OMPT: An OpenMP Tools Application Programming Interface for Performance Analysis

Eichenberger, Alexandre E.; Mellor-Crummey, John; Schulz, Martin; Wong, M. W.; Copty, Nawal; Dietrich, Robert A.; Liu, Xu; Loh, Eugene; Lorenz, Daniel

doi:10.1007/978-3-642-40698-0_13

Cited by 79 publications

(37 citation statements)

References 6 publications

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“…We chose to implement Cilkprof using compiler instrumentation (e.g., [31,32]), but there are other strategies we could have used to examine the behavior of a computation, such as asynchronous sampling (e.g., [13]) and binary instrumentation (e.g., [6,9,29,30]). Although asynchronous sampling provides low-overhead solutions for some analytical tools, we do not know of a way to measure the span of a multithreaded Cilk computation by sampling.…”

Section: Related Workmentioning

confidence: 99%

The Cilkprof Scalability Profiler

Schardl¹,

Kuszmaul²,

Lee

et al. 2015

Proceedings of the 27th ACM Symposium on Parallelism in Algorithms and Architectures

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Cilkprof is a scalability profiler for multithreaded Cilk computations. Unlike its predecessor Cilkview, which analyzes only the whole-program scalability of a Cilk computation, Cilkprof collects work (serial running time) and span (critical-path length) data for each call site in the computation to assess how much each call site contributes to the overall work and span. Profiling work and span in this way enables a programmer to quickly diagnose scalability bottlenecks in a Cilk program. Despite the detail and quantity of information required to collect these measurements, Cilkprof runs with only constant asymptotic slowdown over the serial running time of the parallel computation.As an example of Cilkprof's usefulness, we used Cilkprof to diagnose a scalability bottleneck in an 1800-line parallel breadth-first search (PBFS) code. By examining Cilkprof's output in tandem with the source code, we were able to zero in on a call site within the PBFS routine that imposed a scalability bottleneck. A minor code modification then improved the parallelism of PBFS by a factor of 5. Using Cilkprof, it took us less than two hours to find and fix a scalability bug which had, until then, eluded us for months. This paper describes the Cilkprof algorithm and proves theoretically using an amortization argument that Cilkprof incurs only constant overhead compared with the application's native serial running time. Cilkprof was implemented by compiler instrumentation, that is, by modifying the LLVM compiler to insert instrumentation into user programs. On a suite of 16 application benchmarks, Cilkprof incurs a geometric-mean multiplicative overhead of only 1.9 and a maximum multiplicative overhead of only 7.4 compared with running the benchmarks without instrumentation.

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Section: Related Workmentioning

confidence: 99%

The Cilkprof Scalability Profiler

Schardl¹,

Kuszmaul²,

Lee

et al. 2015

Proceedings of the 27th ACM Symposium on Parallelism in Algorithms and Architectures

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“…other sources of non-determinism at scale. In this context, we will develop novel and highly-scalable distributed algorithms for shared-memory programming models, for example, exploiting the OpenMP tools API [9] to control thread schedules. By all means, the exploration space of alternative schedules is large, so we will investigate advanced heuristics that can significantly bound this search space.…”

Section: The Pruner Toolsetmentioning

confidence: 99%

Overcoming extreme-scale reproducibility challenges through a unified, targeted, and multilevel toolset

Ahn

Lee

Gopalakrishnan

et al. 2013

Proceedings of the 1st International Workshop on Software Engineering for High Performance Computing in Computational Science A

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Reproducibility, the ability to repeat program executions with the same numerical result or code behavior, is crucial for computational science and engineering applications. However, non-determinism in concurrency scheduling often hampers achieving this ability on high performance computing (HPC) systems. To aid in managing the adverse effects of non-determinism, prior work has provided techniques to achieve bit-precise reproducibility, but most of them focus only on small-scale parallelism. While scalable techniques recently emerged, they are disparate and target special purposes, e.g., single-schedule domains. On current systems with O(10 6 ) compute cores and future ones with O(10 9 ), any technique that does not embrace a unified, targeted, and multilevel approach will fall short of providing reproducibility. In this paper, we argue for a common toolset that embodies this approach, where programmers select and compose complementary tools and can effectively, yet scalably, analyze, control, and eliminate sources of non-determinism at scale. This allows users to gain reproducibility only to the levels demanded by specific code development needs. We present our research agenda and ongoing work toward this goal.

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“…Recently, a new OpenMP API standard for tools [14], called OMPT, has been proposed by the OpenMP Tools Working group. OMPT is currently being evaluated to be included in the OpenMP standard.…”

Section: Introductionmentioning

confidence: 99%

OpenMP Task Scheduling Analysis via OpenMP Runtime API and Tool Visualization

Qawasmeh

Malik

Chapman

2014

2014 IEEE International Parallel &Amp; Distributed Processing Symposium Workshops

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OpenMP tasks propose a new dimension of concurrency to cap irregular parallelism within applications. The addition of OpenMP tasks allows programmers to express concurrency at a high level of abstraction and makes the OpenMP runtime responsible about the burden of scheduling parallel execution. The ability to observe the performance of OpenMP task scheduling strategies portably across shared memory platforms has been a challenge due to the lack of performance interface standards in the runtime layer. In this paper, we exploit our proposed tasking extensions to the OpenMP Runtime API (ORA), Known as Collector APIs, for profiling task level parallelism. We describe the integration of these Collector APIs, implemented in the OpenUH compiler, into the TAU performance system. Our proposed task extensions are in line with the new interface specification called OMPT, which is currently under evaluation by the OpenMP community. We use this integration to analyze various OpenMP task scheduling strategies implemented in OpenUH. The capabilities of these scheduling strategies are evaluated with respect to exploiting data locality, maintaining load balance, and minimizing overhead costs. We present a comprehensive performance study of diverse OpenMP benchmarks, from the Barcelona OpenMP Test Suite, comparing different task pools (DEFAULT, SIMPLE, SIMPLE 2LEVEL, PUBLIC PRIVATE), task queues (DEQUE, FIFO, CFIFO, LIFO, INV DEQUE), and task queue storages (ARRAY, DYN ARRAY, LIST, LOCKLESS) on an AMD Opteron multicore system (48 cores total). Our results show that the benchmarks with similar characteristics exhibit the same behavior in terms of the performance of the applied scheduling strategies. Moreover, the task pool configuration, which controls the organization of task queues, was found to have the highest impact on performance.

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OMPT: An OpenMP Tools Application Programming Interface for Performance Analysis

Cited by 79 publications

References 6 publications

The Cilkprof Scalability Profiler

The Cilkprof Scalability Profiler

Overcoming extreme-scale reproducibility challenges through a unified, targeted, and multilevel toolset

OpenMP Task Scheduling Analysis via OpenMP Runtime API and Tool Visualization

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