Technical Papers SC18 Proceedings

Technical Papers

  1. 167-PFlops Deep Learning for Electron Microscopy: From Learning Physics to Atomic Manipulation Robert M. Patton, J. Travis Johnston, Steven R. Young, Catherine D. Schuman, Don D. March, Thomas E. Potok, Derek C. Rose, Seung-Hwan Lim, Thomas P. Karnowski, Maxim A. Ziatdinov, and Sergei V. Kalinin (Oak Ridge National Laboratory)

  2. Accelerating Quantum Chemistry with Vectorized and Batched Integrals Hua Huang and Edmond Chow (Georgia Institute of Technology)

  3. ADAPT: Algorithmic Differentiation Applied to Floating-Point Precision Tuning Harshitha Menon (Lawrence Livermore National Laboratory); Michael O. Lam (James Madison University, Lawrence Livermore National Laboratory); and Daniel Osei-Kuffuor, Markus Schordan, Scott Lloyd, Kathryn Mohror, and Jeffrey Hittinger (Lawrence Livermore National Laboratory)

  4. Adaptive Anonymization of Data with b-Edge Covers Arif Khan (Pacific Northwest National Laboratory), Krzysztof Choromanski (Google LLC), Alex Pothen and S M Ferdous (Purdue University), and Mahantesh Halappanavar and Antonino Tumeo (Pacific Northwest National Laboratory)

  5. Anatomy of High-Performance Deep Learning Convolutions on SIMD Architectures Evangelos Georganas, Sasikanth Avancha, Kunal Banerjee, Dhiraj Kalamkar, Greg Henry, Hans Pabst, and Alexander Heinecke (Intel Corporation)

  6. Associative Instruction Reordering to Alleviate Register Pressure Prashant Singh Rawat, Aravind Sukumaran-Rajam, and Atanas Rountev (Ohio State University); Fabrice Rastello (French Institute for Research in Computer Science and Automation (INRIA)); Louis-Noel Pouchet (Colorado State University); and P. Sadayappan (Ohio State University)

  7. Attacking the Opioid Epidemic: Determining the Epistatic and Pleiotropic Genetic Architectures for Chronic Pain and Opioid Addiction Wayne Joubert (Oak Ridge National Laboratory); Deborah Weighill (Oak Ridge National Laboratory, University of Tennessee); David Kainer (Oak Ridge National Laboratory); Sharlee Climer (University of Missouri, St Louis); Amy Justice (Yale University, US Department of Veterans Affairs); Kjiersten Fagnan (Lawrence Berkeley National Laboratory, US Department of Energy Joint Genome Institute); and Daniel Jacobson (Oak Ridge National Laboratory)

  8. BESPOKV: Application Tailored Scale-Out Key-Value Stores Ali Anwar (IBM), Yue Cheng (George Mason University), Hai Huang (IBM), Jingoo Han (Virginia Tech), Hyogi Sim (Oak Ridge National Laboratory), Dongyoon Lee (Virginia Tech), Fred Douglis (Perspecta Labs), and Ali R. Butt (Virginia Tech)

  9. Best Practices and Lessons from Deploying and Operating a Sustained-Petascale System: The Blue Waters Experience Gregory H. Bauer, Brett Bode, Jeremy Enos, William T. Kramer, Scott Lathrop, Celso L. Mendes, and Roberto R. Sisneros (University of Illinois, National Center for Supercomputing Applications)

  10. Characterization of MPI Usage on a Production Supercomputer Sudheer Chunduri, Scott Parker, Pavan Balaji, Kevin Harms, and Kalyan Kumaran (Argonne National Laboratory)

  11. Computing Planetary Interior Normal Modes with a Highly Parallel Polynomial Filtering Eigensolver Jia Shi (Rice University), Ruipeng Li (Lawrence Livermore National Laboratory), Yuanzhe Xi and Yousef Saad (University of Minnesota), and Maarten V. de Hoop (Rice University)

  12. Cooperative Rendezvous Protocols for Improved Performance and Overlap S. Chakraborty, M. Bayatpour, J. Hashmi, H. Subramoni, and D. K. Panda (Ohio State University)

