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36 results on '"Stanisic, Luka"'

1. MPCDF HPC Performance Monitoring System: Enabling Insight via Job-Specific Analysis

Author

Stanisic, Luka and Reuter, Klaus

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing
Abstract

This paper reports on the design and implementation of the HPC performance monitoring system deployed to continuously monitor performance metrics of all jobs on the HPC systems at the Max Planck Computing and Data Facility (MPCDF). Thereby it reveals important information to various stakeholders, in particular to users, application support, system administrators, and management. On each compute node, hardware and software performance monitoring data is collected by our newly developed lightweight open-source hpcmd middleware which builds upon standard Linux tools. The data is transported via rsyslog, and aggregated and processed by a Splunk system, enabling detailed per-cluster and per-job interactive analysis in a web browser. Additionally, performance reports are provided to the users as PDF files. Finally, we report on practical experience and benefits from large-scale deployments on MPCDF HPC systems, demonstrating how our solution can be useful to any HPC center., Comment: 13 pages, 3 figures

Published
2019

2. Cross-validation tests for cryo-EM maps using an independent particle set

Author

Ortiz, Sebastian, Stanisic, Luka, Rodriguez, Boris A, Rampp, Markus, Hummer, Gerhard, and Cossio, Pilar

Subjects
Physics - Biological Physics, Quantitative Biology - Biomolecules
Abstract

Cryo-electron microscopy is a revolutionary technique that can provide 3D density maps at near-atomic resolution. However, map validation is still an open issue in the field. Despite several efforts from the community, it is possible to overfit the reconstructions to noisy data. Here, inspired by modern statistics, we develop a novel methodology that uses a small independent particle set to validate the 3D maps. The main idea is to monitor how the map probability evolves over the control set during the refinement. The method is complementary to the gold-standard procedure, which generates two reconstructions at each iteration. We low-pass filter the two reconstructions for different frequency cutoffs, and we calculate the probability of each filtered map given the control set. For high-quality maps, the probability should increase as a function of the frequency cutoff and of the refinement iteration. We also compute the similarity between the probability distributions of the two reconstructions. As higher frequencies are added to the maps, more dissimilar are the distributions. We optimized the BioEM software package to perform these calculations, and tested the method on several systems, some which were overfitted. Our results show that our method is able to discriminate the overfitted sets from the non-overfitted ones. We conclude that having a control particle set, not used for the refinement, is essential for cross-validating cryo-EM maps.

Published
2019

3. Platform independent profiling of a QCD code

Author

Marinkovic, Marina Krstic and Stanisic, Luka

Subjects
High Energy Physics - Lattice, Computer Science - Distributed, Parallel, and Cluster Computing, Physics - Computational Physics
Abstract

The supercomputing platforms available for high performance computing based research evolve at a great rate. However, this rapid development of novel technologies requires constant adaptations and optimizations of the existing codes for each new machine architecture. In such context, minimizing time of efficiently porting the code on a new platform is of crucial importance. A possible solution for this common challenge is to use simulations of the application that can assist in detecting performance bottlenecks. Due to prohibitive costs of classical cycle-accurate simulators, coarse-grain simulations are more suitable for large parallel and distributed systems. We present a procedure of implementing the profiling for openQCD code [1] through simulation, which will enable the global reduction of the cost of profiling and optimizing this code commonly used in the lattice QCD community. Our approach is based on well-known SimGrid simulator [2], which allows for fast and accurate performance predictions of HPC codes. Additionally, accurate estimations of the program behavior on some future machines, not yet accessible to us, are anticipated.

Published
2017

4. Correlation of Near-Infrared Spectroscopy (NIRS) with Invasive Arterial Pressure Monitoring during Aortic Coarctation Surgery in Pediatric Patients.

Author

Pjevalica Dragic, Jelena, Zecevic, Tatjana, Divac, Ivan, Pavlovic, Andrija, Bisenic, Dejan, Stanisic, Luka, Kalanj, Jasna, Stefanovic, Igor, Nikolic, Dejan, Petrov, Ivana, and Milovanovic, Vladimir

Subjects
PEARSON correlation (Statistics), RESEARCH funding, AORTIC coarctation, NEAR infrared spectroscopy, RETROSPECTIVE studies, DESCRIPTIVE statistics, ARTERIAL pressure, PEDIATRICS, LONGITUDINAL method, MEDICAL records, ACQUISITION of data, DATA analysis software, COMORBIDITY, CHILDREN
Abstract

