2,306 research outputs found
Parallel software tools at Langley Research Center
This document gives a brief overview of parallel software tools available on the Intel iPSC/860 parallel computer at Langley Research Center. It is intended to provide a source of information that is somewhat more concise than vendor-supplied material on the purpose and use of various tools. Each of the chapters on tools is organized in a similar manner covering an overview of the functionality, access information, how to effectively use the tool, observations about the tool and how it compares to similar software, known problems or shortfalls with the software, and reference documentation. It is primarily intended for users of the iPSC/860 at Langley Research Center and is appropriate for both the experienced and novice user
Performance Debugging and Tuning using an Instruction-Set Simulator
Instruction-set simulators allow programmers a detailed level of insight into,
and control over, the execution of a program, including parallel programs and
operating systems. In principle, instruction set simulation can model any
target computer and gather any statistic. Furthermore, such simulators are
usually portable, independent of compiler tools, and deterministic-allowing
bugs to be recreated or measurements repeated. Though often viewed as being
too slow for use as a general programming tool, in the last several years
their performance has improved considerably.
We describe SIMICS, an instruction set simulator of SPARC-based
multiprocessors developed at SICS, in its rôle as a general programming tool.
We discuss some of the benefits of using a tool such as SIMICS to support
various tasks in software engineering, including debugging, testing, analysis,
and performance tuning. We present in some detail two test cases, where we've
used SimICS to support analysis and performance tuning of two applications,
Penny and EQNTOTT. This work resulted in improved parallelism in, and
understanding of, Penny, as well as a performance improvement for EQNTOTT of
over a magnitude. We also present some early work on analyzing SPARC/Linux,
demonstrating the ability of tools like SimICS to analyze operating systems
Exploiting UML dynamic object modeling for the visualization of C++ programs
In this paper we present an approach to modeling and visualizing
the dynamic interactions among objects in a C++
application. We exploit UML diagrams to expressively visualize
both the static and dynamic properties of the application.
We make use of a class diagram and call graph of
the application to select the parts of the application to be
modeled, thereby reducing the number of objects and methods
under consideration with a concomitant reduction in the
cognitive burden on the user of our system. We use aspects
to insert probes into the application to enable profiling of the
interactions of objects and methods and we visualize these
interactions by providing sequence and communication diagrams
for the parts of the program under consideration. We
complement our static selectors with dynamic selectors that
enable the user to further filter objects and methods from
the sequence and communication diagrams, further enhancing
the cognitive economy of our system. A key feature of
our approach is the provision for dynamic interaction with
both the profiler and the application. Interaction with the
profiler enables filtering of methods and objects. Interaction
with the application enables the user to supply input to the
application to provide direction and enhance comprehension
or debugging
Using High-Rising Cities to Visualize Performance in Real-Time
For developers concerned with a performance drop or improvement in their
software, a profiler allows a developer to quickly search and identify
bottlenecks and leaks that consume much execution time. Non real-time profilers
analyze the history of already executed stack traces, while a real-time
profiler outputs the results concurrently with the execution of software, so
users can know the results instantaneously. However, a real-time profiler risks
providing overly large and complex outputs, which is difficult for developers
to quickly analyze. In this paper, we visualize the performance data from a
real-time profiler. We visualize program execution as a three-dimensional (3D)
city, representing the structure of the program as artifacts in a city (i.e.,
classes and packages expressed as buildings and districts) and their program
executions expressed as the fluctuating height of artifacts. Through two case
studies and using a prototype of our proposed visualization, we demonstrate how
our visualization can easily identify performance issues such as a memory leak
and compare performance changes between versions of a program. A demonstration
of the interactive features of our prototype is available at
https://youtu.be/eleVo19Hp4k.Comment: 10 pages, VISSOFT 2017, Artifact:
https://github.com/sefield/high-rising-city-artifac
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