The development of efficient parallel discrete event simulators is a
complicated task because of the large number of interrelated factors
affecting performance. This problem is made more difficult by the lack of
scalable representative models that can be used to analyze optimizations
and isolate bottlenecks. Towards this end, we propose the use of a Performance and Scalabilty
Analysis Framework
(PSAF) for parallel discrete event simulators. PSAF is built on a
platform-independent Workload Specification Language (WSL). WSL
is a language that represents simulation models using a set of fundamental
performance-critical parameters. For each simulator under study, a WSL
translator generates synthetic platform-specific simulation models that
conform to the performance and scalability characteristics specified by
the WSL description. Moreover, sets of portable simulation models that
explore the effects of the different parameters, individually or
collectively, on the execution performance can easily be constructed using
the Synthetic Workload Generator (SWG). SWG is a program that
automatically generates simulation workloads with different performance
properties. PSAF supports seamless integration of real models into the
workload specification. Thus, a benchmark with both real and
synthetically generated models can be built allowing for realistic and
thorough exploration of the performance space.
Currently, efforts are ongoing to bring out PSAF version 1.0 as soon as
possible. PSAF version 1.0 will be freely available sometime this
month. Check back here for details.
![[COLOR]](psaf.gif)