Aortic coarctation surgery in pediatric patients requires the placement of two arterial cannulas to monitor pressure gradients and surgical correction adequacy. Near-infrared spectroscopy (NIRS) monitoring provides insight into regional blood flow. This study aimed to investigate the correlation between NIRS values and invasive arterial pressures, exploring NIRS monitoring as a potential substitute for arterial cannulation. In a cohort of 21 consecutive pediatric patients undergoing aortic coarctation surgery, recordings of NIRS and invasive arterial pressure values were evaluated at various time intervals. Pearson correlation evaluated the relationship between NIRS values and invasively measured arterial pressures. Moderate to strong correlations were observed between the mean arterial pressure (MAP) of the upper and lower arteries and cerebral (rSO2-C) and somatic (rSO2-S) NIRS values 5 min after cross-clamp placement (r = 0.621, p = 0.003; r = 0.757, p < 0.001). Strong correlations were found 15 min after cross-clamp placement (r = 0.828, p = 0.002; r = 0.783, p = 0.004). Before transfer to the ICU, a strong correlation existed between the upper artery MAP and rSO2-C (r = 0.730, p < 0.001), but there was no correlation between the lower artery MAP and rSO2-S. These findings are promising, but further studies are required to validate it as a reliable substitute for invasive pressure monitoring in this patient population. [ABSTRACT FROM AUTHOR]

Published
2024
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5. MPCDF HPC Performance Monitoring System: Enabling Insight via Job-Specific Analysis

Author

Stanisic, Luka, Reuter, Klaus, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Schwardmann, Ulrich, editor, Boehme, Christian, editor, B. Heras, Dora, editor, Cardellini, Valeria, editor, Jeannot, Emmanuel, editor, Salis, Antonio, editor, Schifanella, Claudio, editor, Manumachu, Ravi Reddy, editor, Schwamborn, Dieter, editor, Ricci, Laura, editor, Sangyoon, Oh, editor, Gruber, Thomas, editor, Antonelli, Laura, editor, and Scott, Stephen L., editor

Published
2020
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7. Effective Reproducible Research with Org-Mode and Git

Author

Stanisic, Luka, Legrand, Arnaud, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Kobsa, Alfred, Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Lopes, Luís, editor, Žilinskas, Julius, editor, Costan, Alexandru, editor, Cascella, Roberto G., editor, Kecskemeti, Gabor, editor, Jeannot, Emmanuel, editor, Cannataro, Mario, editor, Ricci, Laura, editor, Benkner, Siegfried, editor, Petit, Salvador, editor, Scarano, Vittorio, editor, Gracia, José, editor, Hunold, Sascha, editor, Scott, Stephen L., editor, Lankes, Stefan, editor, Lengauer, Christian, editor, Carretero, Jesus, editor, Breitbart, Jens, editor, and Alexander, Michael, editor

Published
2014
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8. Modeling and Simulation of a Dynamic Task-Based Runtime System for Heterogeneous Multi-core Architectures

Author

Stanisic, Luka, Thibault, Samuel, Legrand, Arnaud, Videau, Brice, Méhaut, Jean-François, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Kobsa, Alfred, Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Silva, Fernando, editor, Dutra, Inês, editor, and Santos Costa, Vítor, editor

Published
2014
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9. Faithful Performance Prediction of a Dynamic Task-based Runtime System, an Opportunity for Task Graph Scheduling

Author

Thibault, Samuel, Stanisic, Luka, Legrand, Arnaud, STatic Optimizations, Runtime Methods (STORM), Laboratoire Bordelais de Recherche en Informatique (LaBRI), 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 de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Performance analysis and optimization of LARge Infrastructures and Systems (POLARIS), 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 d'Informatique de Grenoble (LIG), Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), and 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

Subjects
[INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2020

11. Simulation of a Sparse Direct Solver on Heterogeneous Systems using Starpu and Simgrid

Author

Agullo, Emmanuel, Buttari, Alfredo, Guermouche, Abdou, Legrand, Arnaud, Masliah, Ian, Stanisic, Luka, High-End Parallel Algorithms for Challenging Numerical Simulations (HiePACS), Laboratoire Bordelais de Recherche en Informatique (LaBRI), 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 de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Algorithmes Parallèles et Optimisation (IRIT-APO), 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, Centre National de la Recherche Scientifique (CNRS), Performance analysis and optimization of LARge Infrastructures and Systems (POLARIS ), 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 d'Informatique de Grenoble (LIG ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), 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, 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), and Université de Toulouse (UT)

Subjects
[INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], ComputingMilieux_MISCELLANEOUS, [MATH.MATH-NA]Mathematics [math]/Numerical Analysis [math.NA]
Abstract

International audience

Published
2019

13. Méthode des multipôles rapide à base de tâches pour des clusters de processeurs multicoeurs

Author

Agullo, Emmanuel, Bramas, Bérenger, Coulaud, Olivier, Khannouz, Martin, Stanisic, Luka, 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), Max Planck Computing and Data Facility [Garching] (MPCDF), STatic Optimizations, Runtime Methods (STORM), Inria Bordeaux Sud-Ouest, plafrim, and 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

Subjects
architecture multicœur, hybrid parallelization, méthode multipôles rapide, Calcul haute performance, moteur d’exécution, fast multipole method, OpenMP, high performance computing (HPC), runtime system, programmation à base de tâches, multicore processor, parallélisation hybride, task-based programming, FMM, MPI, [INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], cluster
Abstract

