Energy efficient parallel and distributed simulation

Abstract

New challenges and opportunities emerge as computing interacts with our surroundings in unprecedented ways. One of these challenges is the energy consumed by computations and communications. In large cloud-based computing systems, it is a major concern because it forms the largest proportion of the environmental and operational costs of data centers. In mobile systems, it directly impacts battery life. This work focuses on understanding and reducing power and energy consumption of the parallel and distributed execution of discrete event simulations, an area not extensively studied in the past. We first empirically characterize the energy consumption of widely used synchronization algorithms. Then a model and techniques are presented and exercised to create energy profile of a distributed simulation system. These demonstrate that distributed execution and synchronization can incur a significant energy and power overhead. To study and optimize the energy required for distributed execution, a property termed zero-energy synchronization is proposed. A zero-energy synchronization algorithm based on an oracle is presented, and a practical implementation is discussed. A more generic synchronization algorithm termed Low Energy YAWNS (LEY) is also proposed. LEY represents the first attempt to design a synchronization algorithm for energy efficiency and, in principle, can achieve zero-energy synchronization for a large class of distributed simulation applications. To employ the energy efficiency of specialized computing hardware platforms, recurrence relations for simulating G/G/1 queueing networks, directly implementable using library primitives, are proposed. In addition to optimizations and scalability they offer, the use of library primitives ease development and open up avenues for adapting the simulation for custom hardware. Composition of parallel prefix scans further improve the energy efficiency of the proposed recurrences and similar sequences of parallel prefix scans.