Support for OpenMP tasks in Nanos v4

Teruel, Xavier; Martorell, Xavier; Durán, Alejandro; Ferrer, Roger; Ayguadé, Eduard

doi:10.1145/1321211.1321241

Cited by 43 publications

(34 citation statements)

References 3 publications

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“…The first prototype compiler and run time for OpenMP 3.0 tasks was an extension of Nanos Mercurium [24]. An evaluation of scheduling strategies for tasks using Nanos compared centralized breadth-first and fully-distributed depth-first work stealing schedulers [12].…”

Section: Related Workmentioning

confidence: 99%

Scheduling task parallelism on multi-socket multicore systems

Olivier

Porterfield

Wheeler

et al. 2011

Proceedings of the 1st International Workshop on Runtime and Operating Systems for Supercomputers

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The recent addition of task parallelism to the OpenMP shared memory API allows programmers to express concurrency at a high level of abstraction and places the burden of scheduling parallel execution on the OpenMP run time system. This is a welcome development for scientific computing as supercomputer nodes grow "fatter" with multicore and manycore processors. But efficient scheduling of tasks on modern multi-socket multicore shared memory systems requires careful consideration of an increasingly complex memory hierarchy, including shared caches and NUMA characteristics. In this paper, we propose a hierarchical scheduling strategy that leverages different methods at different levels of the hierarchy. By allowing one thread to steal work on behalf of all of the threads within a single chip that share a cache, our scheduler limits the number of costly remote steals. For cores on the same chip, a shared LIFO queue allows exploitation of cache locality between sibling tasks as well between a parent task and its newly created child tasks.We extended the open-source Qthreads threading library to implement our scheduler, accepting OpenMP programs through the ROSE compiler.We also present a comprehensive performance study of diverse OpenMP task parallel benchmarks, comparing seven different task parallel run time scheduler implementations on current generation multi-socket multicore systems: our hierarchical work stealing scheduler, a fully-distributed work stealing scheduler, a centralized scheduler, and LIFO and FIFO versions of the original Qthreads fullydistributed scheduler. In addition, we compare our results against OpenMP implementations from Intel and GCC. Hierarchical scheduling in Qthreads is competitive on all benchmarks. On several benchmarks, hierarchical scheduling in Qthreads demonstrates speedup and absolute performance superior to both the Intel and GCC OpenMP run time systems.

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Section: Related Workmentioning

confidence: 99%

Scheduling task parallelism on multi-socket multicore systems

Olivier

Porterfield

Wheeler

et al. 2011

Proceedings of the 1st International Workshop on Runtime and Operating Systems for Supercomputers

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“…The last 3 originated from the Cilk benchmarks [14]. The current task definition has been evaluated with some of these benchmarks, which have been rewritten to adopt the new syntax [15], [16], [17], [18].…”

Section: Related Workmentioning

confidence: 99%

Barcelona OpenMP Tasks Suite: A Set of Benchmarks Targeting the Exploitation of Task Parallelism in OpenMP

Durán

Teruel

Ferrer

et al. 2009

2009 International Conference on Parallel Processing

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231

126

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Abstract-Traditional parallel applications have exploited regular parallelism, based on parallel loops. Only a few applications exploit sections parallelism. With the release of the new OpenMP specification (3.0), this programming model supports tasking. Parallel tasks allow the exploitation of irregular parallelism, but there is a lack of benchmarks exploiting tasks in OpenMP.With the current (and projected) multicore architectures that offer many more alternatives to execute parallel applications than traditional SMP machines, this kind of parallelism is increasingly important. And so, the need to have some set of benchmarks to evaluate it.In this paper, we motivate the need of having such a benchmarks suite, for irregular and/or recursive task parallelism. We present our proposal, the Barcelona OpenMP Tasks Suite (BOTS), with a set of applications exploiting regular and irregular parallelism, based on tasks.We present an overall evaluation of the BOTS benchmarks in an Altix system and we discuss some of the different experiments that can be done with the different compilation and runtime alternatives of the benchmarks.

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“…As stated earlier, we implement our ideas in OmpSs [14] and Nanos [40]. We perform our experiments in the Marenostrum supercomputer [3].…”

Section: Discussionmentioning

confidence: 99%

A Runtime Heuristic to Selectively Replicate Tasks for Application-Specific Reliability Targets

Subaşi

Yalcin

Zyulkyarov

et al. 2016

2016 IEEE International Conference on Cluster Computing (CLUSTER)

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Abstract-In this paper we propose a runtime-based selective task replication technique for task-parallel high performance computing applications. Our selective task replication technique is automatic and does not require modification/recompilation of OS, compiler or application code. Our heuristic, we call App FIT, selects tasks to replicate such that the specified reliability target for an application is achieved. In our experimental evaluation, we show that App FIT selective replication heuristic is low-overhead and highly scalable. In addition, results indicate that complete task replication is overkill for achieving reliability targets. We show that with App FIT, we can tolerate pessimistic exascale error rates with only 53% of the tasks being replicated.

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Support for OpenMP tasks in Nanos v4

Cited by 43 publications

References 3 publications

Scheduling task parallelism on multi-socket multicore systems

Scheduling task parallelism on multi-socket multicore systems

Barcelona OpenMP Tasks Suite: A Set of Benchmarks Targeting the Exploitation of Task Parallelism in OpenMP

A Runtime Heuristic to Selectively Replicate Tasks for Application-Specific Reliability Targets

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