  13. CosmoFlow: Using Deep Learning to Learn the Universe at Scale Amrita Mathuriya (Intel Corporation); Deborah Bard (National Energy Research Scientific Computing Center (NERSC), Lawrence Berkeley National Laboratory); Pete Mendygral (Cray Inc); Lawrence Meadows (Intel Corporation); James Arnemann (University of California, Berkeley); Lei Shao (Intel Corporation); Siyu He (Carnegie Mellon University); Tuomas Karna (Intel Corporation); Diana Moise (Cray Inc); Simon J. Pennycook (Intel Corporation); Kristyn Maschhoff (Cray Inc); Jason Sewall and Nalini Kumar (Intel Corporation); Shirley Ho (Lawrence Berkeley National Laboratory, Carnegie Mellon University); Michael F. Ringenburg (Cray Inc); Mr Prabhat (Lawrence Berkeley National Laboratory, National Energy Research Scientific Computing Center (NERSC)); and Victor Lee (Intel Corporation)

  14. Dac-Man: Data Change Management for Scientific Datasets on HPC Systems Devarshi Ghoshal, Lavanya Ramakrishnan, and Deborah Agarwal (Lawrence Berkeley National Laboratory)

  15. The Design, Deployment, and Evaluation of the CORAL Pre-Exascale Systems Sudharshan S. Vazhkudai (Oak Ridge National Laboratory); Bronis R. de Supinski (Lawrence Livermore National Laboratory); Arthur S. Bland and Al Geist (Oak Ridge National Laboratory); James Sexton and Jim Kahle (IBM); Christopher J. Zimmer, Scott Atchley, Sarp H. Oral, Don E. Maxwell, and Veronica G. Vergara Larrea (Oak Ridge National Laboratory); Adam Bertsch and Robin Goldstone (Lawrence Livermore National Laboratory); Wayne Joubert (Oak Ridge National Laboratory); Chris Chambreau (Lawrence Livermore National Laboratory); David Appelhans and Robert Blackmore (IBM); Ben Casses (Lawrence Livermore National Laboratory); George Chochia and Gene Davison (IBM); Matthew A. Ezell (Oak Ridge National Laboratory); Tom Gooding (IBM); Elsa Gonsiorowski (Lawrence Livermore National Laboratory); Leopold Grinberg, Bill Hanson, and Bill Hartner (IBM); Ian Karlin and Matthew L. Leininger (Lawrence Livermore National Laboratory); Dustin Leverman (Oak Ridge National Laboratory); Chris Marroquin (IBM); Adam Moody (Lawrence Livermore National Laboratory); Martin Ohmacht (IBM); Ramesh Pankajakshan (Lawrence Livermore National Laboratory); Fernando Pizzano (IBM); James H. Rogers (Oak Ridge National Laboratory); Bryan Rosenburg (IBM); Drew Schmidt, Mallikarjun Shankar, and Feiyi Wang (Oak Ridge National Laboratory); Py Watson (Lawrence Livermore National Laboratory); Bob Walkup (IBM); Lance D. Weems (Lawrence Livermore National Laboratory); and Junqi Yin (Oak Ridge National Laboratory)

  16. Detecting MPI Usage Anomalies via Partial Program Symbolic Execution Fangke Ye, Jisheng Zhao, and Vivek Sarkar (Georgia Institute of Technology)

  17. Distributed Memory Sparse Inverse Covariance Matrix Estimation on High-Performance Computing Architectures Aryan Eftekhari (University of Lugano), Matthias Bollhöfer (Braunschweig University of Technology), and Olaf Schenk (University of Lugano)

  18. Distributed-Memory Hierarchical Compression of Dense SPD Matrices Chenhan D. Yu (University of Texas), Severin Reiz (Technical University Munich), and George Biros (University of Texas)

  19. A Divide and Conquer Algorithm for DAG Scheduling Under Power Constraints Gökalp Demirci, Ivana Marincic, and Henry Hoffmann (University of Chicago)

  20. Doomsday: Predicting Which Node Will Fail When on Supercomputers Anwesha Das and Frank Mueller (North Carolina State University) and Paul Hargrove, Eric Roman, and Scott Baden (Lawrence Berkeley National Laboratory)

  21. DRAGON: Breaking GPU Memory Capacity Limits with Direct NVM Access Pak Markthub (Tokyo Institute of Technology); Mehmet E. Belviranli, Seyong Lee, and Jeffrey S. Vetter (Oak Ridge National Laboratory); and Satoshi Matsuoka (RIKEN, Tokyo Institute of Technology)

  22. Dynamic Data Race Detection for OpenMP Programs Yizi Gu and John Mellor-Crummey (Rice University)

  23. Dynamic Tracing: Memoization of Task Graphs for Dynamic Task-Based Runtimes Wonchan Lee (Stanford University), Elliott Slaughter (SLAC National Accelerator Laboratory), Michael Bauer and Sean Treichler (Nvidia Corporation), Todd Warszawski (Stanford University), Michael Garland (Nvidia Corporation), and Alex Aiken (Stanford University)

