Degree of parallelism

About: Degree of parallelism is a research topic. Over the lifetime, 1515 publications have been published within this topic receiving 25546 citations.

Orderings and partition of PDE computations for a fixed-size VLSI architecture

Abstract: The parallel iterative solution of systems arising from the finite element discretization of elliptic PDEs, is the problem considered here A red-black ordering is introduced to increase the degree of parallelism of the computation Space-time domain expansion techniques are used to partition the computation for a proposed fixed-size VLSI architecture

Dynamically Adapting the Degree of Parallelism with Reflexive Programs

Abstract: In this paper we present a new method for achieving a higher cost-efficiency on parallel computers We insert routines into a program which detect the amount of computational work without using problem-specific parameters and adapt the number of used CPUs at runtime under given speedup/efficiency constraints Several user-tunable strategies for selecting the number of processors are presented and compared The modularity of this approach and its application-independence permit a general use on parallel computers with a scalable degree of parallelism

Distributed/parallel traffic simulation for IVHS applications

Abstract: This paper presents two algorithms developed for a distributed, discretes-event, and object-oriented traffic simulation, such as the Raffle and Highway Objects for REsearch, Analysis, and Understanding (THOREAU) (McGurrin and Wang, 1991) and (Hsin and Wang, 1992). THOREAU was designed for the study and analysis of Intelligent Vehicle Highway Systems (IVHS) [1] applications. The purpose of using distributed processing for traffic simulation is to extend the scope which can be modeled at an individual vehicle behavior level, by significantly increasing execution speed. The first algorithm was derived to decompose a large traffic model into submodels distributed over a network of workstations, with a minimum amount of inter-processor interactions, and to achieve the highest degree of parallelism. The second algorithm is an improvement of the Floyd algorithm for finding shortest paths using submodel decomposition and node to are incidency to achieve a 10m/sup 3/- fold speed improvement using m distributed processors. Both algorithms are being implemented for IVHS-related applications in a new version of THOREAU.

Adaptive Methods for Irregular Parallel Discrete Event Simulation Workloads

Abstract: Parallel Discrete Event Simulations (PDES) running at large scales involve the coordination of billions of very fine grain events distributed across a large number of processes. At such large scales optimistic synchronization protocols, such as TimeWarp, allow for a high degree of parallelism between processes, but with the additional complexity of managing event rollback and cancellation. This can become especially problematic in models that exhibit imbalance resulting in low event efficiency, which increases the total amount of work required to run a simulation to completion. Managing this complexity becomes key to achieving a high degree of performance across a wide range of models. In this paper, we address this issue by analyzing the relationship between synchronization cost and event efficiency. We first look at how these two characteristics are coupled via the computation of Global Virtual Time (GVT). We then introduce dynamic load balancing, and show how, when combined with low overhead GVT computation, we can achieve higher efficiency with less synchronization cost. In doing so, we achieve up to 2x better performance on a variety of benchmarks and models of practical importance.