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1. Reuse of Data Center Waste Heat in Nearby Neighborhoods: A Neural Networks-Based Prediction Model

Author

Marcel Antal, Tudor Cioara, Ionut Anghel, Radoslaw Gorzenski, Radoslaw Januszewski, Ariel Oleksiak, Wojciech Piatek, Claudia Pop, Ioan Salomie, and Wojciech Szeliga

Subjects
data center, heat reuse, Computational Fluid Dynamics, prediction algorithm, neural networks, Technology
Abstract

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.

Published
2019
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3. TEXTAROSSA: Towards EXtreme scale Technologies and Accelerators for euROhpc hw/Sw Supercomputing Applications for exascale.

Author

Giovanni Agosta, Daniele Cattaneo 0002, William Fornaciari, Andrea Galimberti, Giuseppe Massari, Federico Reghenzani, Federico Terraneo, Davide Zoni, Carlo Brandolese, Massimo Celino, Francesco Iannone, Paolo Palazzari, Giuseppe Zummo, Massimo Bernaschi, Pasqua D'Ambra, Sergio Saponara, Marco Danelutto, Massimo Torquati, Marco Aldinucci, Yasir Arfat, Barbara Cantalupo, Iacopo Colonnelli, Roberto Esposito, Alberto Riccardo Martinelli, Gianluca Mittone, Olivier Beaumont, Bérenger Bramas, Lionel Eyraud-Dubois, Brice Goglin, Abdou Guermouche, Raymond Namyst, Samuel Thibault, Antonio Filgueras, Miquel Vidal, Carlos álvarez 0001, Xavier Martorell, Ariel Oleksiak, Michal Kulczewski, Alessandro Lonardo, Piero Vicini, Francesca Lo Cicero, Francesco Simula, Andrea Biagioni, Paolo Cretaro, Ottorino Frezza, Pier Stanislao Paolucci, Matteo Turisini, Francesco Giacomini, Tommaso Boccali, Simone Montangero, and Roberto Ammendola

Published
2021
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4. Reliable power and time-constraints-aware predictive management of heterogeneous exascale systems.

Author

William Fornaciari, Giovanni Agosta, David Atienza, Carlo Brandolese, Leila Cammoun, Luca Cremona, Alessandro Cilardo, Albert Farrés, José Flich, Carles Hernández 0001, Michal Kulchewski, Simone Libutti, José Maria Martínez, Giuseppe Massari, Ariel Oleksiak, Anna Pupykina, Federico Reghenzani, Rafael Tornero, Michele Zanella, Marina Zapater, and Davide Zoni

Published
2018
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8. Data centres for IoT applications: The M2DC approach (Invited paper).

Author

Michal Kierzynka, Ariel Oleksiak, Giovanni Agosta, Carlo Brandolese, William Fornaciari, Gerardo Pelosi, Micha vor dem Berge, Wolfgang Christmann, Stefan Krupop, Mariano Cecowski, Robert Plestenjak, Justin Cinkelj, Mario Porrmann, Jens Hagemeyer, René Griessl, Meysam Peykanu, Lennart Tigges, Loïc Cudennec, Thierry Goubier, Jean-Marc Philippe, Sven Rosinger, Daniel Schlitt, Christian Pieper, Chris Adeniyi-Jones, Udo Janssen, and Luca Ceva

Published
2016
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10. The M2DC Project: Modular Microserver DataCentre.

Author

Mariano Cecowski, Giovanni Agosta, Ariel Oleksiak, Michal Kierzynka, Micha vor dem Berge, Wolfgang Christmann, Stefan Krupop, Mario Porrmann, Jens Hagemeyer, René Griessl, Meysam Peykanu, Lennart Tigges, Sven Rosinger, Daniel Schlitt, Christian Pieper, Carlo Brandolese, William Fornaciari, Gerardo Pelosi, Robert Plestenjak, Justin Cinkelj, Loïc Cudennec, Thierry Goubier, Jean-Marc Philippe, Udo Janssen, and Chris Adeniyi-Jones

Published
2016
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24. Towards EXtreme scale technologies and accelerators for euROhpc hw/Sw supercomputing applications for exascale: The TEXTAROSSA approach

