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In this paper, we address the management of Data Centers (DCs) by considering their optimal integration with the electrical, thermal, and IT (Information Technology) networks helping them to meet sustainability objectives and gain primary energy savings. Innovative scenarios are defined for exploiting the DCs electrical, thermal, and workload flexibility as a commodity and Information and Communication Technologies (ICT) are proposed and used as enablers for the scenarios’ implementation. The technology and scenarios were evaluated in the context of two operational DCs: a micro DC in Poznan which has on-site renewable sources and a DC in Point Saint Martin. The test cases’ results validate the possibility of using renewable energy sources (RES) for exploiting DCs’ energy flexibility and the potential of combining IT load migration with the availability of RES to increase the amount of energy flexibility by finding a trade-off between the flexibility level, IT load Quality of Service (QoS), and the RES production level. Moreover, the experiments conducted show that the DCs can successfully adapt their thermal energy profile for heat re-use as well as the combined electrical and thermal energy profiles to match specific flexibility requests.
Tudor Cioara; Marcel Antal; Claudia (Pop); Ionut Anghel; Massimo Bertoncini; Diego Arnone; Marilena Lazzaro; Marzia Mammina; Terpsichori-Helen Velivassaki; Artemis Voulkidis; Yoann Ricordel; Nicolas Sainthérant; Ariel Oleksiak; Wojciech Piatek. Data Centers Optimized Integration with Multi-Energy Grids: Test Cases and Results in Operational Environment. Sustainability 2020, 12, 9893 .
AMA StyleTudor Cioara, Marcel Antal, Claudia (Pop), Ionut Anghel, Massimo Bertoncini, Diego Arnone, Marilena Lazzaro, Marzia Mammina, Terpsichori-Helen Velivassaki, Artemis Voulkidis, Yoann Ricordel, Nicolas Sainthérant, Ariel Oleksiak, Wojciech Piatek. Data Centers Optimized Integration with Multi-Energy Grids: Test Cases and Results in Operational Environment. Sustainability. 2020; 12 (23):9893.
Chicago/Turabian StyleTudor Cioara; Marcel Antal; Claudia (Pop); Ionut Anghel; Massimo Bertoncini; Diego Arnone; Marilena Lazzaro; Marzia Mammina; Terpsichori-Helen Velivassaki; Artemis Voulkidis; Yoann Ricordel; Nicolas Sainthérant; Ariel Oleksiak; Wojciech Piatek. 2020. "Data Centers Optimized Integration with Multi-Energy Grids: Test Cases and Results in Operational Environment." Sustainability 12, no. 23: 9893.
Rapid growth of demand for remote computational power, along with high energy costs and infrastructure limits, has led to treating power usage as a primary constraint in data centers. Especially, recent challenges related to development of exascale systems or autonomous edge systems require tools that will limit power usage and energy consumption. This paper presents a power capping method that allows operators to quickly adjust the power usage to external conditions and, at the same time, to reduce energy consumption and negative impact on performance of applications. We propose an optimization model and both heuristic and exact methods to solve this problem. We present an evaluation of power capping approaches supported by results of application benchmarks and experiments performed on new heterogeneous servers.
Tomasz Ciesielczyk; Alberto Cabrera; Ariel Oleksiak; Wojciech Piątek; Grzegorz Waligóra; Francisco Almeida; Vicente Blanco. An approach to reduce energy consumption and performance losses on heterogeneous servers using power capping. Journal of Scheduling 2020, 1 -17.
AMA StyleTomasz Ciesielczyk, Alberto Cabrera, Ariel Oleksiak, Wojciech Piątek, Grzegorz Waligóra, Francisco Almeida, Vicente Blanco. An approach to reduce energy consumption and performance losses on heterogeneous servers using power capping. Journal of Scheduling. 2020; ():1-17.
Chicago/Turabian StyleTomasz Ciesielczyk; Alberto Cabrera; Ariel Oleksiak; Wojciech Piątek; Grzegorz Waligóra; Francisco Almeida; Vicente Blanco. 2020. "An approach to reduce energy consumption and performance losses on heterogeneous servers using power capping." Journal of Scheduling , no. : 1-17.
