Del 10724 i serien Lecture Notes in Computer Science

High Performance Computing Systems. Performance Modeling, Benchmarking, and Simulation

8th International Workshop, PMBS 2017, Denver, CO, USA, November 13, 2017, Proceedings

Häftad, Engelska, 2018

AvStephen Jarvis,Steven Wright,Simon Hammond

739 kr

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This book constitutes the refereed proceedings papers from the 8th International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computing Systems, PMBS 2017, held in Denver, Colorado, USA, in November 2017. The 10 full papers and 3 short papers included in this volume were carefully reviewed and selected from 36 submissions. They were organized in topical sections named: performance evaluation and analysis; performance modeling and simulation; and short papers.

Produktinformation

Utgivningsdatum2018-01-10
Mått155 x 235 x 16 mm
Vikt423 g
FormatHäftad
SpråkEngelska
SerieLecture Notes in Computer Science
Antal sidor261
Upplaga18001
FörlagSpringer International Publishing AG
ISBN9783319729701

Tillhör följande kategorier

Performance Evaluation and Analysis.- Evaluating On-Node GPU Interconnect for Deep Learning Workloads.- Comparison of Parallelisation Approaches,Languages, and Compilers for Unstructured Mesh Algorithms on GPUs.- Periodic I/O scheduling for super-computers.- A performance study of Quantum ESPRESSO's PWscf code on multi-core and GPU systems.- Section B: Performance Modeling and Simulation Modeling Large Compute Nodes with Heterogeneous Memories with Cache-Aware Rooine Model.- A Scalable Analytical Memory Model for CPU Performance Prediction.- Modeling UGAL on the Dragony Topology.- Resilient N-Body Tree Computations with Algorithm-Based Focused Recovery: Model and Performance Analysis.- Multi-fidelity Surrogate Modeling for Application/Architecture Co-design.- A Slurm Simulator: Implementation and Parametric Analysis.- Short Papers.- Path-synchronous Performance Monitoring in HPC Interconnection Networks with Source-code Attribution.- Performance and Energy Usage of Workloads on KNL andHaswell Architectures.- A survey of application memory usage on a national supercomputer: an analysis of memory requirements on ARCHER.

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Del 10724 i serien Lecture Notes in Computer Science

High Performance Computing Systems. Performance Modeling, Benchmarking, and Simulation

8th International Workshop, PMBS 2017, Denver, CO, USA, November 13, 2017, Proceedings

Häftad, Engelska, 2018

AvStephen Jarvis,Steven Wright,Simon Hammond

739 kr

Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt för medlemmar vid köp för minst 249 kr.

Finns i fler format (2)

Häftad

739 kr

Skickas inom 10-15 vardagar

Häftad

709 kr

Skickas inom 10-15 vardagar

Produktinformation

Utgivningsdatum2018-01-10
Mått155 x 235 x 16 mm
Vikt423 g
FormatHäftad
SpråkEngelska
SerieLecture Notes in Computer Science
Antal sidor261
Upplaga18001
FörlagSpringer International Publishing AG
ISBN9783319729701

Tillhör följande kategorier

Performance Evaluation and Analysis.- Evaluating On-Node GPU Interconnect for Deep Learning Workloads.- Comparison of Parallelisation Approaches,Languages, and Compilers for Unstructured Mesh Algorithms on GPUs.- Periodic I/O scheduling for super-computers.- A performance study of Quantum ESPRESSO's PWscf code on multi-core and GPU systems.- Section B: Performance Modeling and Simulation Modeling Large Compute Nodes with Heterogeneous Memories with Cache-Aware Rooine Model.- A Scalable Analytical Memory Model for CPU Performance Prediction.- Modeling UGAL on the Dragony Topology.- Resilient N-Body Tree Computations with Algorithm-Based Focused Recovery: Model and Performance Analysis.- Multi-fidelity Surrogate Modeling for Application/Architecture Co-design.- A Slurm Simulator: Implementation and Parametric Analysis.- Short Papers.- Path-synchronous Performance Monitoring in HPC Interconnection Networks with Source-code Attribution.- Performance and Energy Usage of Workloads on KNL andHaswell Architectures.- A survey of application memory usage on a national supercomputer: an analysis of memory requirements on ARCHER.