Author

Giovanni Agosta, Marco Aldinucci, Carlos Alvarez, Roberto Ammendola, Yasir Arfat, Olivier Beaumont, Massimo Bernaschi, Andrea Biagioni, Tommaso Boccali, Berenger Bramas, Carlo Brandolese, Barbara Cantalupo, Mauro Carrozzo, Daniele Cattaneo, Alessandro Celestini, Massimo Celino, Iacopo Colonnelli, Paolo Cretaro, Pasqua D’Ambra, Marco Danelutto, Roberto Esposito, Lionel Eyraud-Dubois, Antonio Filgueras, William Fornaciari, Ottorino Frezza, Andrea Galimberti, Francesco Giacomini, Brice Goglin, Daniele Gregori, Abdou Guermouche, Francesco Iannone, Michal Kulczewski, Francesca Lo Cicero, Alessandro Lonardo, Alberto R. Martinelli, Michele Martinelli, Xavier Martorell, Giuseppe Massari, Simone Montangero, Gianluca Mittone, Raymond Namyst, Ariel Oleksiak, Paolo Palazzari, Pier Stanislao Paolucci, Federico Reghenzani, Cristian Rossi, Sergio Saponara, Francesco Simula, Federico Terraneo, Samuel Thibault, Massimo Torquati, Matteo Turisini, Piero Vicini, Miquel Vidal, Davide Zoni, Giuseppe Zummo, Politecnico di Milano [Milan] (POLIMI), Università degli studi di Torino = University of Turin (UNITO), Barcelona Supercomputing Center - Centro Nacional de Supercomputacion (BSC - CNS), Istituto Nazionale di Fisica Nucleare, Sezione di Roma Tor Vergata (INFN, Sezione di Roma Tor Vergata), Istituto Nazionale di Fisica Nucleare (INFN), High-End Parallel Algorithms for Challenging Numerical Simulations (HiePACS), Laboratoire Bordelais de Recherche en Informatique (LaBRI), Université de Bordeaux (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS)-Université de Bordeaux (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS)-Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Istituto per le Applicazioni del Calcolo 'Mauro Picone' (IAC), National Research Council of Italy | Consiglio Nazionale delle Ricerche (CNR), Istituto Nazionale di Fisica Nucleare, Sezione di Roma 3 (INFN, Sezione di Roma 3), Compilation pour les Architectures MUlti-coeurS (CAMUS), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire des sciences de l'ingénieur, de l'informatique et de l'imagerie (ICube), École Nationale du Génie de l'Eau et de l'Environnement de Strasbourg (ENGEES)-Université de Strasbourg (UNISTRA)-Institut National des Sciences Appliquées - Strasbourg (INSA Strasbourg), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Les Hôpitaux Universitaires de Strasbourg (HUS)-Centre National de la Recherche Scientifique (CNRS)-Matériaux et Nanosciences Grand-Est (MNGE), Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Réseau nanophotonique et optique, Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS)-École Nationale du Génie de l'Eau et de l'Environnement de Strasbourg (ENGEES)-Université de Strasbourg (UNISTRA)-Institut National des Sciences Appliquées - Strasbourg (INSA Strasbourg), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Les Hôpitaux Universitaires de Strasbourg (HUS)-Centre National de la Recherche Scientifique (CNRS)-Matériaux et Nanosciences Grand-Est (MNGE), Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS), Istituto Nazionale di Fisica Nucleare [Pisa] (INFN), Agenzia Nazionale per le nuove Tecnologie, l’energia e lo sviluppo economico sostenibile = Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA), University of Pisa - Università di Pisa, Topology-Aware System-Scale Data Management for High-Performance Computing (TADAAM), Poznan Supercomputing and Networking Center (PSNC), Istituto Nazionale di Fisica Nucleare [Sezione di Roma 1] (INFN), Istituto Nazionale di Fisica Nucleare, Università degli Studi di Padova = University of Padua (Unipd), STatic Optimizations, Runtime Methods (STORM), European Project: 956831,TEXTAROSSA(2021), Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors, Universitat Politècnica de Catalunya. Doctorat en Arquitectura de Computadors, Barcelona Supercomputing Center, and Universitat Politècnica de Catalunya. CAP - Grup de Computació d'Altes Prestacions

Subjects
thermal and power management, Computer Networks and Communications, Energia -- Consum, exascale computing, thermal and power management, euroHPC, euroHPC, Energy consumption, exascale computing, Artificial Intelligence, Hardware and Architecture, [INFO]Computer Science [cs], High performance computing, High-performance computing, Informàtica::Arquitectura de computadors [Àrees temàtiques de la UPC], Càlcul intensiu (Informàtica), Software
Abstract

In the near future, Exascale systems will need to bridge three technology gaps to achieve high performance while remaining under tight power constraints: energy efficiency and thermal control; extreme computation efficiency via HW acceleration and new arithmetic; methods and tools for seamless integration of reconfigurable accelerators in heterogeneous HPC multi-node platforms. TEXTAROSSA addresses these gaps through a co-design approach to heterogeneous HPC solutions, supported by the integration and extension of HW and SW IPs, programming models, and tools derived from European research. This work is supported by the TEXTAROSSA project (G.A. n. 956831), as part of the EuroHPC initiative. Peer Reviewed Article signat per 56 autors/es: Giovanni Agosta (a) , Marco Aldinucci (f) , Carlos Alvarez (h) , Roberto Ammendola (n) , Yasir Arfat (f) , Olivier Beaumont (g) , Massimo Bernaschi (c) , Andrea Biagioni (j) , Tommaso Boccali (l) , Berenger Bramas (g) , Carlo Brandolese (a) , Barbara Cantalupo (f) , Mauro Carrozzo (c) , Daniele Cattaneo (a) , Alessandro Celestini (c) , Massimo Celino (b) , Iacopo Colonnelli (f) , Paolo Cretaro (j) , Pasqua D’Ambra (d) , Marco Danelutto (e) , Roberto Esposito (f) , Lionel Eyraud-Dubois (g) , Antonio Filgueras (h) , William Fornaciari (a) , Ottorino Frezza (j) , Andrea Galimberti (a) , Francesco Giacomini (k) , Brice Goglin (g) , Daniele Gregori (o) , Abdou Guermouche (g) , Francesco Iannone (b) , Michal Kulczewski (i) , Francesca Lo Cicero (j) , Alessandro Lonardo (j) , Alberto R. Martinelli (f) , Michele Martinelli (j) , Xavier Martorell (h) , Giuseppe Massari (a) , Simone Montangero (m), Gianluca Mittone (f) , Raymond Namyst (g) , Ariel Oleksiak (i) , Paolo Palazzari (b) , Pier Stanislao Paolucci (j) , Federico Reghenzani (a)∗ , Cristian Rossi (j) , Sergio Saponara (e) , Francesco Simula (j) , Federico Terraneo (a) , Samuel Thibault (g) , Massimo Torquati (e) , Matteo Turisini (j) , Piero Vicini (j) , Miquel Vidal (h) , Davide Zoni (a) , Giuseppe Zummo (b) // (a) Politecnico di Milano, Dipartimento di Elettronica, Informazione e Bioingegneria, Italy; (b) ENEA, Agenzia nazionale per le nuove tecnologie, l’energia e lo sviluppo economico sostenibile, Italy; (c) Istituto per le Applicazioni del Calcolo (IAC), Consiglio Nazionale delle Ricerche, Rome, Italy; (d) Istituto per le Applicazioni del Calcolo (IAC), Consiglio Nazionale delle Ricerche, Naples, Italy; (e) University of Pisa, Italy; (f) University of Torino, Italy; (g) Institut national de recherche en informatique et en automatique (Inria), France; (h) Barcelona Supercomputing Center, Spain; (i) Poznan Supercomputing and Networking Center, Poland; (j) Istituto Nazionale di Fisica Nucleare, Sezione di Roma, Italy; (k) Istituto Nazionale di Fisica Nucleare, CNAF, Italy; (l) Istituto Nazionale di Fisica Nucleare, Sezione di Pisa, Italy; (m) University of Padova and Istituto Nazionale di Fisica Nucleare Sezione di Padova, Italy; (n) Istituto Nazionale di Fisica Nucleare, Sezione di Roma Tor Vergata, Italy; (o) E4 Computer Engineering Spa, Italy

