A cost-efficient congestion management methodology for fat-trees using traffic pattern detection

Abstract

Interconnection networks have a great impact on the performance of parallel systems. These networks provide the communication mechanism and framework needed by parallel applications. One such important network is fat-tree. Selection functions were shown to have a great impact on the performance of fat-trees. Selection functions perform differently under certain traffic patterns. The stage and destination priority (SADP) selection function was shown to have better performance in case of uniform traffic while the stage and origin priority (SAOP) selection function was shown to perform better in case of hot-spot traffic. In this paper, we propose a cost-efficient congestion management mechanism for fat-trees that choose a certain selection function for certain traffic pattern. The mechanism has the ability to detect the current traffic pattern and switch to a certain selection function that is proved to give better performance under the detected traffic pattern. This directly decreases the congestion in the network. First, we analyze the hot-spot traffic in fat-trees if SADP selection function is used. We derive a condition for the existence of hot-spot traffic if SADP function is used. We give an implementation for detecting this condition. Once this condition is detected, the network is forced to switch to use the SAOP selection function. Then, we use the analysis of SAOP to derive a condition to detect that a non hot-spot traffic exists in the fat-tree. We give an implementation for detecting this condition. In turn, we switch back to the SADP selection function. We use synthetic workloads to show the accuracy of the proposed mechanism for detecting the hot-spot traffic in the network. We show that the proposed mechanism incurs a constant number of bits per physical link as an overhead. Finally, we compare the proposed mechanism with other techniques.