| Title/Authors | Title | Research Artifacts
[?] A research
artifact is any by-product of a research project that is not
directly included in the published research paper. In Computer
Science research this is often source code and data sets, but
it could also be media, documentation, inputs to proof
assistants, shell-scripts to run experiments, etc.
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Mitigating MPI Message Matching Misery Mario Flajslik, James Dinan, Keith D. Underwood |
Mitigating MPI Message Matching Misery Details |
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Efficient and Predictable Group Communication for Manycore NoCs Karthik Yagna, Onkar Patil, Frank Mueller |
Efficient and Predictable Group Communication for Manycore NoCs Details |
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Comparing Runtime Systems with Exascale Ambitions Using the Parallel Research Kernels Rob F. Van der Wijngaart, Abdullah Kayi, Jeff R. Hammond, Gabriele Jost, Tom St. John, Srinivas Sridharan, Timothy G. Mattson, John Abercrombie, Jacob Nelson |
Comparing Runtime Systems with Exascale Ambitions Using the Parallel Research Kernels Details |
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Diana Palsetia, William Hendrix, Sunwoo Lee, Ankit Agrawal, Wei-keng Liao, Alok N. Choudhary |
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Towards Machine Learning on the Automata Processor Tommy Tracy II, Yao Fu, Indranil Roy, Eric Jonas, Paul Glendenning |
Towards Machine Learning on the Automata Processor Details |
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Multi-versioning Performance Opportunities in BGAS System for Resilience Nan Dun, Dirk Pleiter, Aiman Fang, Nicolas Vandenbergen, Andrew A. Chien |
Multi-versioning Performance Opportunities in BGAS System for Resilience Details |
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Tapasya Patki, Natalie J. Bates, Girish Ghatikar, Anders Clausen, Sonja Klingert, Ghaleb Abdulla, Mehdi Sheikhalishahi |
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TCU: A Multi-Objective Hardware Thread Mapping Unit for HPC Clusters Ravi Kumar Pujari, Thomas Wild, Andreas Herkersdorf |
TCU: A Multi-Objective Hardware Thread Mapping Unit for HPC Clusters Details |
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SPRITE: A Fast Parallel SNP Detection Pipeline Vasudevan Rengasamy, Kamesh Madduri |
SPRITE: A Fast Parallel SNP Detection Pipeline Details |
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Resource Management for Running HPC Applications in Container Clouds Stephen Herbein, Ayush Dusia, Aaron Landwehr, Sean McDaniel, José Monsalve Diaz, Yang Yang, Seetharami R. Seelam, Michela Taufer |
Resource Management for Running HPC Applications in Container Clouds Details |
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Scalability of Partial Differential Equations Preconditioner Resilient to Soft and Hard Faults Karla Morris, Francesco Rizzi, Khachik Sargsyan, Kathryn Dahlgren, Paul Mycek, Cosmin Safta, Olivier P. Le Maître, Omar M. Knio, Bert J. Debusschere |
Scalability of Partial Differential Equations Preconditioner Resilient to Soft and Hard Faults Details |
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Author Comments:
Please feel free to contact us in case you want to collaborate with us on resilience or discuss details of our work.
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An Analytical Model-Based Auto-tuning Framework for Locality-Aware Loop Scheduling Rengan Xu, Sunita Chandrasekaran, Xiaonan Tian, Barbara M. Chapman |
An Analytical Model-Based Auto-tuning Framework for Locality-Aware Loop Scheduling Details |
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AutoMOMML: Automatic Multi-objective Modeling with Machine Learning Prasanna Balaprakash, Ananta Tiwari, Stefan M. Wild, Laura Carrington, Paul D. Hovland |
AutoMOMML: Automatic Multi-objective Modeling with Machine Learning Details |
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Efficiency of High Order Spectral Element Methods on Petascale Architectures Maxwell Hutchinson, Alexander Heinecke, Hans Pabst, Greg Henry, Matteo Parsani, David E. Keyes |
Efficiency of High Order Spectral Element Methods on Petascale Architectures Details |
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INAM2: InfiniBand Network Analysis and Monitoring with MPI Hari Subramoni, Albert Mathews Augustine, Mark Daniel Arnold, Jonathan L. Perkins, Xiaoyi Lu, Khaled Hamidouche, Dhabaleswar K. Panda |
INAM2: InfiniBand Network Analysis and Monitoring with MPI Details |
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High Order Seismic Simulations on the Intel Xeon Phi Processor (Knights Landing) Alexander Heinecke, Alexander Breuer, Michael Bader, Pradeep Dubey |
High Order Seismic Simulations on the Intel Xeon Phi Processor (Knights Landing) Details |
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As described in the paper, git tag 201511 was used for the performance measurements.
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TiDA: High-Level Programming Abstractions for Data Locality Management Didem Unat, Tan Nguyen, Weiqun Zhang, Muhammed Nufail Farooqi, Burak Bastem, George Michelogiannakis, Ann S. Almgren, John Shalf |
TiDA: High-Level Programming Abstractions for Data Locality Management Details |
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OpenAtom: Scalable Ab-Initio Molecular Dynamics with Diverse Capabilities Nikhil Jain, Eric J. Bohm, Eric Mikida, Subhasish Mandal, Minjung Kim, Prateek Jindal, Qi Li, Sohrab Ismail-Beigi, Glenn J. Martyna, Laxmikant V. Kalé |
OpenAtom: Scalable Ab-Initio Molecular Dynamics with Diverse Capabilities Details |
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An Efficient Parallel Load-Balancing Framework for Orthogonal Decomposition of Geometrical Data Bruno R. C. Magalhães, Farhan Tauheed, Thomas Heinis, Anastasia Ailamaki, Felix Schürmann |
An Efficient Parallel Load-Balancing Framework for Orthogonal Decomposition of Geometrical Data Details |
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Predictive Modeling for Job Power Consumption in HPC Systems Andrea Borghesi, Andrea Bartolini, Michele Lombardi, Michela Milano, Luca Benini |
Predictive Modeling for Job Power Consumption in HPC Systems Details |
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Performance, Design, and Autotuning of Batched GEMM for GPUs Ahmad Abdelfattah, Azzam Haidar, Stanimire Tomov, Jack J. Dongarra |
Performance, Design, and Autotuning of Batched GEMM for GPUs Details |
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Dynamic Sparse-Matrix Allocation on GPUs James King, Thomas Gilray, Robert M. Kirby, Matthew Might |
Dynamic Sparse-Matrix Allocation on GPUs Details |
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Many-Core Acceleration of a Discrete Ordinates Transport Mini-App at Extreme Scale Tom Deakin, Simon McIntosh-Smith, Wayne P. Gaudin |
Many-Core Acceleration of a Discrete Ordinates Transport Mini-App at Extreme Scale Details |
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Distributed Job Allocation for Large-Scale Manycores Subramanian Ramachandran, Frank Mueller |
Distributed Job Allocation for Large-Scale Manycores Details |
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Leveraging a Cluster-Booster Architecture for Brain-Scale Simulations Pramod S. Kumbhar, Michael L. Hines, Aleksandr Ovcharenko, Damián A. Mallón, James G. King, Florentino Sainz, Felix Schürmann, Fabien Delalondre |
Leveraging a Cluster-Booster Architecture for Brain-Scale Simulations Details |
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