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, Cédric 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 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 & Computation : Practice & Experience (2014)

Detailed reference viewed: 92 (26 UL)