The Experts below are selected from a list of 237 Experts worldwide ranked by ideXlab platform
Henri Casanova - One of the best experts on this subject based on the ideXlab platform.
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Dynamic Fractional Resource Scheduling versus Batch Scheduling
IEEE Transactions on Parallel and Distributed Systems, 2012Co-Authors: Mark Stillwell, Frédéric Vivien, Henri CasanovaAbstract:We propose a novel job scheduling approach for Homogeneous Cluster computing platforms. Its key feature is the use of virtual machine technology to share fractional node resources in a precise and controlled manner. Other VM-based scheduling approaches have focused primarily on technical issues or extensions to existing batch scheduling systems, while we take a more aggressive approach and seek to find heuristics that maximize an objective metric correlated with job performance. We derive absolute performance bounds and develop algorithms for the online nonclairvoyant version of our scheduling problem. We further evaluate these algorithms in simulation against both synthetic and real-world HPC workloads and compare our algorithms to standard batch scheduling approaches. We find that our approach improves over batch scheduling by orders of magnitude in terms of job stretch, while leading to comparable or better resource utilization. Our results demonstrate that virtualization technology coupled with lightweight online scheduling strategies can afford dramatic improvements in performance for executing HPC workloads.
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Dynamic Fractional Resource Scheduling vs. Batch Scheduling
ReVision, 2011Co-Authors: Henri Casanova, Mark Stillwell, Frédéric VivienAbstract:We propose a novel job scheduling approach for Homogeneous Cluster computing platforms. Its key feature is the use of virtual machine technology to share fractional node resources in a precise and controlled manner. Other VM-based scheduling approaches have focused primarily on technical issues or on extensions to existing batch scheduling systems, while we take a more aggressive approach and seek to find heuristics that maximize an objective metric correlated with job performance. We derive absolute performance bounds and develop algorithms for the online, non-clairvoyant version of our scheduling problem. We further evaluate these algorithms in simulation against both synthetic and real-world HPC workloads and compare our algorithms to standard batch scheduling approaches. We find that our approach improves over batch scheduling by orders of magnitude in terms of job stretch, while leading to comparable or better resource utilization. Our results demonstrate that virtualization technology coupled with lightweight online scheduling strategies can afford dramatic improvements in performance for executing HPC workloads.
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On Cluster Resource Allocation for Multiple Parallel Task Graphs
Journal of Parallel and Distributed Computing, 2010Co-Authors: Henri Casanova, Frédéric Desprez, Frédéric SuterAbstract:Many scientific applications can be structured as Parallel Task Graphs (PTGs), that is, graphs of data-parallel tasks. Adding data-parallelism to a task-parallel application provides opportunities for higher performance and scalability, but poses additional scheduling challenges. In this paper, we study the off-line scheduling of multiple PTGs on a single, Homogeneous Cluster. The objective is to optimize performance without compromising fairness among the PTGs. We consider the range of previously proposed scheduling algorithms applicable to this problem, both from the applied and the theoretical literature, and we propose minor improvements when possible. Our main contribution is an extensive evaluation of these algorithms in simulation, using both synthetic and real-world application configurations, using two different metrics for performance and one metric for fairness. We identify a handful of algorithms that provide good trade-offs when considering all these metrics. The best algorithm overall is one that structures the schedule as a sequence of phases of increasing duration based on a makespan guarantee produced by an approximation algorithm.
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Minimizing Stretch and Makespan of Multiple Parallel Task Graphs via Malleable Allocations
2010Co-Authors: Henri Casanova, Frédéric Desprez, Frédéric SuterAbstract:Many scientific applications can be structured as Parallel Task Graphs (PTGs), i.e., graphs of data-parallel tasks. Adding data-parallelism to a task-parallel application provides opportunities for higher performance and scalability, but poses scheduling challenges. We study the off-line scheduling of multiple PTGs on a single, Homogeneous Cluster. The objective is to optimize performance and fairness. We propose a novel algorithm that first computes perfectly fair PTG completion times assuming that each PTG is an ideal malleable job. These completion times are then relaxed so that the schedule is organized as a sequence of periods and is still close to the perfectly fair schedule. Finally, since PTGs are not perfectly malleable, the algorithm increases the execution time of all PTGs uniformly until it can successfully schedule each task in a period. Our evaluation in simulation, using both synthetic and real-world application configurations, shows that our algorithm outperforms previously proposed algorithms when considering two different performance metrics and one fairness metric.
