References of "Plugaru, Valentin 50002873"
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See detailPerformance Evaluation of the XDEM framework on the OpenStack Cloud Computing Middleware
Besseron, Xavier UL; Plugaru, Valentin UL; Mahmoudi, Amir Houshang UL et al

in Proceedings of the Fourth International Conference on Parallel, Distributed, Grid and Cloud Computing for Engineering (2015, February)

As Cloud Computing services become ever more prominent, it appears necessary to assess the efficiency of these solutions. This paper presents a performance evaluation of the OpenStack Cloud Computing ... [more ▼]

As Cloud Computing services become ever more prominent, it appears necessary to assess the efficiency of these solutions. This paper presents a performance evaluation of the OpenStack Cloud Computing middleware using our XDEM application simulating the pyrolysis of biomass as a benchmark. We propose a systematic study based on a fully automated benchmarking framework to evaluate 3 different configurations: Native (i.e. no virtualization), OpenStack with KVM and XEN hypervisors. Our approach features the following advantages: real user application, the fair comparison using the same hardware, the large scale distributed execution, while fully automated and reproducible. Experiments has been run on two different clusters, using up to 432 cores. Results show a moderate overhead for sequential execution and a significant penalty for distributed execution under the Cloud middleware. The overhead on multiple nodes is between 10% and 30% for OpenStack/KVM and 30% and 60% for OpenStack/XEN. [less ▲]

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See detailVizBin - an application for reference-independent visualization and human-augmented binning of metagenomic data
Laczny, Cedric Christian UL; Sternal, Tomasz; Plugaru, Valentin UL et al

in Microbiome (2015)

Background Metagenomics is limited in its ability to link distinct microbial populations to genetic potential due to a current lack of representative isolate genome sequences. Reference-independent ... [more ▼]

Background Metagenomics is limited in its ability to link distinct microbial populations to genetic potential due to a current lack of representative isolate genome sequences. Reference-independent approaches, which exploit for example inherent genomic signatures for the clustering of metagenomic fragments (binning), offer the prospect to resolve and reconstruct population-level genomic complements without the need for prior knowledge. Results We present VizBin, a Java™-based application which offers efficient and intuitive reference-independent visualization of metagenomic datasets from single samples for subsequent human-in-the-loop inspection and binning. The method is based on nonlinear dimension reduction of genomic signatures and exploits the superior pattern recognition capabilities of the human eye-brain system for cluster identification and delineation. We demonstrate the general applicability of VizBin for the analysis of metagenomic sequence data by presenting results from two cellulolytic microbial communities and one human-borne microbial consortium. The superior performance of our application compared to other analogous metagenomic visualization and binning methods is also presented. Conclusions VizBin can be applied de novo for the visualization and subsequent binning of metagenomic datasets from single samples, and it can be used for the post hoc inspection and refinement of automatically generated bins. Due to its computational efficiency, it can be run on common desktop machines and enables the analysis of complex metagenomic datasets in a matter of minutes. The software implementation is available at https://claczny.github.io/VizBin under the BSD License (four-clause) and runs under Microsoft Windows™, Apple Mac OS X™ (10.7 to 10.10), and Linux. [less ▲]

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See detailPerformance Analysis of Cloud Environments on Top of Energy-Efficient Platforms Featuring Low Power Processors
Plugaru, Valentin UL; Varrette, Sébastien UL; Bouvry, Pascal UL

in Proc. of the 6th IEEE Intl. Conf. on Cloud Computing Technology and Science (CloudCom'14) (2014, December)

Energy efficiency remains a prevalent concern in the development of future HPC systems. Thus the next generations of supercomputers are foreseen to be developed as hybrid systems featuring traditional ... [more ▼]

Energy efficiency remains a prevalent concern in the development of future HPC systems. Thus the next generations of supercomputers are foreseen to be developed as hybrid systems featuring traditional processors, accelerators (such as GPGPUs) and/or low-power processor architectures (ARM, Intel Atom, etc.) primarily designed for the mobile and embedded de- vices market. Also, a confluence with the Cloud Computing (CC) paradigm is anticipated, driven by economic sustainability factors. However, the performance impact of running Cloud middleware on such crossbred platforms remains to be explored, especially on low power processors. In this context, this paper brings two main contributions: (1) the design and implementation of BACH, a framework able to execute automated performance evaluations of Cloud and HPC cluster environments; (2) the concrete validation of the framework for the evaluation of the modern OpenStack Infrastructure-as-a-Service (IaaS) middleware, deployed on a cutting-edge cluster based on ultra low power energy efficient ARM processors. The efficiency in itself is measured with synthetic HPC benchmarks: HPCC (incorporating the well known HPL), HPCG and real world applications from the bioinformatics domain - GROMACS and ABySS. The experimental evaluation revealed an average 24% performance drop in performance for compute-intensive tasks and 65.6% drop in communication capacity compared to the native environment without the IaaS solution, showing a non-negligible impact on the tested platform. To our knowledge, this is one of the first studies of this type, since deployment attempts of the OpenStack infrastructure on top of ARM platforms are in early stages, and are generally performed only for demonstration purposes. [less ▲]