Most high-performance, scientific libraries have adopted hybrid parallelization schemes - such as the popular MPI+OpenMP hybridization - to benefit from the capacities of modern distributed-memory machines. While these approaches have shown to achieve high performance, they require a lot of effort to design and maintain sophisticated synchronization/communication strategies. On the other hand, task-based programming paradigms aim at delegating this burden to a runtime system for maximizing productivity. In this article, we assess the potential of task-based fast multipole methods (FMM) on clusters of multicore processors. We propose both a hybrid MPI+task FMM parallelization and a pure task-based parallelization where the MPI communications are implicitly handled by the runtime system. The latter approach yields a very compact code following a sequential task-based programming model. We show that task-based approaches can compete with a hybrid MPI+OpenMP highly optimized code and that furthermore the compact task-based scheme fully matches the performance of the sophisticated, hybrid MPI+task version, ensuring performance while maximizing productivity. We illustrate our discussion with the ScalFMM FMM library and the StarPU runtime system.; La plupart des bibliothèques scientifiques très performantes ont adopté des parallélisations hybrides - comme l’approche MPI+OpenMP - pour profiter des capacités des machines modernes à mémoire distribuée. Ces approches permettent d’obtenir de très hautes performances, mais elles nécessitent beaucoup d’efforts pour concevoir et pour maintenir des stratégies de synchronisation/communication sophistiquées. D’un autre côté, les paradigmes de programmation à base de tâches visent à déléguer ce fardeau à un moteur d'exécution pour maximiser la productivité. Dans cet article, nous évaluons le potentiel de la méthode des multipôles rapide (FMM) à base de tâches sur les clusters de processeurs multic\oe{}urs. Nous proposons deux types de parallélisation, une première approche hybride (MPI+Tâche) à base de tâches et d’appels à MPI pour gérer explicitement les communications et la deuxième uniquement à base de tâches où les communications MPI sont implicitement postées par le moteur d'exécution. Cette dernière approche conduit à un code très compact qui suit le modèle de programmation séquentiel à base de tâches. Nous montrons que cette approche rivalise avec le code hybride MPI+OpenMP fortement optimisé et qu'en outre le code compact atteint les performances de la version hybride MPI+Tâche, assurant une très haute performance tout en maximisant la productivité. Nous illustrons notre propos avec la bibliothèque FMM ScalFMM et le moteur d'exécution StarPU.

Published
2017

14. Task-based fast multipole method for clusters of multicore processors

Author

Agullo, Emmanuel, Bramas, Bérenger, Coulaud, Olivier, Khannouz, Martin, Stanisic, Luka, High-End Parallel Algorithms for Challenging Numerical Simulations (HiePACS), Laboratoire Bordelais de Recherche en Informatique (LaBRI), 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 de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Max Planck Computing and Data Facility [Garching] (MPCDF), STatic Optimizations, Runtime Methods (STORM), Inria Bordeaux Sud-Ouest, and plafrim

Subjects
architecture multicœur, hybrid parallelization, méthode multipôles rapide, Calcul haute performance, moteur d’exécution, fast multipole method, OpenMP, high performance computing (HPC), runtime system, programmation à base de tâches, multicore processor, parallélisation hybride, task-based programming, FMM, MPI, [INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], cluster
Abstract

Most high-performance, scientific libraries have adopted hybrid parallelization schemes - such as the popular MPI+OpenMP hybridization - to benefit from the capacities of modern distributed-memory machines. While these approaches have shown to achieve high performance, they require a lot of effort to design and maintain sophisticated synchronization/communication strategies. On the other hand, task-based programming paradigms aim at delegating this burden to a runtime system for maximizing productivity. In this article, we assess the potential of task-based fast multipole methods (FMM) on clusters of multicore processors. We propose both a hybrid MPI+task FMM parallelization and a pure task-based parallelization where the MPI communications are implicitly handled by the runtime system. The latter approach yields a very compact code following a sequential task-based programming model. We show that task-based approaches can compete with a hybrid MPI+OpenMP highly optimized code and that furthermore the compact task-based scheme fully matches the performance of the sophisticated, hybrid MPI+task version, ensuring performance while maximizing productivity. We illustrate our discussion with the ScalFMM FMM library and the StarPU runtime system.; La plupart des bibliothèques scientifiques très performantes ont adopté des parallélisations hybrides - comme l’approche MPI+OpenMP - pour profiter des capacités des machines modernes à mémoire distribuée. Ces approches permettent d’obtenir de très hautes performances, mais elles nécessitent beaucoup d’efforts pour concevoir et pour maintenir des stratégies de synchronisation/communication sophistiquées. D’un autre côté, les paradigmes de programmation à base de tâches visent à déléguer ce fardeau à un moteur d'exécution pour maximiser la productivité. Dans cet article, nous évaluons le potentiel de la méthode des multipôles rapide (FMM) à base de tâches sur les clusters de processeurs multic\oe{}urs. Nous proposons deux types de parallélisation, une première approche hybride (MPI+Tâche) à base de tâches et d’appels à MPI pour gérer explicitement les communications et la deuxième uniquement à base de tâches où les communications MPI sont implicitement postées par le moteur d'exécution. Cette dernière approche conduit à un code très compact qui suit le modèle de programmation séquentiel à base de tâches. Nous montrons que cette approche rivalise avec le code hybride MPI+OpenMP fortement optimisé et qu'en outre le code compact atteint les performances de la version hybride MPI+Tâche, assurant une très haute performance tout en maximisant la productivité. Nous illustrons notre propos avec la bibliothèque FMM ScalFMM et le moteur d'exécution StarPU.