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Dynamic Fractional Resource Scheduling for HPC Workloads
2010Co-Authors: Mark Stillwell, Frédéric Vivien, Henri CasanovaAbstract:We propose a novel job scheduling approach for Homogeneous Cluster computing platforms. Its key feature is the use of virtual machine technology for sharing resources in a precise and controlled manner. We justify our approach and propose several job scheduling algorithms. We present results obtained in simulations for synthetic and real-world High Performance Computing (HPC) workloads, in which we compare our proposed algorithms with standard batch scheduling algorithms. We find that our approach widely outperforms batch scheduling. We also identify a few promising algorithms that perform well across most experimental scenarios. Our results demonstrate that virtualization technology coupled with lightweight scheduling strategies affords dramatic improvements in performance for HPC workloads.
E. D. Vries - One of the best experts on this subject based on the ideXlab platform.
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the optimization and validation of the biotyper maldi tof ms database for the identification of gram positive anaerobic cocci
Clinical Microbiology and Infection, 2016Co-Authors: A.c.m. Veloo, E. D. Vries, E. Urbán, Ingrid Wybo, Ulrik Stenz Justesen, T. Morris, Helene Jeanpierre, A J Van Winkelhoff, Haroun N Shah, E NagyAbstract:Gram-positive anaerobic cocci (GPAC) account for 24%-31% of the anaerobic bacteria isolated from human clinical specimens. At present, GPAC are under-represented in the Biotyper MALDI-TOF MS database. Profiles of new species have yet to be added. We present the optimization of the matrix-assisted laser desorption-ionization time-of-flight mass spectrometry (MALDI-TOF MS) database for the identification of GPAC. Main spectral profiles (MSPs) were created for 108 clinical GPAC isolates. Identity was confirmed using 16S rRNA gene sequencing. Species identification was considered to be reliable if the sequence similarity with its closest relative was ≥98.7%. The optimized database was validated using 140 clinical isolates. The 16S rRNA sequencing identity was compared with the MALDI-TOF MS result. MSPs were added from 17 species that were not yet represented in the MALDI-TOF MS database or were under-represented (fewer than five MSPs). This resulted in an increase from 53.6% (75/140) to 82.1% (115/140) of GPAC isolates that could be identified at the species level using MALDI-TOF MS. An improved log score was obtained for 51.4% (72/140) of the strains. For strains with a sequence similarity <98.7% with their closest relative (n = 5) or with an inconclusive sequence identity (n = 4), no identification was obtained by MALDI-TOF MS or in the latter case an identity with one of its relatives. For some species the MSP of the type strain was not part of the confined Cluster of the corresponding clinical isolates. Also, not all species formed a Homogeneous Cluster. It emphasizes the necessity of adding sufficient MSPs of human clinical isolates.
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The optimization and validation of the Biotyper MALDI-TOF MS database for the identification of Gram-positive anaerobic cocci
Clinical Microbiology and Infection, 2016Co-Authors: E. D. Vries, Habas Jean-Pierre, A.c.m. Veloo, E. Urbán, Ingrid Wybo, H Shah, Ulrik Stenz Justesen, Markus Kostrzewa, T. Morris, Arie Jan Van WinkelhoffAbstract:Gram-positive anaerobic cocci (GPAC) account for 24%\textendash31% of the anaerobic bacteria isolated from human clinical specimens. At present, GPAC are under-represented in the Biotyper MALDI-TOF MS database. Profiles of new species have yet to be added. We present the optimization of the matrix-assisted laser desorption\textendashionization time-of-flight mass spectrometry (MALDI-TOF MS) database for the identification of GPAC. Main spectral profiles (MSPs) were created for 108 clinical GPAC isolates. Identity was confirmed using 16S rRNA gene sequencing. Species identification was considered to be reliable if the sequence similarity with its closest relative was >=98.7%. The optimized database was validated using 140 clinical isolates. The 16S rRNA sequencing identity was compared with the MALDI-TOF MS result. MSPs were added from 17 species that were not yet represented in the MALDI-TOF MS database or were under-represented (fewer than five MSPs). This resulted in an increase from 53.6% (75/140) to 82.1% (115/140) of GPAC isolates that could be identified at the species level using MALDI-TOF MS. An improved log score was obtained for 51.4% (72/140) of the strains. For strains with a sequence similarity \textless98.7% with their closest relative (n~=~5) or with an inconclusive sequence identity (n~=~4), no identification was obtained by MALDI-TOF MS or in the latter case an identity with one of its relatives. For some species the MSP of the type strain was not part of the confined Cluster of the corresponding clinical isolates. Also, not all species formed a Homogeneous Cluster. It emphasizes the necessity of adding sufficient MSPs of human clinical isolates.
