Search

Your search keyword '"Teylo, Luan"' showing total 29 results
Start Over Author "Teylo, Luan"

Refine your results

more »

more »

more »
29 results on '"Teylo, Luan"'

1. Harnessing Low-Cost Virtual Machines on the Spot

Author

Sena, Alexandre C., Boeres, Cristina, Teylo, Luan, Drummond, Lúcia Maria A., Rebello, Vinod E. F., Borin, Edson, editor, Drummond, Lúcia Maria A., editor, Gaudiot, Jean-Luc, editor, Melo, Alba, editor, Melo Alves, Maicon, editor, and Navaux, Philippe Olivier Alexandre, editor

Published
2023
Full Text
View/download PDF

3. Scheduling Bag-of-Tasks in Clouds using Spot and Burstable Virtual Machines

Author

Teylo, Luan, Arantes, Luciana, Sens, Pierre, and Drummond, Lúcia Maria de A.

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

Leading Cloud providers offer several types of Virtual Machines (VMs) in diverse contract models, with different guarantees in terms of availability and reliability. Among them, the most popular contract models are the on-demand and the spot models. In the former, on-demand VMs are allocated for a fixed cost per time unit, and their availability is ensured during the whole execution. On the other hand, in the spot market, VMs are offered with a huge discount when compared to the on-demand VMs, but their availability fluctuates according to the cloud's current demand that can terminate or hibernate a spot VM at any time. Furthermore, in order to cope with workload variations, cloud providers have also introduced the concept of burstable VMs which are able to burst up their respective baseline CPU performance during a limited period of time with an up to 20% discount when compared to an equivalent non-burstable on-demand VMs. In the current work, we present the Burst Hibernation-Aware Dynamic Scheduler (Burst-HADS), a framework that schedules and executes tasks of Bag-of-Tasks applications with deadline constraints by exploiting spot and on-demand burstable VMs, aiming at minimizing both the monetary cost and the execution time. Based on ILS metaheuristics, Burst-HADS defines an initial scheduling map of tasks to VMs which can then be dynamically altered by migrating tasks of a hibernated spot VM or by performing work-stealing when VMs become idle. Performance results on Amazon EC2 cloud with different applications show that, when compared to a solution that uses only regular on-demand instances, Burst-HADS reduces the monetary cost of the execution and meet the application deadline even in scenarios with high spot hibernation rates. It also reduces the total execution time when compared to a solution that uses only spot and non-burstable on-demand instances.

Published
2020

4. A Bag-of-Tasks Scheduler Tolerant to Temporal Failures in Clouds

Author

Teylo, Luan, Drummond, Lúcia Maria de A., Arantes, Luciana, and Sens, Pierre

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

Cloud platforms have emerged as a prominent environment to execute high performance computing (HPC) applications providing on-demand resources as well as scalability. They usually offer different classes of Virtual Machines (VMs) which ensure different guarantees in terms of availability and volatility, provisioning the same resource through multiple pricing models. For instance, in Amazon EC2 cloud, the user pays per hour for on-demand VMs while spot VMs are unused instances available for lower price. Despite the monetary advantages, a spot VM can be terminated, stopped, or hibernated by EC2 at any moment. Using both hibernation-prone spot VMs (for cost sake) and on-demand VMs, we propose in this paper a static scheduling for HPC applications which are composed by independent tasks (bag-of-task) with deadline constraints. However, if a spot VM hibernates and it does not resume within a time which guarantees the application's deadline, a temporal failure takes place. Our scheduling, thus, aims at minimizing monetary costs of bag-of-tasks applications in EC2 cloud, respecting its deadline and avoiding temporal failures. To this end, our algorithm statically creates two scheduling maps: (i) the first one contains, for each task, its starting time and on which VM (i.e., an available spot or on-demand VM with the current lowest price) the task should execute; (ii) the second one contains, for each task allocated on a VM spot in the first map, its starting time and on which on-demand VM it should be executed to meet the application deadline in order to avoid temporal failures. The latter will be used whenever the hibernation period of a spot VM exceeds a time limit. Performance results from simulation with task execution traces, configuration of Amazon EC2 VM classes, and VMs market history confirms the effectiveness of our scheduling and that it tolerates temporal failures.