This paper addresses the problem of data centers’ cost efficiency considering the potential of reusing the generated heat in district heating networks. We started by analyzing the requirements and heat reuse potential of a high performance computing data center and then we had defined a heat reuse model which simulates the thermodynamic processes from the server room. This allows estimating by means of Computational Fluid Dynamics simulations the temperature of the hot air recovered by the heat pumps from the server room allowing them to operate more efficiently. To address the time and space complexity at run-time we have defined a Multi-Layer Perceptron neural network infrastructure to predict the hot air temperature distribution in the server room from the training data generated by means of simulations. For testing purposes, we have modeled a virtual server room having a volume of 48 m3 and two typical 42U racks. The results show that using our model the heat distribution in the server room can be predicted with an error less than 1 °C allowing data centers to accurately estimate in advance the amount of waste heat to be reused and the efficiency of heat pump operation.
Claudia Antal; Tudor Cioara; Ionut Anghel; Radoslaw Gorzenski; Radoslaw Januszewski; Ariel Oleksiak; Wojciech Piatek; Claudia Pop; Ioan Salomie; Wojciech Szeliga. Reuse of Data Center Waste Heat in Nearby Neighborhoods: A Neural Networks-Based Prediction Model. Energies 2019, 12, 814 .
AMA StyleClaudia Antal, Tudor Cioara, Ionut Anghel, Radoslaw Gorzenski, Radoslaw Januszewski, Ariel Oleksiak, Wojciech Piatek, Claudia Pop, Ioan Salomie, Wojciech Szeliga. Reuse of Data Center Waste Heat in Nearby Neighborhoods: A Neural Networks-Based Prediction Model. Energies. 2019; 12 (5):814.
Chicago/Turabian StyleClaudia Antal; Tudor Cioara; Ionut Anghel; Radoslaw Gorzenski; Radoslaw Januszewski; Ariel Oleksiak; Wojciech Piatek; Claudia Pop; Ioan Salomie; Wojciech Szeliga. 2019. "Reuse of Data Center Waste Heat in Nearby Neighborhoods: A Neural Networks-Based Prediction Model." Energies 12, no. 5: 814.
The Modular Microserver Datacentre (M2DC) project targets the development of a new class of energy-efficient TCO-optimized appliances with built-in efficiency and dependability enhancements. The appliances will be easy to integrate with a broad ecosystem of management software and fully software defined to enable optimization for a variety of future demanding applications in a cost-effective way. The highly flexible M2DC server platform will enable customization and smooth adaptation to various types of applications, while advanced management strategies and system efficiency enhancements (SEE) will be used to improve energy efficiency, performance, security, and reliability. Data center capable abstraction of the underlying heterogeneity of the server is provided by an OpenStack-based middleware. In this chapter, we focus in particular on the architecture of the server platform including a dedicated high-speed, low latency communication infrastructure, give a short introduction into the software stack including thermal management strategies, and provide an overview of the targeted applications.
Ariel Oleksiak; Michal Kierzynka; Wojciech Piatek; Micha Vor Dem Berge; Wolfgang Christmann; Stefan Krupop; Mario Porrmann; Jens Hagemeyer; René Griessl; Meysam Peykanu; Lennart Tigges; Sven Rosinger; Daniel Schlitt; Christian Pieper; Udo Janssen; Holm Rauchfuss; Giovanni Agosta; Alessandro Barenghi; Carlo Brandolese; William Fornaciari; Gerardo Pelosi; Joao Pita Costa; Mariano Cecowski; Robert Plestenjak; Justin Cinkelj; Loïc Cudennec; Thierry Goubier; Jean-Marc Philippe; Chris Adeniyi-Jones; Javier Setoain; Luca Ceva. M2DC—A Novel Heterogeneous Hyperscale Microserver Platform. Hardware Accelerators in Data Centers 2018, 109 -128.
AMA StyleAriel Oleksiak, Michal Kierzynka, Wojciech Piatek, Micha Vor Dem Berge, Wolfgang Christmann, Stefan Krupop, Mario Porrmann, Jens Hagemeyer, René Griessl, Meysam Peykanu, Lennart Tigges, Sven Rosinger, Daniel Schlitt, Christian Pieper, Udo Janssen, Holm Rauchfuss, Giovanni Agosta, Alessandro Barenghi, Carlo Brandolese, William Fornaciari, Gerardo Pelosi, Joao Pita Costa, Mariano Cecowski, Robert Plestenjak, Justin Cinkelj, Loïc Cudennec, Thierry Goubier, Jean-Marc Philippe, Chris Adeniyi-Jones, Javier Setoain, Luca Ceva. M2DC—A Novel Heterogeneous Hyperscale Microserver Platform. Hardware Accelerators in Data Centers. 2018; ():109-128.