Published
2017

15. Modeling Irregular Kernels of Task-based codes: Illustration with the Fast Multipole Method

Author

Agullo, Emmanuel, Bramas, Bérenger, Coulaud, Olivier, Stanisic, Luka, Thibault, Samuel, STatic Optimizations, Runtime Methods (STORM), Laboratoire Bordelais de Recherche en Informatique (LaBRI), 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 de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), High-End Parallel Algorithms for Challenging Numerical Simulations (HiePACS), Max Planck Computing and Data Facility [Garching] (MPCDF), INRIA Bordeaux, PLAFRIM, and 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

Subjects
Mathematical Software, Modeling and simulation, task-based programming, fast multipole method, Parallel computing methodologies, runtime system, [INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC]
Abstract

The significant increase of the hardware complexity that occurred in the last few years led the high performance community to design many scientific libraries according to a task-based parallelization. The modeling of the performance of the individual tasks (or kernels) they are composed of is crucial for facing multiple challenges as diverse as performing accurate performance predictions, designing robust scheduling algorithms, tuning the applications, etc. Fine-grain modeling such as emulation and cycle-accurate simulation may lead to very accurate results. However, not only their high cost may be prohibitive but they furthermore require a high fidelity modeling of the processor, which makes them hard to deploy in practice. In this paper, we propose an alternative coarse-grain, empirical methodology oblivious to both the target code and the hardware architecture, which leads to robust and accurate timing predictions. We illustrate our approach with a task-based Fast Multipole Method (FMM) algorithm, whose kernels are highly irregular, implemented in the \scalfmm library on top of the starpu task-based runtime system and the simgrid simulator.; L'augmentation significative de la complexité matérielle qui s'est produite ces quelques dernières années a amené la communauté de calcul haute performance à mettre au point de nombreuses bibliothèques scientifiques sur le principe d'une parallélisation à base de tâches. La modélisation de la performance des tâches individuelles (ou noyaux) qui les composent est cruciale pour faire face aux multiples challenges aussi variés que la réalisation de prédictions de performance précises, la mise au point d'algorithme d'ordonnancement robustes, l'optimisation des applications, etc. La modélisation à grain fin tel que l'émulation et la simulation à la précision du cycle peut permettre des résultats très précis. Toutefois, non seulement leur coût élevé peut être prohibitif mais elles requièrent de surcroît une modélisation très fidèle du processeur, ce qui les rend difficiles à déployer en pratique. Dans ce papier, nous proposons une méthodologie alternative, à plus gros grain, empirique, transparente à la fois pour le code et l'architecture cibles, ce qui permet des prédictions robustes et précises. Nous illustrons notre approche avec une méthode méthode multipolaire rapide (FMM) à base de tâches, dont les noyaux sont hautement irréguliers, implémentée dans la librairie ScalFMM au-dessus du moteur d'exécution StarPU et du simulateur SimGrid.

Published
2017

16. Analyzing Dynamic Task-Based Applications on Hybrid Platforms: An Agile Scripting Approach

Author

Garcia Pinto, Vinicius, Stanisic, Luka, Legrand, Arnaud, Mello Schnorr, Lucas, Thibault, Samuel, Danjean, Vincent, Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Universidade Federal do Rio Grande do Sul [Porto Alegre] (UFRGS), STatic Optimizations, Runtime Methods (STORM), Laboratoire Bordelais de Recherche en Informatique (LaBRI), 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 de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), High-End Parallel Algorithms for Challenging Numerical Simulations (HiePACS), Performance analysis and optimization of LARge Infrastructures and Systems (POLARIS ), 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 d'Informatique de Grenoble (LIG ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), PlaFRIM, IN2P3, Grid5000, ANR-11-INFR-0013,SONGS,Simulation de systèmes de prochaine génération(2011), European Project: 689772,H2020 Pilier Industrial Leadership,H2020-EUB-2015,HPC4E(2015), and 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

Subjects
020203 distributed computing, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, 02 engineering and technology, [INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC]
Abstract

Held in conjunction with SC16; International audience; In this paper, we present visual analysis techniques to evaluate the performance of HPC task-based applications on hybrid architectures. Our approach is based on composing modern data analysis tools (pjdump, R, ggplot2, plotly), enabling an agile and flexible scripting framework with minor development cost. We validate our proposal by analyzing traces from the full-fledged implementation of the Cholesky decomposition available in the MORSE library running on a hybrid (CPU/GPU) platform. The analysis compares two different workloads and three different task schedulers from the StarPU runtime system. Our analysis based on composite views allows to identify allocation mistakes, priority problems in scheduling decisions, GPU tasks anomalies causing bad performance, and critical path issues.