Published
2022

25. Energy-efficient power cap configurations through Pareto Front Analysis and Machine Learning Categorization

Author

Alberto Cabrera, Francisco Almeida, Dagoberto Castellanos-Nieves, Ariel Oleksiak, and Vicente Blanco

Abstract

The growing demand for more computational resources has increased the overall energy consumption in computer systems. To support the increasing requirements, power and energy consumption have to be considered as a constraint to execute software. Modern architectures provide tools to manage directly the power constraints of a system. The Intel Power Cap is a relatively recent tool developed to offer fine control of power usage to users at a central processing unit (CPU) level. We propose a methodology to analyze the performance and the energy efficiency trade-offs using this power cap technology for a given algorithm. We extract a Pareto front for the multi-objective performance and energy problem to represent multiple feasible configurations for both objectives. We perform an extensive experimentation to categorize the different algorithms to reduce the total amount of optimal power cap configurations. We propose the use of Machine Learning (ML) clustering techniques to categorize any algorithm in the target architecture.The use of Machine Learning allows to automate the procedure and simplifies the effort required to solve the optimization problem.We present a practical case where we categorize the kernels using ML techniques, with the option to include a new algorithm into an already existing categorization.

Published
2022

36. An approach to reduce energy consumption and performance losses on heterogeneous servers using power capping

Author

Alberto Cabrera, Vicente Blanco, Tomasz Ciesielczyk, Wojciech Piątek, Francisco Almeida, Grzegorz Waligóra, and Ariel Oleksiak

Subjects
Supply chain management, Heuristic (computer science), Computer science, Distributed computing, General Engineering, 020206 networking & telecommunications, 02 engineering and technology, Energy consumption, Management Science and Operations Research, Power (physics), Artificial Intelligence, Server, Limit (music), 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Enhanced Data Rates for GSM Evolution, Software, Efficient energy use
Abstract

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.

Published
2020

37. TEXTAROSSA: Towards EXtreme scale Technologies and Accelerators for euROhpc hw/Sw Supercomputing Applications for exascale

Author

Ottorino Frezza, Olivier Beaumont, Simone Montangero, Francesco Simula, Marco Aldinucci, Francesca Lo Cicero, Tommaso Boccali, Raymond Namyst, Piero Vicini, Brice Goglin, Pasqua D'Ambra, Federico Terraneo, Davide Zoni, Massimo Bernaschi, Massimo Torquati, Alessandro Lonardo, Gianluca Mittone, Alberto Riccardo Martinelli, Andrea Galimberti, Roberto Esposito, Daniele Cattaneo, Paolo Cretaro, Massimo Celino, Carlos Alvarez, Pierluigi Paolucci, F. Iannone, Xavier Martorell, Iacopo Colonnelli, Federico Reghenzani, Bérenger Bramas, Giuseppe Massari, William Fornaciari, Antonio Filgueras, Giovanni Agosta, Yasir Arfat, Michal Kulczewski, Sergio Saponara, Andrea Biagioni, Matteo Turisini, Samuel Thibault, Roberto Ammendola, Giuseppe Zummo, Barbara Cantalupo, Francesco Giacomini, Ariel Oleksiak, Marco Danelutto, Miquel Vidal, Lionel Eyraud-Dubois, Paolo Palazzari, Carlo Brandolese, Abdou Guermouche, Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB), Politecnico di Milano [Milan] (POLIMI), Agenzia Nazionale per le nuove Tecnologie, l’energia e lo sviluppo economico sostenibile = Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA), Istituto per le Applicazioni del Calcolo 'Mauro Picone' (IAC), National Research Council of Italy | Consiglio Nazionale delle Ricerche (CNR), University of Pisa - Università di Pisa, Università degli studi di Torino = University of Turin (UNITO), High-End Parallel Algorithms for Challenging Numerical Simulations (HiePACS), Laboratoire Bordelais de Recherche en Informatique (LaBRI), Université de Bordeaux (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS)-Université de Bordeaux (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS)-Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Compilation pour les Architectures MUlti-coeurS (CAMUS), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire des sciences de l'ingénieur, de l'informatique et de l'imagerie (ICube), École Nationale du Génie de l'Eau et de l'Environnement de Strasbourg (ENGEES)-Université de Strasbourg (UNISTRA)-Institut National des Sciences Appliquées - Strasbourg (INSA Strasbourg), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Les Hôpitaux Universitaires de Strasbourg (HUS)-Centre National de la Recherche Scientifique (CNRS)-Matériaux et Nanosciences Grand-Est (MNGE), Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Réseau nanophotonique et optique, Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS)-École Nationale du Génie de l'Eau et de l'Environnement de Strasbourg (ENGEES)-Université de Strasbourg (UNISTRA)-Institut National des Sciences Appliquées - Strasbourg (INSA Strasbourg), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Les Hôpitaux Universitaires de Strasbourg (HUS)-Centre National de la Recherche Scientifique (CNRS)-Matériaux et Nanosciences Grand-Est (MNGE), Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS), Topology-Aware System-Scale Data Management for High-Performance Computing (TADAAM), Université de Bordeaux (UB), STatic Optimizations, Runtime Methods (STORM), Barcelona Supercomputing Center - Centro Nacional de Supercomputacion (BSC - CNS), Poznan Supercomputing and Networking Center (PSNC), Istituto Nazionale di Fisica Nucleare [Sezione di Roma 1] (INFN), Istituto Nazionale di Fisica Nucleare, Istituto Nazionale di Fisica Nucleare (INFN), Istituto Nazionale di Fisica Nucleare [Pisa] (INFN), Istituto Nazionale di Fisica Nucleare, Sezione di Padova (INFN, Sezione di Padova), Istituto Nazionale di Fisica Nucleare, Sezione di Roma Tor Vergata (INFN, Sezione di Roma Tor Vergata), This work is supported by the TEXTAROSSA project G.A. n° 956831, as part of the EuroHPC initiative., European Project: 956831,TEXTAROSSA(2021), Goglin, Brice, Towards EXtreme scale Technologies and Accelerators for euROhpc hw/Sw Supercomputing Applications for exascale - TEXTAROSSA - 2021-01-01 - 2024-01-01 - 956831 - VALID, Consiglio Nazionale delle Ricerche [Roma] (CNR), Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA), Università degli studi di Torino (UNITO), Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Inria Bordeaux - Sud-Ouest, Institut National des Sciences Appliquées - Strasbourg (INSA Strasbourg), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS)-École Nationale du Génie de l'Eau et de l'Environnement de Strasbourg (ENGEES)-Réseau nanophotonique et optique, Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Matériaux et nanosciences d'Alsace (FMNGE), Institut de Chimie du CNRS (INC)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Chimie du CNRS (INC)-Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Appliquées - Strasbourg (INSA Strasbourg), Institut de Chimie du CNRS (INC)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Chimie du CNRS (INC)-Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors, Barcelona Supercomputing Center, Universitat Politècnica de Catalunya. CAP - Grup de Computació d'Altes Prestacions, and Laboratoire des sciences de l'ingénieur, de l'informatique et de l'imagerie (ICube)