Chicago/Turabian StyleAriel Oleksiak; Michal Kierzynka; Wojciech Piatek; Micha Vor Dem Berge; Wolfgang Christmann; Stefan Krupop; Mario Porrmann; Jens Hagemeyer; René Griessl; Meysam Peykanu; Lennart Tigges; Sven Rosinger; Daniel Schlitt; Christian Pieper; Udo Janssen; Holm Rauchfuss; Giovanni Agosta; Alessandro Barenghi; Carlo Brandolese; William Fornaciari; Gerardo Pelosi; Joao Pita Costa; Mariano Cecowski; Robert Plestenjak; Justin Cinkelj; Loïc Cudennec; Thierry Goubier; Jean-Marc Philippe; Chris Adeniyi-Jones; Javier Setoain; Luca Ceva. 2018. "M2DC—A Novel Heterogeneous Hyperscale Microserver Platform." Hardware Accelerators in Data Centers , no. : 109-128.
Ariel Oleksiak; Tomasz Ciesielczyk; Michal Kierzynka; Wojciech Piątek. Minimising energy costs of data centers using high dense heterogeneous systems and intelligent resource management. Proceedings of the Ninth International Conference on Tangible, Embedded, and Embodied Interaction 2018, 1 .
AMA StyleAriel Oleksiak, Tomasz Ciesielczyk, Michal Kierzynka, Wojciech Piątek. Minimising energy costs of data centers using high dense heterogeneous systems and intelligent resource management. Proceedings of the Ninth International Conference on Tangible, Embedded, and Embodied Interaction. 2018; ():1.
Chicago/Turabian StyleAriel Oleksiak; Tomasz Ciesielczyk; Michal Kierzynka; Wojciech Piątek. 2018. "Minimising energy costs of data centers using high dense heterogeneous systems and intelligent resource management." Proceedings of the Ninth International Conference on Tangible, Embedded, and Embodied Interaction , no. : 1.
Francisco Almeida; Marcos D. Assunção; Jorge Barbosa; Vicente Blanco; Ivona Brandic; Georges Da Costa; Manuel F. Dolz; Anne C. Elster; Mateusz Jarus; Helen D. Karatza; Laurent Lefèvre; Ilias Mavridis; Ariel Oleksiak; Anne-Cécile Orgerie; Jean-Marc Pierson. Energy monitoring as an essential building block towards sustainable ultrascale systems. Sustainable Computing: Informatics and Systems 2018, 17, 27 -42.
AMA StyleFrancisco Almeida, Marcos D. Assunção, Jorge Barbosa, Vicente Blanco, Ivona Brandic, Georges Da Costa, Manuel F. Dolz, Anne C. Elster, Mateusz Jarus, Helen D. Karatza, Laurent Lefèvre, Ilias Mavridis, Ariel Oleksiak, Anne-Cécile Orgerie, Jean-Marc Pierson. Energy monitoring as an essential building block towards sustainable ultrascale systems. Sustainable Computing: Informatics and Systems. 2018; 17 ():27-42.
Chicago/Turabian StyleFrancisco Almeida; Marcos D. Assunção; Jorge Barbosa; Vicente Blanco; Ivona Brandic; Georges Da Costa; Manuel F. Dolz; Anne C. Elster; Mateusz Jarus; Helen D. Karatza; Laurent Lefèvre; Ilias Mavridis; Ariel Oleksiak; Anne-Cécile Orgerie; Jean-Marc Pierson. 2018. "Energy monitoring as an essential building block towards sustainable ultrascale systems." Sustainable Computing: Informatics and Systems 17, no. : 27-42.
Ariel Oleksiak; Michal Kierzynka; Wojciech Piatek; Giovanni Agosta; Alessandro Barenghi; Carlo Brandolese; William Fornaciari; Gerardo Pelosi; Mariano Cecowski; Robert Plestenjak; Justin Činkelj; Mario Porrmann; Jens Hagemeyer; René Griessl; Jan Lachmair; Meysam Peykanu; Lennart Tigges; Micha Vor Dem Berge; Wolfgang Christmann; Stefan Krupop; Alexandre Carbon; Loïc Cudennec; Thierry Goubier; Jean-Marc Philippe; Sven Rosinger; Daniel Schlitt; Christian Pieper; Chris Adeniyi-Jones; Javier Setoain; Luca Ceva; Udo Janssen. M2DC – Modular Microserver DataCentre with heterogeneous hardware. Microprocessors and Microsystems 2017, 52, 117 -130.
