Performance visualization for parallel programs: task-based, object-oriented approach

Developing and analyzing the performance of concurrent programs on distributed memory concurrent systems is normally a challenging task. Recently, performance visualization gains its importance as a critical tool for programmers. Programmers can have an insight into the development of parallel programs through a performance visualization. Most of the visualization tool to date have been developed for ad-hoc environments in hardware and software, and therefore its lifetime is limited. Since, however, new architectures keep emerging and application domains for distributed memory concurrent computer systems keep growing, the visualization tool should be flexible enough to accommodate unknown future demands of users (eg. new performance perspectives, application-specific views and disparate trace record formats);The Concurrent Object-Oriented ParaGraph (COOPG) is a prototype, general-purpose performance visualization package developed using an object-oriented approach. An object-oriented approach, both in design and implementation, provides a mechanism to build a simple, flexible, effective, and extensible performance visualization tool. The salient features of the COOPG include its flexible adaptability to disparate trace record formats and the incremental extensibility for incorporating user\u27s special-purpose views

The Automated Instrumentation and Monitoring System (AIMS) reference manual

Whether a researcher is designing the 'next parallel programming paradigm,' another 'scalable multiprocessor' or investigating resource allocation algorithms for multiprocessors, a facility that enables parallel program execution to be captured and displayed is invaluable. Careful analysis of execution traces can help computer designers and software architects to uncover system behavior and to take advantage of specific application characteristics and hardware features. A software tool kit that facilitates performance evaluation of parallel applications on multiprocessors is described. The Automated Instrumentation and Monitoring System (AIMS) has four major software components: a source code instrumentor which automatically inserts active event recorders into the program's source code before compilation; a run time performance-monitoring library, which collects performance data; a trace file animation and analysis tool kit which reconstructs program execution from the trace file; and a trace post-processor which compensate for data collection overhead. Besides being used as prototype for developing new techniques for instrumenting, monitoring, and visualizing parallel program execution, AIMS is also being incorporated into the run-time environments of various hardware test beds to evaluate their impact on user productivity. Currently, AIMS instrumentors accept FORTRAN and C parallel programs written for Intel's NX operating system on the iPSC family of multi computers. A run-time performance-monitoring library for the iPSC/860 is included in this release. We plan to release monitors for other platforms (such as PVM and TMC's CM-5) in the near future. Performance data collected can be graphically displayed on workstations (e.g. Sun Sparc and SGI) supporting X-Windows (in particular, Xl IR5, Motif 1.1.3)

Visualizing the performance of parallel programs

Bibliography: pages 110-115.The performance analysis of parallel programs is a complex task, particularly if the program has to be efficient over a wide range of parallel machines. We have designed a performance analysis system called Chiron that uses scientific visualization techniques to guide and help the user in performance analysis activities. The aim of Chiron is to give the user full control over what section of the data he/she wants to investigate in detail. Chiron uses interactive three-dimensional graphics techniques to display large amounts of data in a compact and easy to understand/ conceptualize way. The system assists in the tracking of performance bottlenecks by showing data in 10 different views and allowing the user to interact with the data. In this thesis the design and implementation of Chiron are described, and its effectiveness illustrated by means of three case studies

Visualizing performance debugging

Abstract: "This article discusses visualizing performance of parallel and sequential computations using the Programming and Instrumentation Environment (PIE) as an example. First, the importance of being able to visualize the performance of a computation is demonstrated. Secondly, an easy guide to one way, the PIE way, of [t]his visualization process is presented. This is followed by examples of concrete uses of the environment. Finally, some of the pressing issues concerning measuring performance are discussed. Three issues are stressed in this article: 1. Visualization of program performance is necessary for fast, correct performance debugging. 2. PIE is a powerful and useful implementation for supporting visualization. It is also a dramatic teaching assistant in that it visually shows actions like forking, scheduling, etc. 3. PIE provides complete support for visualization. The system is aware of issues like program replay, suitably presenting performance data, compensation for perturbation by the measurement facility and support for multiple architectures and languages.