On synthesizing workloads emulating MPI applications

Evaluation of high performance parallel systems is a delicate issue, due to the difficulty of generating workloads that represent, with fidelity, those that will run on actual systems. In this paper we make an overview of the most usual methodologies used to generate workloads for performance evaluation purposes, focusing on the network: random traffic, patterns based on permutations, traces, execution-driven, etc. In order to fill the gap between purely synthetic and application- driven workloads, we present a set of pseudo-synthetic workloads that mimic applications behavior, emulating some widely-used implementations of MPI collectives and some communication patterns commonly used in scientific applications. This mimicry is done in terms of spatial distribution of messages as well as in the causal relationship among them. As an example of the proposed methodology, we use a subset of these workloads to confront tori and fat-trees.