AMA StyleAriel Oleksiak, Michal Kierzynka, Wojciech Piatek, Giovanni Agosta, Alessandro Barenghi, Carlo Brandolese, William Fornaciari, Gerardo Pelosi, Mariano Cecowski, Robert Plestenjak, Justin Činkelj, Mario Porrmann, Jens Hagemeyer, René Griessl, Jan Lachmair, Meysam Peykanu, Lennart Tigges, Micha Vor Dem Berge, Wolfgang Christmann, Stefan Krupop, Alexandre Carbon, Loïc Cudennec, Thierry Goubier, Jean-Marc Philippe, Sven Rosinger, Daniel Schlitt, Christian Pieper, Chris Adeniyi-Jones, Javier Setoain, Luca Ceva, Udo Janssen. M2DC – Modular Microserver DataCentre with heterogeneous hardware. Microprocessors and Microsystems. 2017; 52 ():117-130.
Chicago/Turabian StyleAriel Oleksiak; Michal Kierzynka; Wojciech Piatek; Giovanni Agosta; Alessandro Barenghi; Carlo Brandolese; William Fornaciari; Gerardo Pelosi; Mariano Cecowski; Robert Plestenjak; Justin Činkelj; Mario Porrmann; Jens Hagemeyer; René Griessl; Jan Lachmair; Meysam Peykanu; Lennart Tigges; Micha Vor Dem Berge; Wolfgang Christmann; Stefan Krupop; Alexandre Carbon; Loïc Cudennec; Thierry Goubier; Jean-Marc Philippe; Sven Rosinger; Daniel Schlitt; Christian Pieper; Chris Adeniyi-Jones; Javier Setoain; Luca Ceva; Udo Janssen. 2017. "M2DC – Modular Microserver DataCentre with heterogeneous hardware." Microprocessors and Microsystems 52, no. : 117-130.
The environmental protection is a dominant concern for all types of industries, organizations, and governments. In this regard, the reduction of the energy consumption is substantial in bringing down the CO2 gas emission, which is considered as an important factor causing global warming. The e-infrastructure service providers, such as National Research and Education Networks or National Grid Initiatives have crucial role in the context of energy awareness because the energy consumption of the networking, data, and computational infrastructures keeps increasing exponentially over the time. In addition to this, scientific gateways and cloud services are becoming more significant to tackle scientific and societal challenges. Therefore, there is a need to provide robust and reliable services taking into account energy consumption aspect of e-infrastructures. The aim of the article is to introduce an energy optimization methodology for the beneficiaries of the e-infrastructures to explore, optimize, and report the energy consumption and CO2 emission of data, computing, and networking facilities. The suggested methodology has been implemented within the Armenian e-infrastructure aiming at the reduction of the energy consumption and thereby the CO2 emission.
Hrachya Astsatryan; Wahi Narsisian; Aram Kocharyan; Georges Da Costa; Albert Hankel; Ariel Oleksiak. Energy optimization methodology for e-infrastructure providers. Concurrency and Computation: Practice and Experience 2017, 29, e4073 .
AMA StyleHrachya Astsatryan, Wahi Narsisian, Aram Kocharyan, Georges Da Costa, Albert Hankel, Ariel Oleksiak. Energy optimization methodology for e-infrastructure providers. Concurrency and Computation: Practice and Experience. 2017; 29 (10):e4073.
Chicago/Turabian StyleHrachya Astsatryan; Wahi Narsisian; Aram Kocharyan; Georges Da Costa; Albert Hankel; Ariel Oleksiak. 2017. "Energy optimization methodology for e-infrastructure providers." Concurrency and Computation: Practice and Experience 29, no. 10: e4073.
