124,863 research outputs found

    ΠœΠ°Ρ‚Π΅ΠΌΠ°Ρ‚ΠΈΡ‡Π΅ΡΠΊΠΎΠ΅ ΠΌΠΎΠ΄Π΅Π»ΠΈΡ€ΠΎΠ²Π°Π½ΠΈΠ΅ Ρ€Π°Π±ΠΎΡ‚Ρ‹ ΡƒΠ΄Π°Ρ€Π½ΠΎΠ³ΠΎ Π³Π΅Π½Π΅Ρ€Π°Ρ‚ΠΎΡ€Π° с ΡƒΡ‡Π΅Ρ‚ΠΎΠΌ измСнСния скорости вращСния ΠΈ насыщСния ΠΌΠ°Π³Π½ΠΈΡ‚Π½ΠΎΠΉ Ρ†Π΅ΠΏΠΈ

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    We take a look at the performance analysis tools Vampir, Scalasca, Sun Performance Analyzer and the Intel Trace Analyzer and Collector, which provide execution analysis of parallel programs for optimization and scaling purposes. We investigate, from a novice user?s point of view, to what extent these tools support frequently used programming languages and constructs, discuss their performance impact and the insight these tools provide focusing on the instrumentation and program analysis. For this we analyzed codes currently used at the RWTH Aachen University: XNS, DROPS and HPL

    The Automated Instrumentation and Monitoring System (AIMS) reference manual

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    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)

    A Fast Causal Profiler for Task Parallel Programs

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    This paper proposes TASKPROF, a profiler that identifies parallelism bottlenecks in task parallel programs. It leverages the structure of a task parallel execution to perform fine-grained attribution of work to various parts of the program. TASKPROF's use of hardware performance counters to perform fine-grained measurements minimizes perturbation. TASKPROF's profile execution runs in parallel using multi-cores. TASKPROF's causal profile enables users to estimate improvements in parallelism when a region of code is optimized even when concrete optimizations are not yet known. We have used TASKPROF to isolate parallelism bottlenecks in twenty three applications that use the Intel Threading Building Blocks library. We have designed parallelization techniques in five applications to in- crease parallelism by an order of magnitude using TASKPROF. Our user study indicates that developers are able to isolate performance bottlenecks with ease using TASKPROF.Comment: 11 page
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