Published
2016

21. A Reproducible Research Methodology for Designing and Conducting Faithful Simulations of Dynamic HPC Applications

Author

Stanisic, Luka, Laboratoire d'Informatique de Grenoble (LIG), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF), Université Grenoble Alpes, Jean-François Méhaut, and Arnaud Legrand

Subjects
Performance Evaluation, Méthodologie, Runtime, Recherche Reproducible, Évaluation de performances, Hpc, Methodology, Reproducible Research, [INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], Simulation
Abstract

The evolution of High-Performance Computing systems has taken asharp turn in the last decade. Due to the enormous energyconsumption of modern platforms, miniaturization and frequencyscaling of processors have reached a limit. The energy constraintshas forced hardware manufacturers to develop alternative computerarchitecture solutions in order to manage answering the ever-growingneed of performance imposed by the scientists and thesociety. However, efficiently programming such diversity ofplatforms and fully exploiting the potentials of the numerousdifferent resources they offer is extremely challenging. Thepreviously dominant trend for designing high performanceapplications, which was based on large monolithic codes offeringmany optimization opportunities, has thus become more and moredifficult to apply since implementing and maintaining such complexcodes is very difficult. Therefore, application developersincreasingly consider modular approaches and dynamic applicationexecutions. A popular approach is to implement the application at ahigh level independently of the hardware architecture as DirectedAcyclic Graphs of tasks, each task corresponding to carefullyoptimized computation kernels for each architecture. A runtimesystem can then be used to dynamically schedule those tasks on thedifferent computing resources.Developing such solutions and ensuring their good performance on awide range of setups is however very challenging. Due to the highcomplexity of the hardware, to the duration variability of theoperations performed on a machine and to the dynamic scheduling ofthe tasks, the application executions are non-deterministic and theperformance evaluation of such systems is extremelydifficult. Therefore, there is a definite need for systematic andreproducible methods for conducting such research as well asreliable performance evaluation techniques for studying thesecomplex systems.In this thesis, we show that it is possible to perform a clean,coherent, reproducible study, using simulation, of dynamic HPCapplications. We propose a unique workflow based on two well-knownand widely-used tools, Git and Org-mode, for conducting areproducible experimental research. This simple workflow allows forpragmatically addressing issues such as provenance tracking and dataanalysis replication. Our contribution to the performance evaluationof dynamic HPC applications consists in the design and validation ofa coarse-grain hybrid simulation/emulation of StarPU, a dynamictask-based runtime for hybrid architectures, over SimGrid, aversatile simulator for distributed systems. We present how thistool can achieve faithful performance predictions of nativeexecutions on a wide range of heterogeneous machines and for twodifferent classes of programs, dense and sparse linear algebraapplications, that are a good representative of the real scientificapplications.; L'évolution de l'informatique haute performance s'est réorientée au cours de cette dernière décennie. L'importante consommation énergétique des plates-formes modernes limite fortement la miniaturisation et l'augmentation des fréquences des processeurs. Cette contrainte énergétique a poussé les fabricants de matériels à développer de nombreuses architectures alternatives afin de répondre au besoin croissant de performance imposé par la communauté scientifique. Cependant, programmer efficacement sur une telle diversité de plate-formes et exploiter l'intégralité des ressources qu'elles offrent s'avère d'une grande difficulté. La tendance générale de conception d'application haute performance, basée sur un gros code monolithique offrant de nombreuses opportunités d'optimisation, est ainsi devenu de plus en plus difficile à appliquer en raison de la difficulté d'implémentation et de maintenance de ces codes complexes. Par conséquent, les développeurs de telles applications considèrent maintenant une approche plus modulaire et une exécution dynamique de celles-ci. Une approche populaire est d'implémenter ces applications à plus haut niveau, indépendamment de l'architecture matérielle, suivant un graphe de tâches où chacune d'entre elles correspond à un noyau de calcul soigneusement optimisé pour chaque architecture. Un système de runtime peut ensuite être utilisé pour ordonnancer dynamiquement ces tâches sur les ressources de calcul.Développer ces solutions et assurer leur bonne performance sur un large spectre de configurations reste un défit majeur. En raison de la grande complexité du matériel, de la variabilité des temps d'exécution des calculs et de la dynamicité d'ordonnancement des tâches, l'exécution des applications n'est pas déterministe et l'évaluation de la performance de ces systèmes est très difficile. Par conséquent, il y a un besoin de méthodes systématiques et reproductibles pour la conduite de recherche ainsi que de techniques d'évaluation de performance fiables pour étudier ces systèmes complexes.Dans cette thèse, nous montrons qu'il est possible de mettre en place une étude propre, cohérente et reproductible, par simulation, d'applications dynamiques. Nous proposons une méthode de travail unique basée sur deux outils connus, Git et Org-mode, pour la conduite de recherche expérimentale reproductible. Cette méthode simple permet une résolution pragmatique de problèmes comme le suivi de la provenance ou la réplication de l'analyse des données. Notre contribution à l'évaluation de performance des applications dynamiques consiste au design et à la validation de simulation/émulation hybride gros-grain de StarPU, un runtime dynamique basé sur un graphe de tâches pour architecture hybride, au dessus de SimGrid, un simulateur polyvalent pour systèmes distribués. Nous présentons comment notre solution permet l'obtention de prédictions fiables de performances d'exécutions réelles dans un large panel de machines hétérogènes sur deux classes de programme différentes, des applications d'algèbre linéaire dense et creuse, qui sont représentatives des applications scientifiques.

