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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)

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See detailInternet shopping with price sensitive discounts
Blazewicz, Jacek; Bouvry, Pascal UL; Kovalyov, Mikhael et al

in 4OR: a quarterly journal of operations research (2014), 12(1), 35-48

A customer would like to buy a given set of products in a given set of Internet shops. For each Internet shop, standard prices for the products are known as well as a concave increasing discounting ... [more ▼]

A customer would like to buy a given set of products in a given set of Internet shops. For each Internet shop, standard prices for the products are known as well as a concave increasing discounting function of total standard and delivery price. The problem is to buy all the required products at the minimum total discounted price. Computational complexity of various special cases is established. Properties of optimal solutions are proved and polynomial time and exponential time solution algorithms based on these properties are designed. Two heuristic algorithms are suggested and computationally tested. [less ▲]

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See detailProfiling Cloud Applications with Hardware Performance Counters
Kandalintsev, Alexandre; Lo Cigno, Renato; Kliazovich, Dzmitry UL et al

in International Conference on Information Networking (ICOIN), Phuket, Thailand, 2014 (2014)

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See detailNC-CELL: Network Coding-based Content Distribution in Cellular Networks for Cloud Applications
Fiandrino, Claudio UL; Kliazovich, Dzmitry UL; Bouvry, Pascal UL et al

in IEEE Global Communications Conference, Austin, TX, USA, 2014 (2014)

The popularity of cloud applications surged in the last years. Billions of mobile devices remain always connected. Location services, online games, social networking and navigation are a just few examples ... [more ▼]

The popularity of cloud applications surged in the last years. Billions of mobile devices remain always connected. Location services, online games, social networking and navigation are a just few examples of “always on” cloud applications in which the same or partially overlapping content is delivered to multiple users. In this paper, we propose a technique, called NCCELL, which uses network coding to foster content distribution in mobile cellular networks. Specifically, NC-CELL implements a software module at mobile base stations (or eNodeBs) which cans in transit traffic and looks for opportunities to code packets destined to different mobile users together. The proposed approach can significantly improve cell throughput and is particularly relevant for delay tolerant content distribution. [less ▲]

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See detailIt's Not a Bug, It'sa Feature: Wait-free Asynchronous Cellular Genetic Algorithm
Pinel, Frédéric UL; Dorronsoro, Bernabé UL; Bouvry, Pascal UL et al

in Wyrzykowski, Roman; Dongarra, Jack (Eds.) Parallel Processing and Applied Mathematics 10th International Conference, PPAM 2013 Warsaw, Poland, September 8–11, 2013 (2014)

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See detailDesign of an Energy Efficiency Model and Architecture for Cloud Management using Prediction Models
Nguyen, Anh Quan UL; Tantar, Alexandru-Adrian UL; Bouvry, Pascal UL et al

Scientific Conference (2013, December 18)

In this paper, we present a new energy efficiency model and architecture for cloud management based on a prediction model with Gaussian Mixture Models. The methodology relies on a distributed agent model ... [more ▼]

In this paper, we present a new energy efficiency model and architecture for cloud management based on a prediction model with Gaussian Mixture Models. The methodology relies on a distributed agent model and the validation will be performed on OpenStack. This paper intends to be a position paper, the implementation and experimental run will be conducted in future work. The design concept leverages the prediction model by providing a full architecture binding the resource demands, the predictions and the actual cloud environment (Openstack). The prediction analysis feeds the power-aware agents that run on the compute nodes in order to turn the nodes into sleep mode when the load state is low to reduce the energy consumption of the data center. [less ▲]

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See detailScalable, Low complexity, and fast greedy scheduling heuristics for highly heterogeneous distributed computing systems
Diaz, Cesar UL; Pecero, Johnatan UL; Bouvry, Pascal UL

in Journal of Supercomputing (2013)

Forheterogeneousdistributedcomputingsystems,importantdesignissues are scalability and system optimization. Given such systems, it is crucial to develop low computational complexity algorithms to schedule ... [more ▼]