Highlights•A comparative study of pairwise sequence alignment tools is presented.•Considerable differences in energy efficiency between individual tools are reported.•The proposed FPGA implementation outperforms other tools on energy efficiency front.•Newly developed RECS®|BoxRECS®|Box hardware is presented with its monitoring infrastructure. AbstractPairwise sequence alignment is ubiquitous in modern bioinformatics. It may be performed either explicitly, e.g. to find the most similar sequences in a database, or implicitly as a hidden building block of more complex methods, e.g. for reads mapping. The alignment algorithms have been widely investigated over the last few years, mainly with respect to their speed. However, no attention was given to their energy efficiency, which is becoming critical in high performance computing and cloud environment. We compare the energy efficiency of the most established software tools performing exact pairwise sequence alignment on various computational architectures: CPU, GPU and Intel Xeon Phi. The results show that the energy consumption may differ as much as nearly 5 times. Substantial differences are reported even for different implementations running on the same hardware. Moreover, we present an FPGA implementation of one of the tested tools — G-DNA, and show how it outperforms all the others on the energy efficiency front. Finally, some details regarding the special RECS®|BoxRECS®|Box servers used in our study are outlined. This hardware is designed and manufactured within the FiPS project by the Bielefeld University and Christmann Informationstechnik + Medien with a special purpose to deliver highly heterogeneous computational environment supporting energy efficiency and green ICT.
Michał Kierzynka; Lars Kosmann; Micha Vor Dem Berge; Stefan Krupop; Jens Hagemeyer; René Griessl; Meysam Peykanu; Ariel Oleksiak. Energy efficiency of sequence alignment tools—Software and hardware perspectives. Future Generation Computer Systems 2017, 67, 455 -465.
AMA StyleMichał Kierzynka, Lars Kosmann, Micha Vor Dem Berge, Stefan Krupop, Jens Hagemeyer, René Griessl, Meysam Peykanu, Ariel Oleksiak. Energy efficiency of sequence alignment tools—Software and hardware perspectives. Future Generation Computer Systems. 2017; 67 ():455-465.
Chicago/Turabian StyleMichał Kierzynka; Lars Kosmann; Micha Vor Dem Berge; Stefan Krupop; Jens Hagemeyer; René Griessl; Meysam Peykanu; Ariel Oleksiak. 2017. "Energy efficiency of sequence alignment tools—Software and hardware perspectives." Future Generation Computer Systems 67, no. : 455-465.
Mateusz Jarus; Ariel Oleksiak. Top-Down Characterization Approximation based on performance counters architecture for AMD processors. Simulation Modelling Practice and Theory 2016, 68, 146 -162.
AMA StyleMateusz Jarus, Ariel Oleksiak. Top-Down Characterization Approximation based on performance counters architecture for AMD processors. Simulation Modelling Practice and Theory. 2016; 68 ():146-162.
Chicago/Turabian StyleMateusz Jarus; Ariel Oleksiak. 2016. "Top-Down Characterization Approximation based on performance counters architecture for AMD processors." Simulation Modelling Practice and Theory 68, no. : 146-162.
Energy consumption is one of the main limiting factors for designing and deploying ultrascale systems. Therefore, this paper presents challenges and trends associated with energy efficiency for ultrascale systems based on current activities of the working group on "Energy Efficiency" in the European COST Action Nesus IC1305. The analysis contains major areas that are related to studies of energy efficiency in ultrascale systems: heterogeneous and low power hardware architectures, power monitoring at large scale, modeling and simulation of ultrascale systems, energy-aware scheduling and resource management, and energy-efficient application design.
Michel Bagein; Jorge Barbosa; Vicente Blanco; Ivona Brandic; Samuel Cremer; Sebastien Fremal; Helen Karatza; Laurent Lefèvre; Toni Mastelic; Ariel Oleksiak; Anne-Cecile Orgerie; Georgios L. Stavrinides; Sébastien Varrette. Energy Efficiency for Ultrascale Systems: Challenges and Trends from Nesus Project. Supercomputing Frontiers and Innovations 2015, 2, 1 .
AMA StyleMichel Bagein, Jorge Barbosa, Vicente Blanco, Ivona Brandic, Samuel Cremer, Sebastien Fremal, Helen Karatza, Laurent Lefèvre, Toni Mastelic, Ariel Oleksiak, Anne-Cecile Orgerie, Georgios L. Stavrinides, Sébastien Varrette. Energy Efficiency for Ultrascale Systems: Challenges and Trends from Nesus Project. Supercomputing Frontiers and Innovations. 2015; 2 (2):1.
Chicago/Turabian StyleMichel Bagein; Jorge Barbosa; Vicente Blanco; Ivona Brandic; Samuel Cremer; Sebastien Fremal; Helen Karatza; Laurent Lefèvre; Toni Mastelic; Ariel Oleksiak; Anne-Cecile Orgerie; Georgios L. Stavrinides; Sébastien Varrette. 2015. "Energy Efficiency for Ultrascale Systems: Challenges and Trends from Nesus Project." Supercomputing Frontiers and Innovations 2, no. 2: 1.