A.c.m. Veloo - One of the best experts on this subject based on the ideXlab platform.
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the optimization and validation of the biotyper maldi tof ms database for the identification of gram positive anaerobic cocci
Clinical Microbiology and Infection, 2016Co-Authors: A.c.m. Veloo, E. D. Vries, E. Urbán, Ingrid Wybo, Ulrik Stenz Justesen, T. Morris, Helene Jeanpierre, A J Van Winkelhoff, Haroun N Shah, E NagyAbstract:Gram-positive anaerobic cocci (GPAC) account for 24%-31% of the anaerobic bacteria isolated from human clinical specimens. At present, GPAC are under-represented in the Biotyper MALDI-TOF MS database. Profiles of new species have yet to be added. We present the optimization of the matrix-assisted laser desorption-ionization time-of-flight mass spectrometry (MALDI-TOF MS) database for the identification of GPAC. Main spectral profiles (MSPs) were created for 108 clinical GPAC isolates. Identity was confirmed using 16S rRNA gene sequencing. Species identification was considered to be reliable if the sequence similarity with its closest relative was ≥98.7%. The optimized database was validated using 140 clinical isolates. The 16S rRNA sequencing identity was compared with the MALDI-TOF MS result. MSPs were added from 17 species that were not yet represented in the MALDI-TOF MS database or were under-represented (fewer than five MSPs). This resulted in an increase from 53.6% (75/140) to 82.1% (115/140) of GPAC isolates that could be identified at the species level using MALDI-TOF MS. An improved log score was obtained for 51.4% (72/140) of the strains. For strains with a sequence similarity <98.7% with their closest relative (n = 5) or with an inconclusive sequence identity (n = 4), no identification was obtained by MALDI-TOF MS or in the latter case an identity with one of its relatives. For some species the MSP of the type strain was not part of the confined Cluster of the corresponding clinical isolates. Also, not all species formed a Homogeneous Cluster. It emphasizes the necessity of adding sufficient MSPs of human clinical isolates.
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The optimization and validation of the Biotyper MALDI-TOF MS database for the identification of Gram-positive anaerobic cocci
Clinical Microbiology and Infection, 2016Co-Authors: E. D. Vries, Habas Jean-Pierre, A.c.m. Veloo, E. Urbán, Ingrid Wybo, H Shah, Ulrik Stenz Justesen, Markus Kostrzewa, T. Morris, Arie Jan Van WinkelhoffAbstract:Gram-positive anaerobic cocci (GPAC) account for 24%\textendash31% of the anaerobic bacteria isolated from human clinical specimens. At present, GPAC are under-represented in the Biotyper MALDI-TOF MS database. Profiles of new species have yet to be added. We present the optimization of the matrix-assisted laser desorption\textendashionization time-of-flight mass spectrometry (MALDI-TOF MS) database for the identification of GPAC. Main spectral profiles (MSPs) were created for 108 clinical GPAC isolates. Identity was confirmed using 16S rRNA gene sequencing. Species identification was considered to be reliable if the sequence similarity with its closest relative was >=98.7%. The optimized database was validated using 140 clinical isolates. The 16S rRNA sequencing identity was compared with the MALDI-TOF MS result. MSPs were added from 17 species that were not yet represented in the MALDI-TOF MS database or were under-represented (fewer than five MSPs). This resulted in an increase from 53.6% (75/140) to 82.1% (115/140) of GPAC isolates that could be identified at the species level using MALDI-TOF MS. An improved log score was obtained for 51.4% (72/140) of the strains. For strains with a sequence similarity \textless98.7% with their closest relative (n~=~5) or with an inconclusive sequence identity (n~=~4), no identification was obtained by MALDI-TOF MS or in the latter case an identity with one of its relatives. For some species the MSP of the type strain was not part of the confined Cluster of the corresponding clinical isolates. Also, not all species formed a Homogeneous Cluster. It emphasizes the necessity of adding sufficient MSPs of human clinical isolates.