  24. Dynamically Negotiating Capacity Between On-Demand and Batch Clusters Feng Liu (University of Minnesota), Kate Keahey (Argonne National Laboratory), Pierre Riteau (University of Chicago), and Jon Weissman (University of Minnesota)

  25. Energy Efficiency Modeling of Parallel Applications Mark Endrei, Chao Jin, Minh Ngoc Dinh, and David Abramson (University of Queensland); Heidi Poxon and Luiz DeRose (Cray Inc); and Bronis R. de Supinski (Lawrence Livermore National Laboratory)

  26. Evaluating and Accelerating High-Fidelity Error Injection for HPC Chun-Kai Chang, Sangkug Lym, and Nicholas Kelly (University of Texas); Michael B. Sullivan (Nvidia Corporation); and Mattan Erez (University of Texas)

  27. Evaluation of an Interference-Free Node Allocation Policy on Fat-Tree Clusters Samuel D. Pollard (University of Oregon) and Nikhil Jain, Stephen Herbein, and Abhinav Bhatele (Lawrence Livermore National Laboratory)

  28. Exascale Deep Learning for Climate Analytics Thorsten Kurth (Lawrence Berkeley National Laboratory), Sean Treichler and Joshua Romero (Nvidia Corporation), Mayur Mudigonda (Lawrence Berkeley National Laboratory), Nathan Luehr and Everett Phillips (Nvidia Corporation), Ankur Mahesh (Lawrence Berkeley National Laboratory), Michael Matheson (Oak Ridge National Laboratory), Jack Deslippe (Lawrence Berkeley National Laboratory), Massimiliano Fatica (Nvidia Corporation), Mr Prabhat (Lawrence Berkeley National Laboratory), and Michael Houston (Nvidia Corporation)

  29. Exploiting Idle Resources in a High-Radix Switch for Supplemental Storage Matthias A. Blumrich, Nan Jiang, and Larry R. Dennison (Nvidia Corporation)

  30. Exploring Flexible Communications for Streamlining DNN Ensemble Training Pipelines Randall Pittman, Hui Guan, and Xipeng Shen (North Carolina State University) and Seung-Hwan Lim and Robert M. Patton (Oak Ridge National Laboratory)

  31. Extreme Scale De Novo Metagenome Assembly Evangelos Georganas (Intel Corporation) and Rob Egan, Steven Hofmeyr, Eugene Goltsman, Bill Arndt, Andrew Tritt, Aydin Buluc, Leonid Oliker, and Katherine Yelick (Lawrence Berkeley National Laboratory)

  32. faimGraph: High Performance Management of Fully-Dynamic Graphs Under Tight Memory Constraints on the GPU Martin Winter and Daniel Mlakar (Graz University of Technology); Rhaleb Zayer and Hans-Peter Seidel (Max Planck Institute for Informatics); and Markus Steinberger (Graz University of Technology, Max Planck Institute for Informatics)

  33. A Fast Scalable Implicit Solver for Nonlinear Time-Evolution Earthquake City Problem on Low-Ordered Unstructured Finite Elements with Artificial Intelligence and Transprecision Computing Tsuyoshi Ichimura, Kohei Fujita, and Takuma Yamaguchi (University of Tokyo); Akira Naruse (Nvidia Corporation); Jack C. Wells (Oak Ridge National Laboratory); Thomas C. Schulthess (Swiss National Supercomputing Centre); Tjerk P. Straatsma and Christopher J. Zimmer (Oak Ridge National Laboratory); Maxime Martinasso (Swiss National Supercomputing Centre); and Kengo Nakajima, Muneo Hori, and Lalith Maddegedara (University of Tokyo)

  34. Fault Tolerant One-Sided Matrix Decompositions on Heterogeneous Systems with GPUs Jieyang Chen, Hongbo Li, Sihuan Li, and Xin Liang (University of California, Riverside); Panruo Wu (University of Houston); Dingwen Tao (University of Alabama); Kaiming Ouyang, Yuanlai Liu, and Kai Zhao (University of California, Riverside); Qiang Guan (Kent State University); and Zizhong Chen (University of California, Riverside)

  35. Fine-Grained, Multi-Domain Network Resource Abstraction as a Fundamental Primitive to Enable High-Performance, Collaborative Data Sciences Qiao Xiang (Yale University); J. Jensen Zhang, X. Tony Wang, and Y. Jace Liu (Tongji University); Chin Guok (Lawrence Berkeley National Laboratory); Franck Le (IBM); John MacAuley (Lawrence Berkeley National Laboratory); Harvey Newman (California Institute of Technology); and Y. Richard Yang (Yale University)