The need to improve how efficiently data centre operate is increasing due to the continued high demand for new data centre capacity combined with other factors such as the increased competition for energy resources. The financial crisis may have dampened data centre demand temporarily, but current projections indicate strong growth ahead. By 2020, it is estimated that annual investment in the construction of new data centres will rise to $ 50bn in the US, and $ 220bn worldwide [23].
Micha Vor Dem Berge; Jochen Buchholz; Leandro Cupertino; Georges Da Costa; Andrew Donoghue; Georgina Gallizo; Mateusz Jarus; Lara Lopez; Ariel Oleksiak; Enric Pages; Wojciech Piatek; Jean-Marc Pierson; Tomasz Piontek; Daniel Rathgeb; Jaume Salom; Laura Sisó; Eugen Volk; Uwe Wössner; Thomas Zilio. CoolEmAll: Models and Tools for Planning and Operating Energy Efficient Data Centres. Handbook on Data Centers 2015, 191 -245.
AMA StyleMicha Vor Dem Berge, Jochen Buchholz, Leandro Cupertino, Georges Da Costa, Andrew Donoghue, Georgina Gallizo, Mateusz Jarus, Lara Lopez, Ariel Oleksiak, Enric Pages, Wojciech Piatek, Jean-Marc Pierson, Tomasz Piontek, Daniel Rathgeb, Jaume Salom, Laura Sisó, Eugen Volk, Uwe Wössner, Thomas Zilio. CoolEmAll: Models and Tools for Planning and Operating Energy Efficient Data Centres. Handbook on Data Centers. 2015; ():191-245.
Chicago/Turabian StyleMicha Vor Dem Berge; Jochen Buchholz; Leandro Cupertino; Georges Da Costa; Andrew Donoghue; Georgina Gallizo; Mateusz Jarus; Lara Lopez; Ariel Oleksiak; Enric Pages; Wojciech Piatek; Jean-Marc Pierson; Tomasz Piontek; Daniel Rathgeb; Jaume Salom; Laura Sisó; Eugen Volk; Uwe Wössner; Thomas Zilio. 2015. "CoolEmAll: Models and Tools for Planning and Operating Energy Efficient Data Centres." Handbook on Data Centers , no. : 191-245.
Nowadays, moderating energy consumption and building eco-friendly computing infrastructure is a major goal in large data centers. Moreover, data center energy usage has risen dramatically over the past decade and will continue to grow in-step with the High Performance Computing (HPC) intensive workloads which are at the heart of our modern life. The recent advances in the technology has driven the data center into a new phase of expansion featuring solutions with higher density. To this end, much has been done to increase server efficiency and IT space utilization. In this chapter, we will provide a state-of-the-art overview as regards energy-efficiency in High Performance Computing (HPC) facilities while describing the open challenges the research community has to face in the coming years to enable the building and usage of an Exascale platform by 2020.
Sébastien Varrette; Pascal Bouvry; Mateusz Jarus; Ariel Oleksiak. Energy Efficiency in HPC Data Centers: Latest Advances to Build the Path to Exascale. Handbook on Data Centers 2015, 81 -107.
AMA StyleSébastien Varrette, Pascal Bouvry, Mateusz Jarus, Ariel Oleksiak. Energy Efficiency in HPC Data Centers: Latest Advances to Build the Path to Exascale. Handbook on Data Centers. 2015; ():81-107.
Chicago/Turabian StyleSébastien Varrette; Pascal Bouvry; Mateusz Jarus; Ariel Oleksiak. 2015. "Energy Efficiency in HPC Data Centers: Latest Advances to Build the Path to Exascale." Handbook on Data Centers , no. : 81-107.
In this paper we present an approach to improve power and cooling capacity management in a data center by taking into account knowledge about applications and workloads. We apply power capping techniques and proper cooling infrastructure configuration to achieve savings in energy and costs. To estimate values of a total energy consumption and costs we simulate both IT software/hardware and cooling infrastructure at once using the CoolEmAll SVD Toolkit. We also investigated the use of power capping to adjust data center operation to variable power supply and pricing. By better adjusting cooling infrastructure to specific types of workloads, we were able to find a configuration which resulted in energy, OPEX and CAPEX savings in the range of 4–25 %.
