficulty in concurrent programming of a distributed system is how to deal with scheduling and load balancing of such a system which may consist of heterogeneous computers. Loop scheduling schemes for parallel computers and computer clusters have been proposed in the past. A11 these schemes are one-dimensional because they partition only the outermost loop of a nested loop construct. In this work, we consider scheduling nested loops with many dimensions. We propose a new methodology which partitions many levels (or dimensions) of nested loops. These new schemes show superior performance over the existing schemes. We implement our new schemes on a network of computers and make performance comparisons with other existing schemes. We expect the new schemes to be particularly useful for multi-core systems because of the fine granularity of the generated tasks.
UR - https://www.scopus.com/pages/publications/53349174605
U2 - 10.1109/CLUSTR.2007.4629237
DO - 10.1109/CLUSTR.2007.4629237
M3 - Conference Paper published in a book
AN - SCOPUS:53349174605
SN - 1424413885
SN - 9781424413881
T3 - Proceedings - IEEE International Conference on Cluster Computing, ICCC
SP - 241
EP - 248
BT - Proceedings - 2007 IEEE International Conference on Cluster Computing, CLUSTER 2007
T2 - 2007 IEEE International Conference on Cluster Computing, CLUSTER 2007
Y2 - 19 September 2007 through 20 September 2007
ER -