Subjects
[INFO.INFO-AR]Computer Science [cs]/Hardware Architecture [cs.AR], [INFO.INFO-AR] Computer Science [cs]/Hardware Architecture [cs.AR], European Projects, Power aware computing, Computer science, high Performance Computing, Exascale computing, European Projects, Thermal and power management, run-time management, Tools, Parallel Computing, Reconfigurable architectures, Exascale computing, Superordinadors -- Consum d'energia, run-time management, [INFO.INFO-DC] Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], high Performance Computing, Informàtica::Arquitectura de computadors [Àrees temàtiques de la UPC], Thermal and power management, European research, Computational modeling, Supercomputer, Software algorithms, Thermal control, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, High performance computing -- Energy consumption, Europe, Computer architecture, [INFO.INFO-OS] Computer Science [cs]/Operating Systems [cs.OS], Extreme scale, HPC, Programming paradigm, Key (cryptography), [INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation, [INFO.INFO-OS]Computer Science [cs]/Operating Systems [cs.OS], [INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], Digital systems, Programming parallel machines, Efficient energy use
Abstract

To achieve high performance and high energy efficiency on near-future exascale computing systems, three key technology gaps needs to be bridged. These gaps include: energy efficiency and thermal control; extreme computation efficiency via HW acceleration and new arithmetics; methods and tools for seamless integration of reconfigurable accelerators in heterogeneous HPC multi-node platforms. TEXTAROSSA aims at tackling this gap through a co-design approach to heterogeneous HPC solutions, supported by the integration and extension of HW and SW IPs, programming models and tools derived from European research. This work is supported by the TEXTAROSSA project G.A. n.956831, as part of the EuroHPC initiative. Peer Reviewed Article signat per 51 autors/es: Giovanni Agosta, Daniele Cattaneo, William Fornaciari, Andrea Galimberti, Giuseppe Massari, Federico Reghenzani, Federico Terraneo, Davide Zoni, Carlo Brandolese (DEIB – Politecnico di Milano, Italy, name.surname@polimi.it) | Massimo Celino, Francesco Iannone, Paolo Palazzari, Giuseppe Zummo (ENEA, Italy, name.surname@enea.it) | Massimo Bernaschi, Pasqua D’Ambra (Istituto per le Applicazioni del Calcolo (IAC) - CNR, Italy, name.surname@cnr.it) | Sergio Saponara, Marco Danelutto, Massimo Torquati (University of Pisa, Italy, name.surname@unipi.it) | Marco Aldinucci, Yasir Arfat, Barbara Cantalupo, Iacopo Colonnelli, Roberto Esposito, Alberto R. Martinelli, Gianluca Mittone (University of Torino, Italy, name.surname@unito.it) | Olivier Beaumont, Berenger Bramas, Lionel Eyraud-Dubois, Brice Goglin, Abdou Guermouche, Raymond Namyst, Samuel Thibault (Inria - France, name.surname@inria.fr) | Antonio Filgueras, Miquel Vidal, Carlos Alvarez, Xavier Martorell (BSC - Spain, name.surname@bsc.es) | Ariel Oleksiak, Michal Kulczewski (PSNC, Poland, ariel@man.poznan.pl, kulka@man.poznan.pl) | Alessandro Lonardo, Piero Vicini, Francesca Lo Cicero, Francesco Simula, Andrea Biagioni, Paolo Cretaro, Ottorino Frezza, Pier Stanislao Paolucci, Matteo Turisini (INFN Sezione di Roma - Italy, name.surname@roma1.infn.it) | Francesco Giacomini (INFN CNAF - Italy, name.surname@cnaf.infn.it) | Tommaso Boccali (INFN Sezione di Pisa - Italy, name.surname@pi.infn.it) | Simone Montangero (University of Padova and INFN Sezione di Padova - Italy, name.surname@pd.infn.it) | Roberto Ammendola (INFN Sezione di Roma Tor Vergata - Italy, name.surname@roma2.infn.it)

Published
2021

38. Data Centers Optimized Integration with Multi-Energy Grids: Test Cases and Results in Operational Environment

Author

Tudor Cioara, Marcel Antal, Wojciech Piatek, Marzia Mammina, Terpsichori-Helen Velivassaki, Artemis Voulkidis, Nicolas Saintherant, Massimo Bertoncini, Yoann Ricordel, Claudia Antal, Marilena Lazzaro, Ionut Anghel, Diego Arnone, and Ariel Oleksiak

Subjects
Primary energy, Computer science, 020209 energy, Geography, Planning and Development, TJ807-830, Context (language use), 02 engineering and technology, 010501 environmental sciences, Management, Monitoring, Policy and Law, TD194-195, 7. Clean energy, 01 natural sciences, Renewable energy sources, Thermal, 0202 electrical engineering, electronic engineering, information engineering, evaluation in relevant environment, GE1-350, energy efficiency, 0105 earth and related environmental sciences, Flexibility (engineering), Environmental effects of industries and plants, Renewable Energy, Sustainability and the Environment, business.industry, Quality of service, workload migration, Reliability engineering, Renewable energy, Environmental sciences, heat re-use, data centers, Test case, energy flexibility, business, Thermal energy, Efficient energy use
Abstract

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&rsquo, 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&rsquo, results validate the possibility of using renewable energy sources (RES) for exploiting DCs&rsquo, 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.

