References of "Plugaru, Valentin 012136920C"
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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 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: 46 (6 UL)