Published
2018

5. An Interference-Aware Strategy for Co-locating High Performance Computing Applications in Clouds

Author

Alves, Maicon Melo, Teylo, Luan, Frota, Yuri, Drummond, Lúcia Maria de A., Barbosa, Simone Diniz Junqueira, Editorial Board Member, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Kotenko, Igor, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Bianchini, Calebe, editor, Osthoff, Carla, editor, Souza, Paulo, editor, and Ferreira, Renato, editor

Published
2020
Full Text
View/download PDF

7. A GPU-Based Metaheuristic for Workflow Scheduling on Clouds

Author

Cieza, Elliod, Teylo, Luan, Frota, Yuri, Bentes, Cristiana, Drummond, Lúcia M. A., Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Pandu Rangan, C., Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Senger, Hermes, editor, Marques, Osni, editor, Garcia, Rogerio, editor, Pinheiro de Brito, Tatiana, editor, Iope, Rogério, editor, Stanzani, Silvio, editor, and Gil-Costa, Veronica, editor

Published
2019
Full Text
View/download PDF

8. Design and analyses of web scraping on burstable virtual machines.

Author

Drummond, Lúcia Maria A., Andrade, Luciano, Muniz, Pedro de Brito, Pereira, Matheus Marotti, Silva, Thiago do Prado, and Teylo, Luan

Subjects
VIRTUAL machine systems, WEB design, SERVICE level agreements, COST control, DATA extraction, WEB services
Abstract

Summary: Web scraping is a widely used technique for decision‐making, collecting, and structuring public data from the internet. As the volume of data continues to grow, the need for more efficient methods of data extraction becomes crucial. This article introduces a novel web scraping framework that utilizes Burstable virtual machines (VMs) on Amazon Web Services with the objective of reducing the monetary cost of execution while ensuring compliance with service level agreements (SLAs). To achieve this, the framework utilizes a combination of fixed and temporary Burstable VMs in a mixed cluster, which can be elastically scaled up to fulfill the SLA and scaled down to minimize monetary costs. Two strategies for handling VM allocation are proposed and evaluated: (i) a queue and SLA‐based strategy that employs queue size information and SLA criteria to determine the required number of VMs for the current scraping requests, and (ii) a credit‐based strategy that incorporates information about Burstable VM credits to effectively manage instance creation and termination. Experimental tests show that the proposed framework meets the defined SLA while achieving cost reductions of up to 74% compared to an approach that executes on fixed‐size clusters of Burstable instances. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

11. MScheduler: leveraging spot instances for high-performance reservoir simulation in the cloud

Author

Universitat Politècnica de Catalunya. Doctorat en Arquitectura de Computadors, Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors, Barcelona Supercomputing Center, Universitat Politècnica de Catalunya. CROMAI - Computing Resources Orchestration and Management for AI, Albuquerque Portella, Felipe, Estrela, Paulo J.B., Malini, Renzo Q., Teylo, Luan, Berral García, Josep Lluís, Drummond, Lúcia M.A., Universitat Politècnica de Catalunya. Doctorat en Arquitectura de Computadors, Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors, Barcelona Supercomputing Center, Universitat Politècnica de Catalunya. CROMAI - Computing Resources Orchestration and Management for AI, Albuquerque Portella, Felipe, Estrela, Paulo J.B., Malini, Renzo Q., Teylo, Luan, Berral García, Josep Lluís, and Drummond, Lúcia M.A.

Abstract

Petroleum reservoir simulation uses computer models to predict fluid flow in porous media, aiding to forecast oil production. Engineers execute numerous simulations with different geological realizations to refine the accuracy of the model. These experiments require considerable computational resources, which are not always available within the on-premises infrastructure. Commercial public cloud platforms can offer many advantages, such as virtually unlimited scalability and payper-use pricing. This paper introduces MSCHEDULER, a meta scheduler framework for reservoir simulations at Petrobras, a Brazilian energy company. It efficiently executes jobs in the cloud, utilizing spot Virtual Machines (VMs) to reduce costs and ensure job completion even with VM termination. Contributions include a novel methodology for reservoir simulation checkpointing, a cost-based scheduler, and an analysis of the strategy using real production jobs from Petrobras., This work was funded by Petroleo Brasileiro S.A. – Petrobras, by Project Universal/CNPq no 404087/2021-3 and CNE/FAPERJ no E-26/201.012/2022(271103). Also by Spanish Ministry of Science (MICINN, AEI, ERDF/FEDER) under grant agreement PID2021-126248OB-I00, MCIN/AEI/10.13039/ 501100011033/FEDER, UE, and Generalitat de Catalunya (AGAUR) 2021-SGR-00478., Peer Reviewed, Postprint (author's final draft)

