Portraying the behavior of parallel programs can be done in a variety of ways. One way is to generate a graphical display related to the program’s behavior so that a user can visualize what happens during the program’s execution. As an alternative to visualization, auralization can also be used to portray the behavior of parallel programs. This paper explores how sound can be used to depict different events that take place during a parallel program’s execution. In particular, the discussion is focused on dis@ibutedmemory parallel programs. Three mappings of execution behavior to sound were studied. The first mapping is related to process communication in a distributed-memory parallel program. The second mapping tracks the load balance of the processors of a system, In the third mapping, the flows-ofcontrol of the parallel processes are mapped to related sounds.

Debugging parallel programs using sound

A bibliography of over three hundred technical reports, journal and conference papers, and Ph.D. dissertations dealing with parallel and distributed debuggers. Treatments of programming environments, debugging methodology, and techniques for program analysis are included when a significant portion of the publication is devoted to factors influencing the design or implementation of debugging tools.

A bibliography of parallel debuggers, 1993 edition

This thesis addresses the problem of locating the source of performance bottlenecks in large-scale parallel and distributed applications. Performance monitoring creates a dilemma: identifying a bottleneck necessitates collecting detailed information, yet collecting data can be too expensive. Meanwhile, users are inundated with graphs and tables that require a performance expert to interpret. I have developed an approach to address both these problems by combining dynamic on-the-fly selection of what performance data to collect with decision support to assist users with the selection and presentation of performance data. The approach is called the $W\sp3$ Search Model. I have also developed a monitoring technique called Dynamic Instrumentation.
Applying the W$\sp3$ Search Model is an iterative process of refining the answers to three questions: why is the application performing poorly, where is the bottleneck, and when does it occur. To answer the why question, tests are conducted to identify the type of bottleneck (e.g., synchronization, I/O, or computation). Answering the where question isolates a performance bottleneck to specific resources used by the program (e.g., disk, synchronization variable, or procedure). Answering when a problem occurs, isolates a bottleneck to a specific phase of the program's execution.
Dynamic Instrumentation differs from traditional data collection because it defers selecting what data to collect until the program is running. This permits insertion and alteration of the instrumentation during program execution. Instrumentation to count and time events is inserted by dynamically modifying the binary program. These counters and timers are periodically sampled. Based on this intermediate data, changes are made in the instrumentation to further isolate the bottleneck.
I have built a prototype implementation of the W$\sp3$ Search Model and of Dynamic Instrumentation. The prototype runs on Thinking Machine's CM-5 and a network of workstations running PVM. In one study, the tools identified the bottlenecks in several real programs using two to three orders of magnitude less data than traditional techniques. In another study, Dynamic Instrumentation was used to monitor long running programs and introduced less than 10% perturbation. The W$\sp3$ Search Model and Dynamic Instrumentation are being incorporated into the Paradyn Performance Tools.

/pdf/finding-bottlenecks-in-large-scale-parallel-programs-1dpqxnxxjm.pdf

Finding bottlenecks in large-scale parallel programs

Portraying the behavior of parallel programs is useful in pro8ram debuming and performance tuning. For the most part, researchers have focused on finding ways to visualize what happens during a program's execution. As an alternative to visualization, auralization can also be used to portray the behavior of parallel programs. This paper investigates whether or not sound can be used effectively t o depict dzferent events that take place during a parallel proBram's execution. In particular, we focus this discussion on distributedmemory parallel programs. Three mappings of execution behavior to sound were studied. ?'he first mapping tracks the load balance of the processors of a system. In the second mapping, the jlows-of-control of the parallel processes are mapped to related sounds. The third mapping is related t o process communication in a distributed-memory parallel program.

http://ieeexplore.ieee.org/iel3/5006/13730/00633316.pdf

The Sounds of Parallel Programs

Developing robust techniques for visualizing the performance behavior of parallel programs that can scale in problem size and/or number of processors remains a challenge. We present several performance visualization techniques based on the context of data-parallel programming and execution that demonstrate good visual scalability properties. These techniques are a result of utilizing the structural and distribution semantics of data-parallel programs as well as sophisticated three-dimensional graphics. A categorization and examples of scalable performance visualizations are given for programs, written in Dataparallel C and pC++. >

Scalable performance visualization for data-parallel programs

The complexity of parallel programming has stimulated the development of a variety of debugging tools. This survey of recent research focuses on debugger visualization systems. The effectiveness of such systems is bounded by the degree to which their representations of run-time behavior correlate with the language structures used to incorporate parallelism, as well as the logical framework adopted by the programmer. Current visualization systems are compared with the conceptual models supported by parallel languages. Attention is drawn to the fact that debuggers are tied to specific models and that this association may restrict their usefulness and acceptability.

Models for visualization in parallel debuggers

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Models for visualization in parallel debuggers