Georges Da Costa; Ariel Oleksiak; Wojciech Piatek; Jaume Salom; Laura Sisó. Minimization of Costs and Energy Consumption in a Data Center by a Workload-Based Capacity Management. Transactions on Petri Nets and Other Models of Concurrency XV 2015, 102 -119.
AMA StyleGeorges Da Costa, Ariel Oleksiak, Wojciech Piatek, Jaume Salom, Laura Sisó. Minimization of Costs and Energy Consumption in a Data Center by a Workload-Based Capacity Management. Transactions on Petri Nets and Other Models of Concurrency XV. 2015; ():102-119.
Chicago/Turabian StyleGeorges Da Costa; Ariel Oleksiak; Wojciech Piatek; Jaume Salom; Laura Sisó. 2015. "Minimization of Costs and Energy Consumption in a Data Center by a Workload-Based Capacity Management." Transactions on Petri Nets and Other Models of Concurrency XV , no. : 102-119.
This paper describes the CoolEmAll project and its approach for modeling and simulating energy-efficient and thermal-aware data centers. The aim of the project was to address energy-thermal efficiency of data centers by combining the optimization of IT, cooling and workload management. This paper provides a complete data center model considering the workload profiles, the applications profiling, the power model and a cooling model. Different energy efficiency metrics are proposed and various resource management and scheduling policies are presented. The proposed strategies are validated through simulation at different levels of a data center.
Leandro Cupertino; Georges Da Costa; Ariel Oleksiak; Wojciech Pia¸tek; Jean-Marc Pierson; Jaume Salom; Laura Sisó; Patricia Stolf; Hongyang Sun; Thomas Zilio. Energy-efficient, thermal-aware modeling and simulation of data centers: The CoolEmAll approach and evaluation results. Ad Hoc Networks 2015, 25, 535 -553.
AMA StyleLeandro Cupertino, Georges Da Costa, Ariel Oleksiak, Wojciech Pia¸tek, Jean-Marc Pierson, Jaume Salom, Laura Sisó, Patricia Stolf, Hongyang Sun, Thomas Zilio. Energy-efficient, thermal-aware modeling and simulation of data centers: The CoolEmAll approach and evaluation results. Ad Hoc Networks. 2015; 25 ():535-553.
Chicago/Turabian StyleLeandro Cupertino; Georges Da Costa; Ariel Oleksiak; Wojciech Pia¸tek; Jean-Marc Pierson; Jaume Salom; Laura Sisó; Patricia Stolf; Hongyang Sun; Thomas Zilio. 2015. "Energy-efficient, thermal-aware modeling and simulation of data centers: The CoolEmAll approach and evaluation results." Ad Hoc Networks 25, no. : 535-553.
Cloud computing is today’s most emphasized Information and Communications Technology (ICT) paradigm that is directly or indirectly used by almost every online user. However, such great significance comes with the support of a great infrastructure that includes large data centers comprising thousands of server units and other supporting equipment. Their share in power consumption generates between 1.1% and 1.5% of the total electricity use worldwide and is projected to rise even more. Such alarming numbers demand rethinking the energy efficiency of such infrastructures. However, before making any changes to infrastructure, an analysis of the current status is required. In this article, we perform a comprehensive analysis of an infrastructure supporting the cloud computing paradigm with regards to energy efficiency. First, we define a systematic approach for analyzing the energy efficiency of most important data center domains, including server and network equipment, as well as cloud management systems and appliances consisting of a software utilized by end users. Second, we utilize this approach for analyzing available scientific and industrial literature on state-of-the-art practices in data centers and their equipment. Finally, we extract existing challenges and highlight future research directions.
Toni Mastelic; Ariel Oleksiak; Holger Claussen; Ivona Brandic; Jean-Marc Pierson; Athanasios V. Vasilakos. Cloud Computing. ACM Computing Surveys 2015, 47, 1 -36.
AMA StyleToni Mastelic, Ariel Oleksiak, Holger Claussen, Ivona Brandic, Jean-Marc Pierson, Athanasios V. Vasilakos. Cloud Computing. ACM Computing Surveys. 2015; 47 (2):1-36.
Chicago/Turabian StyleToni Mastelic; Ariel Oleksiak; Holger Claussen; Ivona Brandic; Jean-Marc Pierson; Athanasios V. Vasilakos. 2015. "Cloud Computing." ACM Computing Surveys 47, no. 2: 1-36.
