Tuning message aggregation on high performance clusters for efficient parallel simulations

High performance clusters (HPCs) based on commodity hardware are becoming more and more popular in the parallel computing community. These new platforms offer a hardware capable of very low latency and very high throughput at an unbeatable cost, making them attractive for a large variety of parallel and distributed applications. With adequate communication software, HPCs have the potential to achieve a level of performance similar to massively parallel computers. However, for parallel applications that present a high communication/computation ratio, it is still essential to provide the lowest latency in order to minimize the communication overhead. In this paper, we are investigating message aggregation techniques to improve parallel simulations of fine-grain ATM communication network models. Even if message aggregation is a well-known solution for improving the communication performance of high latency interconnection networks, the complex interaction between message aggregation and the underlying communication software is often ignored. We show that message aggregation must carefully take into account the characteristics of the communication software to be efficient on an HPC. This methodology can be applied as a preliminary step to tune a message aggregation algorithm for a given combination of hardware architecture and communication software layer.