Forheterogeneousdistributedcomputingsystems,importantdesignissues are scalability and system optimization. Given such systems, it is crucial to develop low computational complexity algorithms to schedule tasks in a manner that exploits the heterogeneity of the resources and applications. In this paper, we report and evalu- ate three scalable, and fast scheduling heuristics for highly heterogeneous distributed computing systems. We conduct a comprehensive performance evaluation study us- ing simulation. The benchmarking outlines the performance of the schedulers, rep- resenting scalability, makespan, flowtime, computational complexity, and memory utilization. The set of experimental results shows that our heuristics perform as good as the traditional approaches, for makespan and flowtime, while featuring lower com- plexity, lower running time, and lower used memory. The experimental results also detail the various scenarios under which certain algorithms excel and fail. [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 detailComparing the Performance and Power Usage of GPU and ARM Clusters for Map-Reduce
Delplace, V.; Manneback, P.; Pinel, Frédéric UL et al

in Proc. of the 3rd Intl. Conf. on Cloud and Green Computing (CGC'13) (2013, October)

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See detailHopfield neural network for simultaneous job scheduling and data replication in grids
Taheri, Javid; Zomaya, Albert; Bouvry, Pascal UL et al

in Future Generation Computer Systems (2013), 29(8), 1885-1900

This paper presents a novel heuristic approach, named JDS-HNN, to simultaneously schedule jobs and replicate data files to different entities of a grid system so that the overall makespan of executing all ... [more ▼]

This paper presents a novel heuristic approach, named JDS-HNN, to simultaneously schedule jobs and replicate data files to different entities of a grid system so that the overall makespan of executing all jobs as well as the overall delivery time of all data files to their dependent jobs is concurrently minimized. JDS-HNN is inspired by a natural distribution of a variety of stones among different jars and utilizes a Hopfield Neural Network in one of its optimization stages to achieve its goals. The performance of JDS-HNN has been measured by using several benchmarks varying from medium- to very-large-sized systems. JDS-HNN’s results are compared against the performance of other algorithms to show its superiority under different working conditions. These results also provide invaluable insights into scheduling and replicating dependent jobs and data files as well as their performance related issues for various grid environments. [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 detailPredictive Modeling in a VoIP System
Simionovici, Ana-Maria UL; Tantar, Alexandru; Bouvry, Pascal UL et al

in Journal of Telecommunications and Information Technology (2013), 4

An important problem one needs to deal with in a Voice over IP system is server overload. One way for pre- venting such problems is to rely on prediction techniques for the incoming traffic, namely as to ... [more ▼]

An important problem one needs to deal with in a Voice over IP system is server overload. One way for pre- venting such problems is to rely on prediction techniques for the incoming traffic, namely as to proactively scale the avail- able resources. Anticipating the computational load induced on processors by incoming requests can be used to optimize load distribution and resource allocation. In this study, the authors look at how the user profiles, peak hours or call pat- terns are shaped for a real system and, in a second step, at constructing a model that is capable of predicting trends. [less ▲]

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See detailDependency Analysis for Critical Infrastructure Security Modelling: A Case Study within the Grid'5000 Project
Schaberreiter, Thomas UL; Varrette, Sébastien UL; Bouvry, Pascal UL et al

in Proc. of the 3th IFIP Intl. SeCIHD'2013 Workshop, part of the 8th Intl. Conf. on Availability, Reliability and Security (ARES'13) (2013, September)

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See detailSystem Design and Implementation Decisions for ParaMoise Organizational Model
Guzek, Mateusz UL; Danoy, Grégoire UL; Bouvry, Pascal UL

in Proceedings of the 2013 Federated Conference on Computer Science and Information Systems (2013, September)

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See detailSavant: Automatic parallelization of a scheduling heuristic with machine learning
Pinel, Frédéric UL; Dorronsoro, Bernabé UL; Bouvry, Pascal UL et al

in Nature and Biologically Inspired Computing (NaBIC), 2013 World Congress on (2013, August 13)

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See detailEnergy Efficiency Metaheuristic Mechanism for Cloud Broker \\ in Multi-Cloud Computing
Nguyen, Anh Quan UL; Tantar, Alexandru-Adrian UL; Bouvry, Pascal UL et al

Scientific Conference (2013, July 13)

In this paper, we would like to present our view on an energy efficiency mechanism based on a metaheuristic algorithm for a cloud broker in multi-cloud computing. The following study is only a design ... [more ▼]