Published
2020
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39. Predictive reliability and fault management in exascale systems: State of the art and perspectives

Author

Rafa Tornero, Ramon Canal, Federico Reghenzani, David Atienza, Giuseppe Massari, Ariel Oleksiak, Wojciech Piątek, Carles Hernandez, Marina Zapater, Alessandro Cilardo, Jaume Abella, William Fornaciari, Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors, Barcelona Supercomputing Center, and Universitat Politècnica de Catalunya. VIRTUOS - Virtualisation and Operating Systems

Subjects
fault, General Computer Science, Computer science, Failures, Hardware_PERFORMANCEANDRELIABILITY, 02 engineering and technology, computer.software_genre, Fault (power engineering), Fault location (Engineering), Fault detection and isolation, Theoretical Computer Science, Fault management, power, Reliability (semiconductor), run-time management, 0202 electrical engineering, electronic engineering, information engineering, Electronics, mixed criticality, Survey, Informàtica::Arquitectura de computadors [Àrees temàtiques de la UPC], 020203 distributed computing, Mixed criticality, reliability, Faults, Supercomputing, Supercomputer, Reliability, 020202 computer hardware & architecture, Reliability engineering, ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES, reliability, exascale, performance, power, energy, fault, design space ezploration, run-time management, mixed criticality, Exascale, Grid computing, Semiconductors, HPC, Superordinadors, exascale, High performance computing, design space ezploration, Prediction, computer, performance, energy
Abstract

[EN] Performance and power constraints come together with Complementary Metal Oxide Semiconductor technology scaling in future Exascale systems. Technology scaling makes each individual transistor more prone to faults and, due to the exponential increase in the number of devices per chip, to higher system fault rates. Consequently, High-performance Computing (HPC) systems need to integrate prediction, detection, and recovery mechanisms to cope with faults efficiently. This article reviews fault detection, fault prediction, and recovery techniques in HPC systems, from electronics to system level. We analyze their strengths and limitations. Finally, we identify the promising paths to meet the reliability levels of Exascale systems., This work has received funding from the European Union's Horizon 2020 (H2020) research and innovation program under the FET-HPC Grant Agreement No. 801137 (RECIPE). Jaume Abella was also partially supported by the Ministry of Economy and Competitiveness of Spain under Contract No. TIN2015-65316-P and under Ramon y Cajal Postdoctoral Fellowship No. RYC-2013-14717, as well as by the HiPEAC Network of Excellence. Ramon Canal is partially supported by the Generalitat de Catalunya under Contract No. 2017SGR0962.

Published
2020
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40. Energy monitoring as an essential building block towards sustainable ultrascale systems

