A conservative approach to parallelizing the Sharks World simulation

Parallelizing a benchmark problem for parallel simulation, the Sharks World, is described. The described solution is conservative, in the sense that no state information is saved, and no 'rollbacks' occur. The used approach illustrates both the principal advantage and principal disadvantage of conservative parallel simulation. The advantage is that by exploiting lookahead an approach was found that dramatically improves the serial execution time, and also achieves excellent speedups. The disadvantage is that if the model rules are changed in such a way that the lookahead is destroyed, it is difficult to modify the solution to accommodate the changes

Development of An Empirical Approach to Building Domain-Specific Knowledge Applied to High-End Computing

This dissertation presents an empirical approach for building and storing knowledge about software engineering through human-subject research. It is based on running empirical studies in stages, where previously held hypotheses are supported or refuted in different contexts, and new hypotheses are generated. The approach is both mixed-methods based and opportunistic, and focuses on identifying a diverse set of potential sources for running studies. The output produced is an experience base which contains a set of these hypotheses, the empirical evidence which generated them, and the implications for practitioners and researchers. This experience base is contained in a software system which can be navigated by stakeholders to trace the "chain of evidence" of hypotheses as they evolve over time and across studies. This approach has been applied to the domain of high-end computing, to build knowledge related to programmer productivity. The methods include controlled experiments and quasi-experiments, case studies, observational studies, interviews, surveys, and focus groups. The results of these studies have been stored in a proof-of-concept system that implements the experience base

Semiannual report, 1 October 1990 - 31 March 1991

Research conducted at the Institute for Computer Applications in Science and Engineering in applied mathematics, numerical analysis, and computer science is summarized

Cumulative reports and publications through December 31, 1990

This document contains a complete list of ICASE reports. Since ICASE reports are intended to be preprints of articles that will appear in journals or conference proceedings, the published reference is included when it is available

Analytic Performance Models for Parallel Discrete Event Battlefield Simulation with Conservative Synchronization

This study investigated the development and use of analytic models for performance analysis of parallel discrete event battlefield simulation using conservative synchronization. A simulation architecture with layered application, simulation, and host machine services provided the model development basis. Simulation entities were modeled with set-theoretic definitions. Deterministic performance models using these definitions were developed for event prediction, scheduling, and execution in sequential battlefield simulation. The sequential model was expanded to include relative bounds for overhead factors introduced when the simulation is spatially decomposed for a parallel distributed memory machine. Comparison of sequential and parallel models instantiated for a simulation with uniform workload showed a potential for unbounded processor blocking. A synchronization algorithm modification to limit per-iteration blocking is shown theoretically to decrease finishing time. Modification results were demonstrated on a hypercube architecture. Demonstration showed that a sequential simulation requiring 60 seconds to run was limited to a best time of 30 seconds on four processors without algorithm modification. The time was improved to 17 seconds using the modification. A number of basic timing measurements also showed that event list operations on a sequential structure take significantly longer than interactive event prediction algorithms using simulation entities maintained in similar structures

Compiling Dataparallel C for efficient execution on tightly coupled multiprocessors

We describe a set of data flow techniques and code transformations that translate a single instruction stream, multiple data stream (SIMD) Dataparallel C program into a semantically equivalent single program, multiple data stream (SPMD) C program suitable for execution on shared memory multiprocessor computers, such as the Sequent Balance and Sequent Symmetry. The technique consists of identifying those areas in the original synchronous SIMD program where barrier synchronizations must be enforced to preserve the semantics, and then rewriting the. program as a loosely synchronous SPMD C program that includes calls to barrier synchronization library routines. The run-time model used by the translated program is also presented. We discuss a Dataparallel C compiler we have implemented using our proposed methodology. Finally, we present some performance results for our compiler, and we discuss techniques to improve these results