Robert Basmadjian; Georges Da Costa; Ghislain Landry Tsafack Chetsa; Laurent Lefèvre; Ariel Oleksiak; Jean-Marc Pierson; Emmanuel Jeannot; Julius Žilinskas. Energy‐Aware Approaches for HPC Systems. High‐Performance Computing on Complex Environments 2014, 341 -363.
AMA StyleRobert Basmadjian, Georges Da Costa, Ghislain Landry Tsafack Chetsa, Laurent Lefèvre, Ariel Oleksiak, Jean-Marc Pierson, Emmanuel Jeannot, Julius Žilinskas. Energy‐Aware Approaches for HPC Systems. High‐Performance Computing on Complex Environments. 2014; ():341-363.
Chicago/Turabian StyleRobert Basmadjian; Georges Da Costa; Ghislain Landry Tsafack Chetsa; Laurent Lefèvre; Ariel Oleksiak; Jean-Marc Pierson; Emmanuel Jeannot; Julius Žilinskas. 2014. "Energy‐Aware Approaches for HPC Systems." High‐Performance Computing on Complex Environments , no. : 341-363.
In this paper we present a concept and specification of Data Center Efficiency Building Blocks (DEBBs), which represent hardware components of a data center complemented by descriptions of their energy efficiency. Proposed building blocks contain hardware and thermodynamic models that can be applied to simulate a data center and to evaluate its energy efficiency. DEBBs are available in an open repository being built by the CoolEmAll project. In the paper we illustrate the concept by an example of DEBB defined for the RECS multi-server system including models of its power usage and thermodynamic properties. We also show how these models are affected by specific architecture of modeled hardware and differences between various classes of applications. Proposed models are verified by a comparison to measurements on a real infrastructure. Finally, we demonstrate how DEBBs are used in data center simulations.
Micha Vor Dem Berge; Georges Da Costa; Mateusz Jarus; Ariel Oleksiak; Wojciech Piatek; Eugen Volk. Modeling Data Center Building Blocks for Energy-Efficiency and Thermal Simulations. Transactions on Petri Nets and Other Models of Concurrency XV 2014, 66 -82.
AMA StyleMicha Vor Dem Berge, Georges Da Costa, Mateusz Jarus, Ariel Oleksiak, Wojciech Piatek, Eugen Volk. Modeling Data Center Building Blocks for Energy-Efficiency and Thermal Simulations. Transactions on Petri Nets and Other Models of Concurrency XV. 2014; ():66-82.
Chicago/Turabian StyleMicha Vor Dem Berge; Georges Da Costa; Mateusz Jarus; Ariel Oleksiak; Wojciech Piatek; Eugen Volk. 2014. "Modeling Data Center Building Blocks for Energy-Efficiency and Thermal Simulations." Transactions on Petri Nets and Other Models of Concurrency XV , no. : 66-82.
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 article, 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 purpose 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.
Mateusz Jarus; Sébastien Varrette; Ariel Oleksiak; Pascal Bouvry. Performance Evaluation and Energy Efficiency of High-Density HPC Platforms Based on Intel, AMD and ARM Processors. Parallel Processing and Applied Mathematics 2013, 182 -200.
AMA StyleMateusz Jarus, Sébastien Varrette, Ariel Oleksiak, Pascal Bouvry. Performance Evaluation and Energy Efficiency of High-Density HPC Platforms Based on Intel, AMD and ARM Processors. Parallel Processing and Applied Mathematics. 2013; ():182-200.
Chicago/Turabian StyleMateusz Jarus; Sébastien Varrette; Ariel Oleksiak; Pascal Bouvry. 2013. "Performance Evaluation and Energy Efficiency of High-Density HPC Platforms Based on Intel, AMD and ARM Processors." Parallel Processing and Applied Mathematics , no. : 182-200.
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 article, 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 purpose 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.
Mateusz Jarus; Ariel Oleksiak. Gicomp and GreenOffice – Monitoring and Management Platforms for IT and Home Appliances. Computer Vision 2013, 58 -62.
AMA StyleMateusz Jarus, Ariel Oleksiak. Gicomp and GreenOffice – Monitoring and Management Platforms for IT and Home Appliances. Computer Vision. 2013; ():58-62.
Chicago/Turabian StyleMateusz Jarus; Ariel Oleksiak. 2013. "Gicomp and GreenOffice – Monitoring and Management Platforms for IT and Home Appliances." Computer Vision , no. : 58-62.