Author

Jorge G. Barbosa, Manuel F. Dolz, Marcos Dias De Assuncao, Helen D. Karatza, Ivona Brandic, Jean-Marc Pierson, Georges Da Costa, Francisco Almeida, Ilias Mavridis, Vicente Blanco, Ariel Oleksiak, Anne C. Elster, Anne-Cécile Orgerie, Laurent Lefèvre, Mateusz Jarus, Universidad de La Laguna [Tenerife - SP] (ULL), Algorithms and Software Architectures for Distributed and HPC Platforms (AVALON), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire de l'Informatique du Parallélisme (LIP), Centre National de la Recherche Scientifique (CNRS)-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École normale supérieure - Lyon (ENS Lyon)-Centre National de la Recherche Scientifique (CNRS)-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École normale supérieure - Lyon (ENS Lyon), Laboratoire de l'Informatique du Parallélisme (LIP), Departamento de matematica aplicada [Porto] (LIACC), Universidade do Porto, Vienna University of Technology (TU Wien), Système d’exploitation, systèmes répartis, de l’intergiciel à l’architecture (IRIT-SEPIA), Institut de recherche en informatique de Toulouse (IRIT), Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées, Université Toulouse III - Paul Sabatier (UT3), Universidad Carlos III de Madrid [Madrid] (UC3M), Department of Electronic Systems [Trondheim] (IES NTNU), Norwegian University of Science and Technology [Trondheim] (NTNU), Norwegian University of Science and Technology (NTNU)-Norwegian University of Science and Technology (NTNU), Poznan Supercomputing and Networking Center (PSNC), Aristotle University of Thessaloniki, Poznan University of Technology (PUT), Design and Implementation of Autonomous Distributed Systems (MYRIADS), Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-SYSTÈMES LARGE ÉCHELLE (IRISA-D1), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes 1 (UR1), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Nesus European COST Action IC1305European Commission under contract 288701 through the project CoolEmAlFrench Fonds national pour la Societe Numerique (FSN) XLCloudGrid5000FWF through project Y 904 START-Program 2015, Grid5000, Avalon, Myriads, Université de Bretagne Sud (UBS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National de Recherche en Informatique et en Automatique (Inria)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-CentraleSupélec-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Bretagne Sud (UBS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Faculdade de Engenharia, Aristotle University of Thessaloniki (GREECE), Centre National de la Recherche Scientifique - CNRS (FRANCE), Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE), Institut National de la Recherche en Informatique et en Automatique - INRIA (FRANCE), Institut National des Sciences Appliquées de Rennes - INSA (FRANCE), Norwegian University of Science and Technology - NTNU (NORWAY), Université Toulouse III - Paul Sabatier - UT3 (FRANCE), Université Toulouse - Jean Jaurès - UT2J (FRANCE), Université Toulouse 1 Capitole - UT1 (FRANCE), Poznan Supercomputing and Networking Center - PSNC (POLAND), Université de Bretagne Sud - UBS (FRANCE), Universität Wien (AUSTRIA), Universidad Carlos III de Madrid - UC3M (SPAIN), Universidad de La Laguna - ULL (SPAIN), Universidade do Porto - UP (PORTUGAL), Université de Rennes 1 (FRANCE), Institut de Recherche en Informatique de Toulouse - IRIT (Toulouse, France), Institut de Recherche en Informatique et Systèmes Aléatoires - IRISA (Rennes, France), Institut National Polytechnique de Toulouse - INPT (FRANCE), Universidad de La Laguna ( ULL ), Algorithms and Software Architectures for Distributed and HPC Platforms ( AVALON ), Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -Laboratoire de l'Informatique du Parallélisme ( LIP ), École normale supérieure - Lyon ( ENS Lyon ) -Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique ( Inria ) -Centre National de la Recherche Scientifique ( CNRS ) -École normale supérieure - Lyon ( ENS Lyon ) -Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique ( CNRS ), Laboratoire de l'Informatique du Parallélisme ( LIP ), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique ( Inria ) -Centre National de la Recherche Scientifique ( CNRS ), Departamento de matematica aplicada [Porto] ( LIACC ), University of Porto, Technical University of Vienna [Vienna] ( TU WIEN ), Institut de recherche en informatique de Toulouse ( IRIT ), Institut National Polytechnique [Toulouse] ( INP ) -Université Toulouse 1 Capitole ( UT1 ) -Université Toulouse - Jean Jaurès ( UT2J ) -Université Paul Sabatier - Toulouse 3 ( UPS ) -Centre National de la Recherche Scientifique ( CNRS ), Universidad Carlos III de Madrid [Madrid], Department of Electronics and Telecommunications [Norwegian University of Science and Technology], Norwegian University of Science and Technology [Trondheim] ( NTNU ), Poznan Supercomputing and Networking Center ( PSNC ), Poznan University of Technology, Design and Implementation of Autonomous Distributed Systems ( MYRIADS ), Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -SYSTÈMES LARGE ÉCHELLE ( IRISA_D1 ), Institut de Recherche en Informatique et Systèmes Aléatoires ( IRISA ), Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -Institut National des Sciences Appliquées - Rennes ( INSA Rennes ) -Université de Bretagne Sud ( UBS ) -École normale supérieure - Rennes ( ENS Rennes ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -CentraleSupélec-Centre National de la Recherche Scientifique ( CNRS ) -IMT Atlantique Bretagne-Pays de la Loire ( IMT Atlantique ) -Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -Institut National des Sciences Appliquées - Rennes ( INSA Rennes ) -Université de Bretagne Sud ( UBS ) -École normale supérieure - Rennes ( ENS Rennes ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -CentraleSupélec-Centre National de la Recherche Scientifique ( CNRS ) -IMT Atlantique Bretagne-Pays de la Loire ( IMT Atlantique ) -Institut de Recherche en Informatique et Systèmes Aléatoires ( IRISA ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -Institut National des Sciences Appliquées - Rennes ( INSA Rennes ) -Université de Bretagne Sud ( UBS ) -École normale supérieure - Rennes ( ENS Rennes ) -CentraleSupélec-Centre National de la Recherche Scientifique ( CNRS ) -IMT Atlantique Bretagne-Pays de la Loire ( IMT Atlantique ), École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS), Universidade do Porto = University of Porto, Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Toulouse Mind & Brain Institut (TMBI), Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), and Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique)

Subjects
Ultra large-scale systems, Monitoring, General Computer Science, Computer science, [ INFO.INFO-NI ] Computer Science [cs]/Networking and Internet Architecture [cs.NI], 020209 energy, energy-efficiency, Big data, Ultra-large-scale systems, Système d'exploitation, Réseaux et télécommunications, Engenharia electrotécnica, electrónica e informática [Ciências da engenharia e tecnologias], 02 engineering and technology, Bottleneck, [INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI], [ INFO.INFO-DC ] Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], Architectures Matérielles, Computer engineering, Electrical engineering, Electronic engineering, Information engineering, 0202 electrical engineering, electronic engineering, information engineering, energy-awareness, Electrical and Electronic Engineering, Simulation, Block (data storage), Energy-efficiency, business.industry, Information and Computer Science, Systèmes embarqués, Electrical engineering, Electronic engineering, Information engineering [Engineering and technology], monitoring, Engenharia de computadores, Engenharia electrotécnica, electrónica e informática, Risk analysis (engineering), Information technology management, Sustainability, [INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], business, Energy-awareness, Efficient energy use
Abstract

International audience; An Ultrascale System (USS) joins parallel and distributed computing systems that will be two to three orders of magnitude larger than today's infrastructure regarding scale, performance, the number of components and their complexity. For such systems to become a reality, however, advances must be made in High Performance Computing (HPC), large-scale distributed systems, and big data solutions, also tackling challenges such as improving the energy efficiency of the IT infrastructure. Monitoring the power consumed by underlying IT resources is essential towards optimising the manner IT resources are used and hence improve the sustainability of such systems. Nevertheless, monitoring the energy consumed by USSs is a challenging endeavour as the system can comprise thousands of heterogeneous server resources spanning multiple data centres. Moreover, the amount of monitoring data, its gathering, and processing , should never become a bottleneck nor profoundly impact the energy efficiency of the overall system. This work surveys state of the art on energy monitoring of large-scale systems and methodologies for monitoring the power consumed by large systems and discusses some of the challenges to be addressed towards monitoring and improving the energy efficiency of USSs. Next, we present efforts made on designing monitoring solutions. Finally, we discuss potential gaps in existing solutions when tackling emerging large-scale monitoring scenarios and present some directions for future research on the topic.

