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NICE: Network-Integrated Cluster-Efficient Storage
Samer Al-Kiswany, Suli Yang, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau
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NICE: Network-Integrated Cluster-Efficient Storage
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Machine and Application Aware Partitioning for Adaptive Mesh Refinement Applications
Milinda Fernando, Dmitry Duplyakin, Hari Sundar
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Machine and Application Aware Partitioning for Adaptive Mesh Refinement Applications
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LetGo: A Lightweight Continuous Framework for HPC Applications Under Failures
Bo Fang, Qiang Guan, Nathan DeBardeleben, Karthik Pattabiraman, Matei Ripeanu
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LetGo: A Lightweight Continuous Framework for HPC Applications Under Failures
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IOGP: An Incremental Online Graph Partitioning Algorithm for Distributed Graph Databases
Dong Dai, Wei Zhang, Yong Chen
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IOGP: An Incremental Online Graph Partitioning Algorithm for Distributed Graph Databases
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Parallel Stream Processing Against Workload Skewness and Variance
Junhua Fang, Rong Zhang, Tom Z. J. Fu, Zhenjie Zhang, Aoying Zhou, Junhua Zhu
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Parallel Stream Processing Against Workload Skewness and Variance
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MaDaTS: Managing Data on Tiered Storage for Scientific Workflows
Devarshi Ghoshal, Lavanya Ramakrishnan
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MaDaTS: Managing Data on Tiered Storage for Scientific Workflows
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AllConcur: Leaderless Concurrent Atomic Broadcast
Marius Poke, Torsten Hoefler, Colin W. Glass
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AllConcur: Leaderless Concurrent Atomic Broadcast
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Better Safe than Sorry: Grappling with Failures of In-Memory Data Analytics Frameworks
Bogdan Ghit, Dick H. J. Epema
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Better Safe than Sorry: Grappling with Failures of In-Memory Data Analytics Frameworks
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ArrayUDF: User-Defined Scientific Data Analysis on Arrays
Bin Dong, Kesheng Wu, Surendra Byna, Jialin Liu, Weijie Zhao, Florin Rusu
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ArrayUDF: User-Defined Scientific Data Analysis on Arrays
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Building Secure Platforms for Research on Human Subjects: The Importance of Computer Scientists
Julia Ingrid Lane
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Building Secure Platforms for Research on Human Subjects: The Importance of Computer Scientists
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knor: A NUMA-Optimized In-Memory, Distributed and Semi-External-Memory k-means Library
Disa Mhembere, Da Zheng, Carey E. Priebe, Joshua T. Vogelstein, Randal C. Burns
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knor: A NUMA-Optimized In-Memory, Distributed and Semi-External-Memory k-means Library
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Enabling Workflow-Aware Scheduling on HPC Systems
Gonzalo Pedro Rodrigo Álvarez, Erik Elmroth, Per-Olov Östberg, Lavanya Ramakrishnan
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Enabling Workflow-Aware Scheduling on HPC Systems
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Caches All the Way Down: Infrastructure for Data Intensive Science
David Abramson
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Caches All the Way Down: Infrastructure for Data Intensive Science
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Towards a More Complete Understanding of SDC Propagation
Jon Calhoun, Marc Snir, Luke N. Olson, William D. Gropp
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Towards a More Complete Understanding of SDC Propagation
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Using Scientific Computing to Advance Wildland Fire Monitoring and Prediction
Janice L. Coen
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Using Scientific Computing to Advance Wildland Fire Monitoring and Prediction
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Predicting Output Performance of a Petascale Supercomputer
Bing Xie, Yezhou Huang, Jeffrey S. Chase, Jong Youl Choi, Scott Klasky, Jay F. Lofstead, Sarp Oral
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Predicting Output Performance of a Petascale Supercomputer
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Deep Learning in Cancer and Infectious Disease: Novel Driver Problems for Future HPC Architecture
Rick Stevens
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Deep Learning in Cancer and Infectious Disease: Novel Driver Problems for Future HPC Architecture
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COS: A Parallel Performance Model for Dynamic Variations in Processor Speed, Memory Speed, and Thread Concurrency
Bo Li, Edgar A. León, Kirk W. Cameron
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COS: A Parallel Performance Model for Dynamic Variations in Processor Speed, Memory Speed, and Thread Concurrency
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TCP Throughput Profiles Using Measurements over Dedicated Connections
Nageswara S. V. Rao, Qiang Liu, Satyabrata Sen, Don Towsley, Gayane Vardoyan, Rajkumar Kettimuthu, Ian T. Foster
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TCP Throughput Profiles Using Measurements over Dedicated Connections
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To Push or To Pull: On Reducing Communication and Synchronization in Graph Computations
Maciej Besta, Michal Podstawski, Linus Groner, Edgar Solomonik, Torsten Hoefler
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To Push or To Pull: On Reducing Communication and Synchronization in Graph Computations
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CuMF_SGD: Parallelized Stochastic Gradient Descent for Matrix Factorization on GPUs
Xiaolong Xie, Wei Tan, Liana L. Fong, Yun Liang
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CuMF_SGD: Parallelized Stochastic Gradient Descent for Matrix Factorization on GPUs
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Diagnosing Machine Learning Pipelines with Fine-grained Lineage
Zhao Zhang, Evan R. Sparks, Michael J. Franklin
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Diagnosing Machine Learning Pipelines with Fine-grained Lineage
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Explaining Wide Area Data Transfer Performance
Zhengchun Liu, Prasanna Balaprakash, Rajkumar Kettimuthu, Ian T. Foster
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Explaining Wide Area Data Transfer Performance
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