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See detailHPC Performance and Energy-Efficiency of the OpenStack Cloud Middleware
Varrette, Sébastien UL; Plugaru, Valentin UL; Guzek, Mateusz UL et al

in Proc. of the 43rd Intl. Conf. on Parallel Processing (ICPP-2014), Heterogeneous and Unconventional Cluster Architectures and Applications Workshop (HUCAA'14) (2014, September)

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See detailEvaluating the HPC Performance and Energy-Efficiency of Intel and ARM-based systems with synthetic and bioinformatics workloads
Plugaru, Valentin UL; Varrette, Sébastien UL; Pinel, Frédéric UL et al

Report (2014)

The increasing demand for High Performance Computing (HPC) paired with the higher power requirements of the ever-faster systems has led to the search for both performant and more energy-efficient ... [more ▼]

The increasing demand for High Performance Computing (HPC) paired with the higher power requirements of the ever-faster systems has led to the search for both performant and more energy-efficient architectures. This article compares and contrasts the performance and energy efficiency of two modern, traditional Intel Xeon and low power ARM-based clusters, which are tested with the recently developed High Performance Conjugate Gradient (HPCG) benchmark and the ABySS, FASTA and MrBayes bioinformatics applications. We show a higher Performance per Watt valuation of the ARM cluster, and lower energy usage during the tests, which does not offset the much faster job completion rate obtained by the Intel cluster, making the latter more suitable for the considered workloads given the disparity in the performance results. [less ▲]

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See detailA Holistic Model of the Performance and the Energy-Efficiency of Hypervisors in an HPC Environment
Guzek, Mateusz UL; Varrette, Sébastien UL; Plugaru, Valentin UL et al

in Concurrency and Computation: Practice and Experience (2014)

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See detailHPC Performance and Energy-Efficiency of Xen, KVM and VMware Hypervisors
Varrette, Sébastien UL; Guzek, Mateusz UL; Plugaru, Valentin UL et al

in Proc. of the 25th Symposium on Computer Architecture and High Performance Computing (SBAC-PAD 2013) (2013, October)

With a growing concern on the considerable energy consumed by HPC platforms and data centers, research efforts are targeting green approaches with higher energy efficiency. In particular, virtualization ... [more ▼]

With a growing concern on the considerable energy consumed by HPC platforms and data centers, research efforts are targeting green approaches with higher energy efficiency. In particular, virtualization is emerging as the prominent approach to mutualize the energy consumed by a single server running multiple VMs instances. Even today, it remains unclear whether the overhead induced by virtualization and the corresponding hypervisor middleware suits an environment as high-demanding as an HPC platform. In this paper, we analyze from an HPC perspective the three most widespread virtualization frameworks, namely Xen, KVM, and VMware ESXi and compare them with a baseline environment running in native mode. We performed our experiments on the Grid’5000 platform by measuring the results of the reference HPL benchmark. Power measures were also performed in parallel to quantify the potential energy efficiency of the virtualized environments. In general, our study offers novel incentives toward in-house HPC platforms running without any virtualized frameworks. [less ▲]

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See detailPerformance tuning of applications for HPC systems employing Simulated Annealing optimization
Plugaru, Valentin UL; Georgatos, Fotis UL; Varrette, Sébastien UL et al

Report (2013)

Building fast software in an HPC environment raises great challenges as software used for simulation and modelling is generally complex and has many dependencies. Current approaches involve manual tuning ... [more ▼]

Building fast software in an HPC environment raises great challenges as software used for simulation and modelling is generally complex and has many dependencies. Current approaches involve manual tuning of compilation parameters in order to minimize the run time, based on a set of predefined defaults, but such an approach involves expert knowledge, is not scalable and can be very expensive in person-hours. In this paper we propose and develop a modular framework called POHPC that uses the Simulated Annealing meta-heuristic algorithm to automatically search for the optimal set of library options and compilation flags that can give the best execution time for a library-application pair on a selected hardware architecture. The framework can be used in modern HPC clusters using a variety of batch scheduling systems as execution backends for the optimization runs, and will discover optimal combinations as well as invalid sets of options and flags that result in failed builds or application crashes. We demonstrate the optimization of the FFTW library working in conjunction with the high- profile community codes GROMACS and QuantumESPRESSO, whereby the suitability of the technique is validated. [less ▲]

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See detailA Holistic Model of the Performance and the Energy-Efficiency of Hypervisors in an HPC Environment
Guzek, Mateusz UL; Varrette, Sébastien UL; Plugaru, Valentin UL et al

in Energy Efficiency in Large Scale Distributed Systems (2013)

Detailed reference viewed: 158 (7 UL)