Parallel Simulation Language Research Articles

Performance evaluation of conservative algorithms in parallel simulation languages

Parallel discrete event simulation with conservative synchronization algorithms has been used as a high performance alternative to sequential simulation. In this paper, we examine the performance of a set of parallel conservative algorithms that have been implemented in the Maisie parallel simulation language. The algorithms include the asynchronous null message algorithm, the synchronous conditional event algorithm, and a new hybrid algorithm called Accelerated Null Message that combines features from the preceding algorithms. The performance of the algorithms is compared using the Ideal Simulation Protocol. This protocol provides a tight lower bound on the execution time of a simulation model on a given architecture and serves as a useful base to compare the synchronization overheads of the different algorithms. The performance of the algorithms is compared as a function of various model characteristics that include model connectivity, computation granularity, load balance, and lookahead.

Parallel languages for discrete-event simulation models

The growing complexity of simulation models has promoted the increased use of parallelism to speed turnaround of large, detailed models of heterogeneous system. The article presents an overview of parallel simulation languages and briefly describes the Parallel Simulation Environment for Complex systems (Parsec), developed at UCLA.

Parsec: a parallel simulation environment for complex systems

Design and development costs for extremely large systems could be significantly reduced if only there were efficient techniques for evaluating design alternatives and predicting their impact on overall system performance metrics. Due to the systems' analytical intractability, simulation is the most common performance evaluation technique for such systems. However, the long execution times needed for sequential simulation models often hampers evaluation. The slow speeds of sequential model execution have led to growing interest in the use of parallel execution for simulating large-scale systems. Widespread use of parallel simulation, however; has been significantly hindered by a lack of tools for integrating parallel model execution into the overall framework of system simulation. Another drawback to widespread use of simulations is the cost of model design and maintenance. The simulation environment the authors developed at UCLA attempts to address some of these issues. It consists of three primary components: a parallel simulation language called Parsec (parallel simulation environment for complex systems), its GUI, called Pave, and the portable runtime system that implements the simulation algorithms.

Design issues in parallel simulation languages

The authors address several key issues in designing languages for parallel discrete-event simulation and survey the state-of-the-art techniques aimed at solving these problems. Attention is given to issues that are specific to parallel simulation, e.g., the parallel synchronization schemes, or issues that have not previously been a problem for sequential simulation, e.g., termination. Various specialized PSLs (parallel simulation languages) may also have quite different design issues. The problem of achieving transparency is addressed. In particular it is observed that a major difficulty in achieving the design criteria is the overhead introduced by the methods for solving the problems considered. In some cases making the design criteria less constrained appears to be unavoidable. The authors also propose several useful high-level language constructs to facilitate modeling in order to have the simulation system deal with the low-level details transparently. They show that extending the capability of an existing programming language is the simplest available technique for designing a PSL.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>