Published
2023

13. I/O performance of multiscale finite element simulations on HPC environments

Author

Boito, Francieli, Gomes, Antonio, Peyrondet, Louis, Teylo, Luan, Topology-Aware System-Scale Data Management for High-Performance Computing (TADAAM), 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), Laboratorio Nacional de Computação Cientifica [Rio de Janeiro] (LNCC / MCT), ANR-17-CE25-0004,DASH,Ordonnancement de données pour le calcul haute-performance(2017), and European Project: 956748,H2020-EU.2.1.1. - INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT) ,ADMIRE(2021)

Subjects
I/O kernel, parallel I/O, mini-app, [INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], High-performance computing, multiscale simulation, numeric library
Abstract

International audience; In this paper, we present MSLIO, a code to mimic the I/O behavior of multiscale simulations. Such an I/O kernel is useful for HPC research, as it can be executed more easily and more efficiently than the full simulations when researchers are interested in the I/O load only. We validate MSLIO by comparing it to the I/O performance of an actual simulation, and we then use it to test some possible improvements to the output routine of the MHM (Multiscale Hybrid Mixed) library.

Published
2022
Full Text
View/download PDF

14. The role of storage target allocation in applications' I/O performance with BeeGFS

Author

Boito, Francieli, Pallez, Guillaume, Teylo, Luan, Topology-Aware System-Scale Data Management for High-Performance Computing (TADAAM), 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), Plafrim, ANR-17-CE25-0004,DASH,Ordonnancement de données pour le calcul haute-performance(2017), European Project: 956748,H2020-EU.2.1.1. - INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT) ,ADMIRE(2021), BOITO, Francieli Zanon, Ordonnancement de données pour le calcul haute-performance - - DASH2017 - ANR-17-CE25-0004 - AAPG2017 - VALID, and Adaptive multi-tier intelligent data manager for Exascale - ADMIRE - - H2020-EU.2.1.1. - INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT) 2021-04-01 - 2024-03-31 - 956748 - VALID

Subjects
I/O performance, Parallel file system, parallel I/O, [INFO.INFO-DC] Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], stripe count, [INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], BeeGFS, performance evaluation
Abstract

International audience; Parallel file systems are at the core of HPC I/O infrastructures. Those systems minimize the I/O time of applications by separating files into fixed-size chunks and distributing them across multiple storage targets. Therefore, the I/O performance experienced with a PFS is directly linked to the capacity to retrieve these chunks in parallel. In this work, we conduct an in-depth evaluation of the impact of the stripe count (the number of targets used for striping) on the write performance of BeeGFS, one of the most popular parallel file systems today. We consider different network configurations and show the fundamental role played by this parameter, in addition to the number of compute nodes, processes and storage targets. Through a rigorous experimental evaluation, we directly contradict conclusions from related work. Notably, we show that sharing I/O targets does not lead to performance degradation and that applications should use as many storage targets as possible. Our recommendations have the potential to significantly improve the overall write performance of BeeGFS deployments and also provide valuable information for future work on storage target allocation and stripe count tuning.