In this paper, we would like to present our view on an energy efficiency mechanism based on a metaheuristic algorithm for a cloud broker in multi-cloud computing. The following study is only a design concept and therefore this paper does not intend offering some established results. The metaheuristic based algorithm we envisage using needs to deal with the multiple objectives defined by the cloud users and the Cloud Service Providers (CSPs). The goal of the mechanism mainly focuses on energy efficiency while searching for a balance point that satisfies the objectives of both the cloud users and the CSPs. In our proposed concept, the designed mechanism needs to include a component to collect the resources that underutilized by the cloud users (in public or private cloud environment) and offers them back to the cloud broker for re-rent. [less ▲]

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See detailDynamic MixVoIP
Simionovici, Ana-Maria UL; Tantar, Alexandru; Bouvry, Pascal UL

Scientific Conference (2013, July)

Dynamic optimization based on incoming load analysis and prediction is considered to be an innovative approach in order to prevent the overload of the servers in a Voice over IP system. The ongoing ... [more ▼]

Dynamic optimization based on incoming load analysis and prediction is considered to be an innovative approach in order to prevent the overload of the servers in a Voice over IP system. The ongoing project is in an early stage of study and the followings are the current vision and concept regarding it. The information gathered by inspecting the real system of an IT company, MixVoIP, (probe server and sensors spread inside the cloud) and by analyzing the data provided by the predictive algorithm, will be used to optimize load distribution and resource allocation. The implementation in the real-life environment should lead to an improvement of the service offered but also to a sensible reduction of the associated carbon emissions, e.g. as a result of an improved load management, reduced idle CPU times or optimally exploited resources. [less ▲]

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See detailComputational Intelligence for Cloud Management Current Trends and Opportunities
Tantar, Alexandru-Adrian UL; Nguyen, Anh Quan UL; Bouvry, Pascal UL et al

Scientific Conference (2013, June 21)

The development of large scale data center and cloud computing optimization models led to a wide range of complex issues like scaling, operation cost and energy efficiency. Different approaches were ... [more ▼]

The development of large scale data center and cloud computing optimization models led to a wide range of complex issues like scaling, operation cost and energy efficiency. Different approaches were proposed to this end, including classical resource allocation heuristics, machine learning or stochastic optimization. No consensus exists but a trend towards using many-objective stochastic models became apparent over the past years. This work reviews in brief some of the more recent studies on cloud computing modeling and optimization, and points at notions on stability, convergence, definitions or results that could serve to analyze, respectively build accurate cloud computing models. A very brief discussion of simulation frameworks that include support for energy-aware components is also given. [less ▲]

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See detailParaMoise: Increasing Capabilities of Parallel Execution and Reorganization in an Organizational Model
Guzek, Mateusz UL; Danoy, Grégoire UL; Bouvry, Pascal UL

in Ito, Takayuki; Jonker, Catholijn; Gini, Maria (Eds.) et al Proceedings of the 12th International Conference on Autonomous Agents and Multiagent Systems, AAMAS'13 (2013, May 06)

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See detailPerformance Evaluation and Energy Efficiency of High-Density HPC Platforms Based on Intel, AMD and ARM Processors
Jarus, M.; Varrette, Sébastien UL; Oleksiak, A. et al

in Proc. of the Intl. Conf. on Energy Efficiency in Large Scale Distributed Systems (EE-LSDS'13) (2013, April)

Due to growth of energy consumption by HPC servers and data centers many research efforts aim at addressing the problem of energy efficiency. Hence, the use of low power processors such as Intel Atom and ... [more ▼]

Due to growth of energy consumption by HPC servers and data centers many research efforts aim at addressing the problem of energy efficiency. Hence, the use of low power processors such as Intel Atom and ARM Cortex have recently gained more interest. In this arti- cle, we compare performance and energy efficiency of cutting-edge high- density HPC platform enclosures featuring either very high-performing processors (such as Intel Core i7 or E7) yet having low power-efficiency, or the reverse i.e. energy efficient processors (such as Intel Atom, AMD Fusion or ARM Cortex A9) yet with limited computing capacity. Our objective was to quantify in a very pragmatic way these general pur- pose CPUs using a set of reference benchmarks and applications run in an HPC environment, the trade-off that could exist between computing and power efficiency. [less ▲]

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