Assessing the Performance of OpenMP Programs on the Intel Xeon Phi

Schmidl, Dirk; Cramer, Tim; Wienke, Sandra; Terboven, Christian; Müller, Matthias S.

doi:10.1007/978-3-642-40047-6_56

Cited by 50 publications

(39 citation statements)

References 15 publications

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“…Schmidl et al [27] access the performance of OpenMP programs on the new Intel Xeon Phi coprocessor and the Intel Sandy Bridge (SNB). The first one, offering more than 60 cores, can act as an accelerator like in a GPU model or as a standalone SMP.…”

Section: Multi-core Cpu Programmingmentioning

confidence: 99%

“…The first one, offering more than 60 cores, can act as an accelerator like in a GPU model or as a standalone SMP. The work [27] studies the performance of Xeon Phi and SNB using kernels, benchmark codes and four real-world applications, achieving a speedup superior to 100 when compared to one core use on Xeon Phi. It shows that OpenMP programs can be portable for the state-of-the-art CPU with almost no modification when compared to GPU based approaches [27].…”

Section: Multi-core Cpu Programmingmentioning

confidence: 99%

“…The work [27] studies the performance of Xeon Phi and SNB using kernels, benchmark codes and four real-world applications, achieving a speedup superior to 100 when compared to one core use on Xeon Phi. It shows that OpenMP programs can be portable for the state-of-the-art CPU with almost no modification when compared to GPU based approaches [27]. Despite the described outstanding performance of Xeon Phi, this processor still is not widely in systems for most users of ClamAV.…”

Section: Multi-core Cpu Programmingmentioning

confidence: 99%

See 2 more Smart Citations

Endpoint Security in Networks: An OpenMP Approach for Increasing Malware Detection Speed

et al. 2017

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Increasingly sophisticated antivirus (AV) software and the growing amount and complexity of malware demand more processing power from personal computers, specifically from the central processor unit (CPU). This paper conducted performance tests with Clam AntiVirus (ClamAV) and improved its performance through parallel processing on multiple cores using the Open Multi-Processing (OpenMP) library. All the tests used the same dataset constituted of 1.33 GB of data distributed among 2766 files of different sizes. The new parallel version of ClamAV implemented in our work achieved an execution time around 62% lower than the original software version, reaching a speedup of 2.6 times faster. The main contribution of this work is to propose and implement a new version of the ClamAV antivirus using parallel processing with OpenMP, easily portable to a variety of hardware platforms and operating systems.

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Section: Multi-core Cpu Programmingmentioning

confidence: 99%

Section: Multi-core Cpu Programmingmentioning

confidence: 99%

Section: Multi-core Cpu Programmingmentioning

confidence: 99%

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Endpoint Security in Networks: An OpenMP Approach for Increasing Malware Detection Speed

et al. 2017

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“…Due to the foundations of Intel architecture, the coprocessor can be programmed in several different ways [32]. Here we introduce two different approaches, one using OpenMP and one using SCIF (Intel's Symmetric Communication Interface).…”

Section: Mtc On Intel Xeonmentioning

confidence: 99%

Many-Task Computing on Many-Core Architectures

Valero-Lara¹,

Nookala²,

Pelayo³

et al. 2016

SCPE

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Abstract. Many-Task Computing (MTC) is a common scenario for multiple parallel systems, such as cluster, grids, cloud and supercomputers, but it is not so popular in shared memory parallel processors. In this sense and given the spectacular growth in performance and in number of cores integrated in many-core architectures, the study of MTC on such architectures is becoming more and more relevant. In this paper, authors present what are those programming mechanisms to take advantages of such massively parallel features for the particular target of MTC. Also, the hardware features of the two dominant many-core platforms (NVIDIA's GPUs and Intel Xeon Phi) are also analyzed for our specific framework. Given the important differences in terms of hardware and software in our two many-core platforms, we have considered different strategies based on CUDA (for GPUs) and OpenMP (for Intel Xeon Phi). We carried out several test cases based on an appropriate and widely studied problem for benchmarking as matrix multiplication. Essentially, this study consisted of comparing the time consumed for computing in parallel several tasks one by one (the whole computational resources are used just to compute one task at a time) with the time consumed for computing in parallel the same set of tasks simultaneously (the whole computational resources are used for computing the set of tasks at very same time). Finally, we compared both software-hardware scenarios to identify the most relevant computer features in each of our many-core architectures.

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“…Intel Xeon Phi). A purely threaded parallelization can lead to several overheads such as increased management of structures and thread synchronization [37], false sharing [10] and resource sharing of a single program [29].…”

Section: Introductionmentioning

confidence: 99%

Invasive Compute Balancing for Applications with Shared and Hybrid Parallelization

Schreiber

Riesinger

Neckel

et al. 2014

Int J Parallel Prog

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Achieving high scalability with dynamically adaptive algorithms in high-performance computing (HPC) is a non-trivial task. The invasive paradigm using compute migration represents an efficient alternative to classical data migration approaches for such algorithms in HPC. We present a coredistribution scheduler which realizes the migration of computational power by distributing the cores depending on the requirements specified by one or more parallel program instances. We validate our approach with different benchmark suites for simulations with artificial workload as well as applications based on dynamically adaptive shallow water simulations, and investigate concurrently executed adaptivity parameter studies on realistic Tsunami simulations. The invasive approach results in significantly faster overall execution times and higher hardware utilization than alternative approaches. A dynamic resource management is therefore mandatory for a more efficient execution of scenarios similar to our simulations, e.g. several Tsunami simulations in urgent computing, to overcome strong scalability challenges in the area of HPC. The optimizations obtained by invasive migration of cores can be generalized to similar classes of algorithms with dynamic resource requirements.

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Assessing the Performance of OpenMP Programs on the Intel Xeon Phi

Cited by 50 publications

References 15 publications

Endpoint Security in Networks: An OpenMP Approach for Increasing Malware Detection Speed

Endpoint Security in Networks: An OpenMP Approach for Increasing Malware Detection Speed

Many-Task Computing on Many-Core Architectures

Invasive Compute Balancing for Applications with Shared and Hybrid Parallelization

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