Published
2015

23. Faithful Performance Prediction of a Dynamic Task-Based Runtime System for Heterogeneous Multi-Core Architectures

Author

Stanisic, Luka, Thibault, Samuel, Legrand, Arnaud, Videau, Brice, Méhaut, Jean-François, Middleware efficiently scalable (MESCAL), 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 d'Informatique de Grenoble (LIG), Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Informatique de Grenoble (LIG), Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS), STatic Optimizations, Runtime Methods (STORM), 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), Université de Bordeaux (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS), Compiler Optimization and Run-time Systems (CORSE), PlaFRIM (https://plafrim.bordeaux.inria.fr/doku.php), ANR-11-INFR-0013,SONGS,Simulation de systèmes de prochaine génération(2011), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Inria Grenoble - Rhône-Alpes, Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF), 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, Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB), and Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)

Subjects
HPC, Starpu-simgrid, simgrid, simulations, [INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], runtimes
Abstract

International audience; SUMMARY Multi-core architectures comprising several GPUs have become mainstream in the field of High-Performance Computing. However, obtaining the maximum performance of such heterogeneous machines is challenging as it requires to carefully offload computations and manage data movements between the different processing units. The most promising and successful approaches so far build on task-based runtimes that abstract the machine and rely on opportunistic scheduling algorithms. As a consequence, the problem gets shifted to choosing the task granularity, task graph structure, and optimizing the scheduling strategies. Trying different combinations of these different alternatives is also itself a challenge. Indeed, getting accurate measurements requires reserving the target system for the whole duration of experiments. Furthermore, observations are limited to the few available systems at hand and may be difficult to generalize. In this article, we show how we crafted a coarse-grain hybrid simulation/emulation of StarPU, a dynamic runtime for hybrid architectures, over SimGrid, a versatile simulator of distributed systems. This approach allows to obtain performance predictions of classical dense linear algebra kernels accurate within a few percents and in a matter of seconds, which allows both runtime and application designers to quickly decide which optimization to enable or whether it is worth investing in higher-end GPUs or not. Additionally, it allows to conduct robust and extensive scheduling studies in a controlled environment whose characteristics are very close to real platforms while having reproducible behavior.

Published
2015

24. Writing a Reproducible Article

Author

Stanisic, Luka, Legrand, Arnaud, Middleware efficiently scalable (MESCAL), Laboratoire d'Informatique de Grenoble (LIG), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF), Pascal Felber, Laurent Philippe, Etienne Riviere, Arnaud Tisserand, 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 d'Informatique de Grenoble (LIG), Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS), and Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Open Science, [INFO.INFO-OH]Computer Science [cs]/Other [cs.OH], Reproducible Research
Abstract

International audience; Nous avons récemment soumis à Europar notre premier article dont l'analyse est reproductible de bout en bout. L'objectif de cette intervention est d'expliquer comment nous avons procédé et de discuter sur la généralisation possible de cette approche à d'autres cas d'étude. Cet article porte sur la validation d'un modèle permettant de simuler StarPU, un runtime à base de tâches pour architectures hybrides, à l'aide de SimGrid. Pour valider ce modèle, un nombre conséquent d'expériences sur des architectures variées a du être réalisé. L'ensemble des traces des exécutions réalisées sur ces différentes plates-formes ainsi que l'ensemble des informations sur leur provenance et nécessaires à leur réalisation (versions des codes, type de machine, OS, options de compilation, ...) ont été consignées systématiquement grâce à une utilisation combinée de git et d'org-mode dans l'équivalent d'un cahier de laboratoire. Il a alors été très simple de rédiger un article sur le même principe. Concrètement, les traces ont été migrées sur figshare et les sources du document contiennent l'intégralité des scripts nécessaires à la réalisation de l'analyse. La compilation du document commence par télécharger l'ensemble des traces en local avant d'en extraire les informations importantes pour l'analyse et de générer les courbes figurant dans l'article. Il devient donc possible pour quiconque de partir d'un graphique et de remonter jusqu'aux informations sur les conditions expérimentales sous-jacentes.