Arie Jan Van Winkelhoff - One of the best experts on this subject based on the ideXlab platform.
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The optimization and validation of the Biotyper MALDI-TOF MS database for the identification of Gram-positive anaerobic cocci
Clinical Microbiology and Infection, 2016Co-Authors: E. D. Vries, Habas Jean-Pierre, A.c.m. Veloo, E. Urbán, Ingrid Wybo, H Shah, Ulrik Stenz Justesen, Markus Kostrzewa, T. Morris, Arie Jan Van WinkelhoffAbstract:Gram-positive anaerobic cocci (GPAC) account for 24%\textendash31% of the anaerobic bacteria isolated from human clinical specimens. At present, GPAC are under-represented in the Biotyper MALDI-TOF MS database. Profiles of new species have yet to be added. We present the optimization of the matrix-assisted laser desorption\textendashionization time-of-flight mass spectrometry (MALDI-TOF MS) database for the identification of GPAC. Main spectral profiles (MSPs) were created for 108 clinical GPAC isolates. Identity was confirmed using 16S rRNA gene sequencing. Species identification was considered to be reliable if the sequence similarity with its closest relative was >=98.7%. The optimized database was validated using 140 clinical isolates. The 16S rRNA sequencing identity was compared with the MALDI-TOF MS result. MSPs were added from 17 species that were not yet represented in the MALDI-TOF MS database or were under-represented (fewer than five MSPs). This resulted in an increase from 53.6% (75/140) to 82.1% (115/140) of GPAC isolates that could be identified at the species level using MALDI-TOF MS. An improved log score was obtained for 51.4% (72/140) of the strains. For strains with a sequence similarity \textless98.7% with their closest relative (n~=~5) or with an inconclusive sequence identity (n~=~4), no identification was obtained by MALDI-TOF MS or in the latter case an identity with one of its relatives. For some species the MSP of the type strain was not part of the confined Cluster of the corresponding clinical isolates. Also, not all species formed a Homogeneous Cluster. It emphasizes the necessity of adding sufficient MSPs of human clinical isolates.
E Nagy - One of the best experts on this subject based on the ideXlab platform.
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the optimization and validation of the biotyper maldi tof ms database for the identification of gram positive anaerobic cocci
Clinical Microbiology and Infection, 2016Co-Authors: A.c.m. Veloo, E. D. Vries, E. Urbán, Ingrid Wybo, Ulrik Stenz Justesen, T. Morris, Helene Jeanpierre, A J Van Winkelhoff, Haroun N Shah, E NagyAbstract:Gram-positive anaerobic cocci (GPAC) account for 24%-31% of the anaerobic bacteria isolated from human clinical specimens. At present, GPAC are under-represented in the Biotyper MALDI-TOF MS database. Profiles of new species have yet to be added. We present the optimization of the matrix-assisted laser desorption-ionization time-of-flight mass spectrometry (MALDI-TOF MS) database for the identification of GPAC. Main spectral profiles (MSPs) were created for 108 clinical GPAC isolates. Identity was confirmed using 16S rRNA gene sequencing. Species identification was considered to be reliable if the sequence similarity with its closest relative was ≥98.7%. The optimized database was validated using 140 clinical isolates. The 16S rRNA sequencing identity was compared with the MALDI-TOF MS result. MSPs were added from 17 species that were not yet represented in the MALDI-TOF MS database or were under-represented (fewer than five MSPs). This resulted in an increase from 53.6% (75/140) to 82.1% (115/140) of GPAC isolates that could be identified at the species level using MALDI-TOF MS. An improved log score was obtained for 51.4% (72/140) of the strains. For strains with a sequence similarity <98.7% with their closest relative (n = 5) or with an inconclusive sequence identity (n = 4), no identification was obtained by MALDI-TOF MS or in the latter case an identity with one of its relatives. For some species the MSP of the type strain was not part of the confined Cluster of the corresponding clinical isolates. Also, not all species formed a Homogeneous Cluster. It emphasizes the necessity of adding sufficient MSPs of human clinical isolates.