Published
2018

42. Energy aware ultrascale systems

Author

Neki Frasheri, Ariel Oleksiak, Pedro Alonso, Wojciech Piatek, Benson K. Muite, Vincenzo De Maio, Anne-Cécile Orgerie, Victor M. Garcia, Joel Guerrero, Alexey Lastovetsky, Patricia Stolf, Sebastien Lafond, Enida Sheme, Radu Prodan, Laurent Lefèvre, Georges Da Costa, Ravi Reddy Manumachu, Sébastien Varrette, Jean-Marc Pierson, Poznan Supercomputing and Networking Center, Laboratoire de l'Informatique du Parallélisme (LIP), Centre National de la Recherche Scientifique (CNRS)-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École normale supérieure - Lyon (ENS Lyon), Algorithms and Software Architectures for Distributed and HPC Platforms (AVALON), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire de l'Informatique du Parallélisme (LIP), Université de Lyon-École normale supérieure - Lyon (ENS Lyon)-Centre National de la Recherche Scientifique (CNRS)-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Universitat Politècnica de València (UPV), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées, University of Vienna [Vienna], Polytechnic University of Tirana, University of Genoa (UNIGE), Åbo Akademi University [Turku], School of Computer Science and Informatics [Dublin], University College Dublin [Dublin] (UCD), University of Tartu, Design and Implementation of Autonomous Distributed Systems (MYRIADS), Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-SYSTÈMES LARGE ÉCHELLE (IRISA-D1), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes 1 (UR1), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Centre National de la Recherche Scientifique (CNRS), Poznan Supercomputing and Networking Center (PSNC), Alpen-Adria-Universität Klagenfurt [Klagenfurt, Austria], Système d’exploitation, systèmes répartis, de l’intergiciel à l’architecture (IRIT-SEPIA), Institut de recherche en informatique de Toulouse (IRIT), Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse 1 Capitole (UT1), Computer Science and Communications Research Unit [Luxembourg] (CSC), Laboratory of Advanced Software SYstems [Luxembourg] (LASSY), Université du Luxembourg (Uni.lu)-Université du Luxembourg (Uni.lu), École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), Université de Toulouse (UT), Università degli studi di Genova = University of Genoa (UniGe), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Toulouse Mind & Brain Institut (TMBI), Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), and Université de Toulouse (UT)-Université Toulouse Capitole (UT Capitole)

Subjects
Computer science, energy models, media_common.quotation_subject, Quality of service, energy monitoring, Energy consumption, energy simulation, energy aware software, sustainability, heterogeneous systems, 7. Clean energy, Reliability engineering, Data sharing, Data access, energy consumption, Quality (business), [INFO]Computer Science [cs], [INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], Resilience (network), Energy (signal processing), media_common, Efficient energy use, energy efficiency metrics
Abstract

International audience; Energy consumption is one of the main limiting factors for the design of ultrascale infrastructures. Multi-level hardware and software optimizations must be designed and explored in order to reduce energy consumption for these largescale equipment. This chapter addresses the issue of energy efficiency of ultrascale systems in front of other quality metrics. The goal of this chapter is to explore the design of metrics, analysis, frameworks and tools for putting energy awareness and energy efficiency at the next stage. Significant emphasis will be placed on the idea of “energy complexity,” reflecting the synergies between energy efficiency and quality of service, resilience and performance, by studying computation power, communication/data sharing power, data access power, algorithm energy consumption, etc.

Published
2019

43. M2DC—A Novel Heterogeneous Hyperscale Microserver Platform

Author

William Fornaciari, Robert Plestenjak, Lennart Tigges, Carlo Brandolese, Wolfgang Christmann, Jean-Marc Philippe, René Griessl, Christian Pieper, Alessandro Barenghi, Mario Porrmann, Michal Kierzynka, Javier Setoain, Joao Pita Costa, Luca Ceva, Justin Cinkelj, Holm Rauchfuss, Loïc Cudennec, Jens Hagemeyer, Udo Janssen, Mariano Cecowski, Stefan Krupop, Daniel Schlitt, Chris Adeniyi-Jones, Sven Rosinger, Giovanni Agosta, Meysam Peykanu, Gerardo Pelosi, Wojciech Piatek, Thierry Goubier, Ariel Oleksiak, and Micha vor dem Berge

Subjects
Computer science, business.industry, Hyperscale, 02 engineering and technology, Microservices, Multi many cores, Modular design, run time management, 03 medical and health sciences, 0302 clinical medicine, Software, Middleware, Embedded system, HPC, 0202 electrical engineering, electronic engineering, information engineering, Dependability, 020201 artificial intelligence & image processing, Data center, power optimizaton, business, Adaptation (computer science), 030217 neurology & neurosurgery, Multi many cores, run time management, power optimizaton, HPC
Abstract

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.

Published
2019
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44. Top-Down Characterization Approximation based on performance counters architecture for AMD processors

Author

Mateusz Jarus and Ariel Oleksiak

Subjects
010302 applied physics, Computer science, Process (computing), 02 engineering and technology, Parallel computing, Top-down and bottom-up design, Characterization (mathematics), 01 natural sciences, 020202 computer hardware & architecture, Microarchitecture, Software portability, Hardware and Architecture, Modeling and Simulation, 0103 physical sciences, 0202 electrical engineering, electronic engineering, information engineering, Architecture, Software, Efficient energy use
Abstract

Due to the increasing complexity of the processors, developers often seek for tools that would simplify the process of finding bottlenecks while executing applications. Although more and more data may be collected from processors, usually much detailed knowledge about the internals of a given architecture is required to understand them. This paper introduces a Top-Down Characterization Approximation for the analysis of applications performance executed on AMD processors and is an extension of a Top-Down Method initially developed by Intel. Since not all required performance counters are available on AMD processors to calculate the exact values of metrics, this method was named as an approximation. It allows one to get a deeper understanding of different stages of program execution, compare different architectures and identify bottlenecks in out-of-order processors. It hides from the user the complexity of microarchitecture details and at the same time exposes the main contributors of inefficient program execution. This method aims at defining a few main metrics on top of performance counters to easily locate the main efficiency issues. At this time this method was applied to Intel processors only. The main reason behind it was the fact that it uses designated performance counters that are unique among different processors and its portability is not straightforward. Positive feedback from users encouraged the authors to develop a similar technique for AMD processors.