Published
2014

26. Towards Modeling and Simulation of Exascale Computing Platforms

Author

Stanisic, Luka, Laboratoire d'Informatique de Grenoble (LIG), Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS), Middleware efficiently scalable (MESCAL), 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 d'Informatique de Grenoble (LIG), Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS), Universite Joseph Fourier, Arnaud Legrand (arnaud.legrand@imag.fr), ANR-11-INFR-0013,SONGS,Simulation de systèmes de prochaine génération(2011), European Project: 288777,EC:FP7:ICT,FP7-ICT-2011-7,MONT-BLANC(2011), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Inria Grenoble - Rhône-Alpes, and Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)

Subjects
HPC High-Performance Computing, ARM processors, Performance Analysis, [INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC]
Abstract

National audience; Future super-computer platforms will be facing big challenges due tothe enormous power consumption. One possible solution to this problemwould be to develop HPC systems from today’s energy-efficient hardwaresolutions used in embedded and mobile devices like ARM. However, ARMchips have never been used in HPC programing before, leading to a numberof significant challenges. Therefore, we experimented with ARM processors and compared their performance with the architectures that are knownbetter, in this case last generations of Intel processors. Due to the memorybottleneck of most scientific applications, understanding the performanceof CPU caches in this context is crucial, thus this research was investigat-ing the processor performance depending on memory hierarchy. We presentnot only differences and complexity of these two architectures, but also howchanging seemingly innocuous aspects of an experimental setup can causecompletely distinctive behavior. Additionally, we demonstrate very cleanand systematic methodology, which aid us in achieving good performanceestimations.

Published
2012

33. Euro-Par 2019: Parallel Processing Workshops : Euro-Par 2019 International Workshops, Göttingen, Germany, August 26–30, 2019, Revised Selected Papers

Author

Ulrich Schwardmann, Christian Boehme, Dora B. Heras, Valeria Cardellini, Emmanuel Jeannot, Antonio Salis, Claudio Schifanella, Ravi Reddy Manumachu, Dieter Schwamborn, Laura Ricci, Oh Sangyoon, Thomas Gruber, Laura Antonelli, Stephen L. Scott, Ulrich Schwardmann, Christian Boehme, Dora B. Heras, Valeria Cardellini, Emmanuel Jeannot, Antonio Salis, Claudio Schifanella, Ravi Reddy Manumachu, Dieter Schwamborn, Laura Ricci, Oh Sangyoon, Thomas Gruber, Laura Antonelli, and Stephen L. Scott

Subjects
Computer engineering, Computer networks, Software engineering, Microprogramming, Logic design
Abstract

This book constitutes revised selected papers from the workshops held at 25th International Conference on Parallel and Distributed Computing, Euro-Par 2019, which took place in Göttingen, Germany, in August 2019. The 53 full papers and 10 poster papers presented in this volume were carefully reviewed and selected from 77 submissions. Euro-Par is an annual, international conference in Europe, covering all aspects of parallel and distributed processing. These range from theory to practice, from small to the largest parallel and distributed systems and infrastructures, from fundamental computational problems to full-edged applications, from architecture, compiler, language and interface design and implementation to tools, support infrastructures, and application performance aspects. Chapter'In Situ Visualization of Performance-Related Data in Parallel CFD Applications'is available open access under a Creative Commons Attribution 4.0 International License vialink.springer.com.

Published
2020

34. Euro-Par 2015: Parallel Processing Workshops : Euro-Par 2015 International Workshops, Vienna, Austria, August 24-25, 2015, Revised Selected Papers

Author

Sascha Hunold, Alexandru Costan, Domingo Giménez, Alexandru Iosup, Laura Ricci, María Engracia Gómez Requena, Vittorio Scarano, Ana Lucia Varbanescu, Stephen L. Scott, Stefan Lankes, Josef Weidendorfer, Michael Alexander, Sascha Hunold, Alexandru Costan, Domingo Giménez, Alexandru Iosup, Laura Ricci, María Engracia Gómez Requena, Vittorio Scarano, Ana Lucia Varbanescu, Stephen L. Scott, Stefan Lankes, Josef Weidendorfer, and Michael Alexander

Subjects
Electronic digital computers—Evaluation, Software engineering, Computer networks, Database management, Algorithms, Application software
Abstract