Published
2022

15. IO-SETS: Simple and efficient approaches for I/O bandwidth management

Author

Boito, Francieli, Pallez, Guillaume, Teylo, Luan, Vidal, Nicolas, 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), Topology-Aware System-Scale Data Management for High-Performance Computing (TADAAM), 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), This work was supported in part by the Project Région Nouvelle Aquitaine 2018-1R50119 'HPC scalable ecosystem', Plafrim, ANR-17-CE25-0004,DASH,Ordonnancement de données pour le calcul haute-performance(2017), European Project: 956748,H2020-EU.2.1.1. - INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT) ,ADMIRE(2021), Gouveia Lima, Luan, Ordonnancement de données pour le calcul haute-performance - - DASH2017 - ANR-17-CE25-0004 - AAPG2017 - VALID, Adaptive multi-tier intelligent data manager for Exascale - ADMIRE - - H2020-EU.2.1.1. - INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT) 2021-04-01 - 2024-03-31 - 956748 - VALID, Vidal, Nicolas, Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB), 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
Parallel I/O, Resource management, HPC, [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS], [INFO.INFO-DC] Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], I/O scheduling, [INFO.INFO-DS] Computer Science [cs]/Data Structures and Algorithms [cs.DS], [INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC]
Abstract

One of the main performance issues faced by highperformance platforms is the delay caused by concurrent applications performing I/O. When this happens, applications sharing the I/O bandwidth create congestion, which delays the execution time and affects the platform's overall performance. Several solutions have been proposed to tackle I/O congestion. Among those solutions, I/O scheduling strategies are an essential solution to this problem in HPC systems. Currently, their main drawback is the amount of information needed. In this work, we propose a novel framework for I/O management, IO-SETS. We present the potential of this framework through a simple scheduling solution called SET-10, an I/O scheduling solution that demands minimum information from users and can be easily integrated into HPC environments.

Published
2022

16. <sc>IO-Sets</sc>: Simple and Efficient Approaches for I/O Bandwidth Management

Author

Boito, Francieli, Pallez, Guillaume, Teylo, Luan, and Vidal, Nicolas

Abstract

One of the main performance issues faced by high-performance computing platforms is the congestion caused by concurrent I/O from applications. When this happens, the platform's overall performance and utilization are harmed. From the extensive work in this field, I/O scheduling is the essential solution to this problem. The main drawback of current techniques is the amount of information needed about applications, which compromises their applicability. In this paper, we propose a novel method for I/O management, IO-Sets. We present its potential through a scheduling heuristic called Set-10, which is simple and requires only minimal information. Our extensive experimental campaign shows the importance of IO-Sets and the robustness of Set-10 under various workloads. In particular in most of the simulated scenarios we improve the I/O slowdown over fairshare by 50%, which corresponds in our scenarios to a platform utilization gain of 2.5%. In the practical scenarios that we did, the utilization gain varies between 10 and 30%. We also provide insights on using our proposal in practice.

Published
2023
Full Text
View/download PDF

18. Implémentation et test d’un ordonnanceur Weighted Fair Queuing pour des requêtes d’E/S

Author

Mayer, Alessa, Teylo, Luan, Boito, Francieli, BOITO, Francieli Zanon, Topology-Aware System-Scale Data Management for High-Performance Computing (TADAAM), 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), and Inria

Subjects
high performance computing, E/S parallèles, parallel I/O, I/O scheduling, [INFO.INFO-DC] Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], ordonnancement d’E/S, [INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], calcul hautes performances
Abstract

This report describes the work conducted by Alessa Mayer during a two-month internship in the Inria center of the University of Bordeaux, as a member of the Tadaam team. During her internship, her advisors were Luan Teylo and Francieli Boito. The goal of the internship was to implement and test the weighted fair queuing scheduling algorithm applied to I/O requests, and to integrate it into the AGIOS I/O scheduling library. That scheduler will be used to implement the I/O Sets method, proposed by members of the team in a recent paper., Ce rapport porte sur le travail mené par Alessa Mayer lors d’un stage de deux mois au centre Inria de l’université de Bordeaux, au sein de l’équipe Tadaam. Son stage a été encadré par Luan Teylo et Francieli Boito. L’objectif du stage était d’implémenter et de tester l’algorithme d’ordonnancement Weighted Fair Queuing (WFQ) appliqué aux requêtes d’E/S, et de l’intégrer dans la bibliothèque d’ordonnancement d’E/S AGIOS. Cet ordonnanceur sera utilisé pour implémenter la méthode I/O Sets, proposée par les membres de l’équipe dans un article récent.

Published
2022

Catalog

Books, media, physical & digital resources
See catalog results