Published
2016

45. Minimising energy costs of data centers using high dense heterogeneous systems and intelligent resource management

Author

Wojciech Piatek, Michal Kierzynka, Tomasz Ciesielczyk, and Ariel Oleksiak

Subjects
Power management, 021103 operations research, business.industry, Computer science, Distributed computing, 020208 electrical & electronic engineering, 0211 other engineering and technologies, 02 engineering and technology, Energy consumption, 7. Clean energy, 0202 electrical engineering, electronic engineering, information engineering, Data center, Resource management, Enhanced Data Rates for GSM Evolution, Adaptation (computer science), business, Energy (signal processing), Efficient energy use
Abstract

Recent trends in data centers include on one hand consolidation in large data centers and on the other hand increased number of small edge systems located closer to sources of data or energy. In both cases the key features needed to minimise costs are efficiency, adaptation to changing load and external conditions, and highly autonomous management. Additionally, especially in small edge data centers, efficiency and performance can be often optimized for specific applications. However, dynamic management and achieving efficiency gains for platforms containing a significant number of heterogeneous server nodes in a limited space require appropriate management methods. For example, suspending individual components and proper allocation of nodes becomes crucial to achieve high efficiency. In this paper we present a microserver system and demonstrate how much data center operator can gain in terms of overall costs by applying such systems with a special focus on intelligent power management techniques. In particular, we propose the novel power capping method that takes into account dynamic priorities, efficiency of specific types of heterogeneous server nodes, and impact of power capping on efficiency of specific applications. In this way, it both keeps the requested power usage levels as well as to reduce the overall energy consumption. Proposed architecture and management methods jointly allow to save around 30% of energy costs in a data center.

Published
2018

46. Converting Data Centers in Energy Flexibility Ecosystems

Author

Maria Adele Paglia, Vasiliki Georgiadou, Terpsichori-Helen Velivassaki, Claudia Pop, Nicolas Saintherant, Ariel Oleksiak, Ionut Anghel, Artemis Voulkidis, Massimo Bertoncini, and Tudor Cioara

Subjects
Flexibility (engineering), Computer science, business.industry, 020206 networking & telecommunications, 02 engineering and technology, Environmental economics, 7. Clean energy, Renewable energy, Power (physics), Smart grid, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Data center, Ecosystem, business, Energy (signal processing), Efficient energy use
Abstract

This paper presents a novel Data Center (DC) flexibility ecosystem, which aims to accelerate the commercial utilization of innovative energy efficiency solutions and on-site integration of renewable energy generation in DCs. The proposed ecosystem leverages on providing mutualized energy flexibility services to power and heat energy grids, while contributing to increased resiliency and security of the power supply.

Published
2018
Full Text
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49. M2DC-Modular Microserver DataCentre with heterogeneous hardware

Author

Wojciech Piatek, René Griessl, Carlo Brandolese, Lennart Tigges, Loïc Cudennec, Michal Kierzynka, Mariano Cecowski, Daniel Schlitt, Javier Setoain, Sven Rosinger, Jens Hagemeyer, Mario Porrmann, Stefan Krupop, Jean-Marc Philippe, Alessandro Barenghi, Wolfgang Christmann, Chris Adeniyi-Jones, Gerardo Pelosi, Thierry Goubier, Luca Ceva, Christian Pieper, Ariel Oleksiak, Justin Cinkelj, Micha vor dem Berge, Jan Lachmair, Alexandre Carbon, Meysam Peykanu, Robert Plestenjak, Giovanni Agosta, Udo Janssen, William Fornaciari, Poznan Supercomputing and Networking Center (PSNC), Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB), Politecnico di Milano [Milan] (POLIMI), XLAB d.o.o., XLAB, Cognitive Interaction Technology [Bielefeld] (CITEC), Universität Bielefeld = Bielefeld University, Christmann Informationstechnik + Medien (GERMANY), Département d'Architectures, Conception et Logiciels Embarqués-LIST (DACLE-LIST), Laboratoire d'Intégration des Systèmes et des Technologies (LIST), Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Institute for Information Technology [Oldenburg] (OFFIS), ARM Ltd [Cambridge] (ARM), European Project: 688201,H2020,H2020-ICT-2015,M2DC(2016), and Laboratoire d'Intégration des Systèmes et des Technologies (LIST (CEA))

Subjects
Focus (computing), Microservers, Computer Networks and Communications, Computer science, business.industry, Heterogeneous architectures, 02 engineering and technology, Modular design, computer.software_genre, Data Centres, [SPI]Engineering Sciences [physics], Software, Artificial Intelligence, Hardware and Architecture, 020204 information systems, 0202 electrical engineering, electronic engineering, information engineering, Operating system, 020201 artificial intelligence & image processing, Data center, [INFO]Computer Science [cs], business, computer
Abstract

International audience; The Modular Microserver DataCentre (M2DC) project investigates, develops and demonstrates a modular, highly-efficient, cost-optimized server architecture composed of heterogeneous microserver computing resources. The resulting server architecture will be able to be tailored to meet requirements from a wide range of application domains. M2DC is built on three main pillars: a flexible server architecture that can be easily customised, maintained and updated; advanced management strategies and system efficiency enhancements (SEE); well-defined interfaces to the surrounding software data centre ecosystem. In this paper, we focus in particular on the thermal management strategies and on the initial benchmarking of the Aarch64 ARM architecture.

Published
2017

50. Intelligent thermal management in M2DC system

Author

Ariel Oleksiak, Micha vor dem Berge, Jens Hagemeyer, Emmanuel Senechal, and Wojciech Piatek

Subjects
020203 distributed computing, Engineering, Chassis, business.industry, Reliability (computer networking), 02 engineering and technology, Energy consumption, 7. Clean energy, Energy accounting, 020202 computer hardware & architecture, Reliability engineering, Power usage effectiveness, Server, 0202 electrical engineering, electronic engineering, information engineering, Data center, business, Simulation, Efficient energy use
Abstract

Thermal management and cooling are essential parts that have significant influence on the energy efficiency of data centers as cost of cooling can exceed 50% of the whole energy data center energy consumption. Optimized thermal management of data center also affects reliability and availability of a data center due to prevention of creation of the so called hot spots. In this paper, we present a model and optimisation method for thermal management a server platform, developed within M2DC project, equipped with a high number of heterogeneous hardware. We also show how the management of the individual servers and chassis influences efficiency of the whole data center. First, we present how this affects the commonly used PUE metric and how this approach can be misleading in evaluation of the data center effectiveness. Secondly, we show how intelligent fan management may influence energy used for cooling, change of IT systems energy consumption and the overall gain.

Published
2017

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