This book constitutes the thoroughly refereed post-conference proceedings of 12 workshops held at the 21st International Conference on Parallel and Distributed Computing, Euro-Par 2015, in Vienna, Austria, in August 2015. The 67 revised full papers presented were carefully reviewed and selected from 121 submissions. The volume includes papers from the following workshops: BigDataCloud: 4th Workshop on Big Data Management in Clouds - Euro-EDUPAR: First European Workshop on Parallel and Distributed Computing Education for Undergraduate Students - Hetero Par: 13th International Workshop on Algorithms, Models and Tools for Parallel Computing on Heterogeneous Platforms - LSDVE: Third Workshop on Large Scale Distributed Virtual Environments - OMHI: 4th International Workshop on On-chip Memory Hierarchies and Interconnects - PADAPS: Third Workshop on Parallel and Distributed Agent-Based Simulations - PELGA: Workshop on Performance Engineering for Large-Scale Graph Analytics - REPPAR: Second International Workshop on Reproducibility in Parallel Computing - Resilience: 8th Workshop on Resiliency in High Performance Computing in Clusters, Clouds, and Grids - ROME: Third Workshop on Runtime and Operating Systems for the Many Core Era - UCHPC: 8th Workshop on UnConventional High Performance Computing - and VHPC: 10th Workshop on Virtualization in High-Performance Cloud Computing.

Published
2015

35. Euro-Par 2014: Parallel Processing Workshops : Euro-Par 2014 International Workshops, Porto, Portugal, August 25-26, 2014, Revised Selected Papers, Part I

Author

Luís Lopes, Julius Žilinskas, Alexandru Costan, Roberto G. Cascella, Gabor Kecskemeti, Emmanuel Jeannot, Mario Cannataro, Laura Ricci, Siegfried Benkner, Salvador Petit, Vittorio Scarano, José Gracia, Sascha Hunold, Stephen L Scott, Stefan Lankes, Christian Lengauer, Jesus Carretero, Jens Breitbart, Michael Alexander, Luís Lopes, Julius Žilinskas, Alexandru Costan, Roberto G. Cascella, Gabor Kecskemeti, Emmanuel Jeannot, Mario Cannataro, Laura Ricci, Siegfried Benkner, Salvador Petit, Vittorio Scarano, José Gracia, Sascha Hunold, Stephen L Scott, Stefan Lankes, Christian Lengauer, Jesus Carretero, Jens Breitbart, and Michael Alexander

Subjects
Electronic digital computers—Evaluation, Software engineering, Computer networks, Database management, Algorithms, Application software
Abstract

The two volumes LNCS 8805 and 8806 constitute the thoroughly refereed post-conference proceedings of 18 workshops held at the 20th International Conference on Parallel Computing, Euro-Par 2014, in Porto, Portugal, in August 2014. The 100 revised full papers presented were carefully reviewed and selected from 173 submissions. The volumes include papers from the following workshops: APCI&E (First Workshop on Applications of Parallel Computation in Industry and Engineering - BigDataCloud (Third Workshop on Big Data Management in Clouds) - DIHC (Second Workshop on Dependability and Interoperability in Heterogeneous Clouds) - FedICI (Second Workshop on Federative and Interoperable Cloud Infrastructures) - Hetero Par (12th International Workshop on Algorithms, Models and Tools for Parallel Computing on Heterogeneous Platforms) - HiBB (5th Workshop on High Performance Bioinformatics and Biomedicine) - LSDVE (Second Workshop on Large Scale Distributed Virtual Environments on Clouds and P2P) - MuCoCoS (7th International Workshop on Multi-/Many-core Computing Systems) - OMHI (Third Workshop on On-chip Memory Hierarchies and Interconnects) - PADAPS (Second Workshop on Parallel and Distributed Agent-Based Simulations) - PROPER (7th Workshop on Productivity and Performance) - Resilience (7th Workshop on Resiliency in High Performance Computing with Clusters, Clouds, and Grids) - REPPAR (First International Workshop on Reproducibility in Parallel Computing) - ROME (Second Workshop on Runtime and Operating Systems for the Many Core Era) - SPPEXA (Workshop on Software for Exascale Computing) - TASUS (First Workshop on Techniques and Applications for Sustainable Ultrascale Computing Systems) - UCHPC (7th Workshop on Un Conventional High Performance Computing) and VHPC (9th Workshop on Virtualization in High-Performance Cloud Computing.

Published
2014

36. Euro-Par 2014: Parallel Processing : 20th International Conference, Porto, Portugal, August 25-29, 2014, Proceedings

Author

Fernando Silva, Inês Dutra, Vitor Santos Costa, Fernando Silva, Inês Dutra, and Vitor Santos Costa

Subjects
Compilers (Computer programs), Operating systems (Computers), Electronic digital computers—Evaluation, Computer networks, Algorithms
Abstract

This book constitutes the refereed proceedings of the 20th International Conference on Parallel and Distributed Computing, Euro-Par 2014, held in Porto, Portugal, in August 2014. The 68 revised full papers presented were carefully reviewed and selected from 267 submissions. The papers are organized in 15 topical sections: support tools environments; performance prediction and evaluation; scheduling and load balancing; high-performance architectures and compilers; parallel and distributed data management; grid, cluster and cloud computing; green high performance computing; distributed systems and algorithms; parallel and distributed programming; parallel numerical algorithms; multicore and manycore programming; theory and algorithms for parallel computation; high performance networks and communication; high performance and scientific applications; and GPU and accelerator computing.

Published
2014

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