Improving the performance of large interconnection networks using congestion-control mechanisms

Interconnection networks in current parallel systems do not only increase in size; their buffer capacity and number of source ports have increased as well. All these factors result in a significant rise of network congestion compared with their predecessors. Consequently, packet injection must be restricted in order to prevent throughput degradation at high loads. This work evaluates, via simulation, three congestion control mechanisms on adaptive cut-through torus networks, using two different deadlock-avoidance methods, under various synthetic traffic patterns. Workload is generated using bursts of data exchanges (instead of a Bernoulli process) to reflect the synchronized nature of data interchanges in parallel applications. Results show that large networks perform their best when most network resources are dedicated to in-transit traffic. Besides, local congestion-control mechanisms are nearly as effective as the more costly global ones for both uniform and nonuniform traffic patterns.