  36. FlipTracker: Understanding Natural Error Resilience in HPC Applications Luanzheng Guo and Dong Li (University of California, Merced); Ignacio Laguna (Lawrence Livermore National Laboratory); and Martin Schulz (Technical University Munich)

  37. Framework for Scalable Intra-Node Collective Operations Using Shared Memory Surabhi Jain, Rashid Kaleem, Marc Gamell Balmana, Akhil Langer, Dmitry Durnov, Alexander Sannikov, and Maria Garzaran (Intel Corporation)

  38. GPU Age-Aware Scheduling to Improve the Reliability of Leadership Jobs on Titan Christopher Zimmer, Don Maxwell, Stephen McNally, Scott Atchley, and Sudharshan S. Vazhkudai (Oak Ridge National Laboratory)

  39. Harnessing GPU's Tensor Cores Fast FP16 Arithmetic to Speedup Mixed-Precision Iterative Refinement Solvers Azzam Haidar (University of Tennessee, Innovative Computing Laboratory); Stan Tomov and Jack Dongarra (University of Tennessee); and Nicholas Higham (University of Manchester, School of Mathematics)

  40. HiCOO: Hierarchical Storage of Sparse Tensors Jiajia Li, Jimeng Sun, and Richard Vuduc (Georgia Institute of Technology)

  41. High-Performance Dense Tucker Decomposition on GPU Clusters Jee Choi (IBM), Xing Liu (Intel Corporation), and Venkatesan Chakaravarthy (IBM)

  42. HPL and DGEMM Performance Variability on the Xeon Platinum 8160 Processor John D. McCalpin (University of Texas, Texas Advanced Computing Center)

  43. iSpan: Parallel Identification of Strongly Connected Components with Spanning Trees Yuede Ji (George Washington University); Hang Liu (University of Massachusetts, Lowell); and H. Howie Huang (George Washington University)

  44. Large-Scale Hierarchical K-Means for Heterogeneous Many-Core Supercomputers Liandeng Li (Tsinghua University; National Supercomputing Center, Wuxi); Teng Yu (University of St Andrews); Wenlai Zhao and Haohuan Fu (Tsinghua University; National Supercomputing Center, Wuxi); Chenyu Wang (University of St Andrews; National Supercomputing Center, Wuxi); Li Tan (Beijing Technology and Business University); Guangwen Yang (Tsinghua University; National Supercomputing Center, Wuxi); and John Thomson (University of St Andrews)

  45. Lessons Learned from Analyzing Dynamic Promotion for User-Level Threading Shintaro Iwasaki (University of Tokyo), Abdelhalim Amer (Argonne National Laboratory), Kenjiro Taura (University of Tokyo), and Pavan Balaji (Argonne National Laboratory)

  46. Lessons Learned from Memory Errors Observed Over the Lifetime of Cielo Scott Levy and Kurt B. Ferreira (Sandia National Laboratories), Nathan DeBardeleben (Los Alamos National Laboratory), Taniya Siddiqua and Vilas Sridharan (Advanced Micro Devices Inc), and Elisabeth Baseman (Los Alamos National Laboratory)

  47. Light-Weight Protocols for Wire-Speed Ordering Hans Eberle and Larry Dennison (Nvidia Corporation)

  48. A Lightweight Model for Right-Sizing Master-Worker Applications Nathaniel Kremer-Herman, Benjamin Tovar, and Douglas Thain (University of Notre Dame)

  49. Many-Core Graph Workload Analysis Stijn Eyerman, Wim Heirman, Kristof Du Bois, Joshua B. Fryman, and Ibrahim Hur (Intel Corporation)

  50. Mitigating Inter-Job Interference Using Adaptive Flow-Aware Routing Staci A. Smith, Clara E. Cromey, and David K. Lowenthal (University of Arizona); Jens Domke (Tokyo Institute of Technology); and Nikhil Jain, Jayaraman J. Thiagarajan, and Abhinav Bhatele (Lawrence Livermore National Laboratory)

  51. Optimizing High Performance Distributed Memory Parallel Hash Tables for DNA k-mer Counting Tony C. Pan (Georgia Institute of Technology, School of Computational Science and Engineering); Sanchit Misra (Intel Corporation, Parallel Computing Lab); and Srinivas Aluru (Georgia Institute of Technology, School of Computational Science and Engineering)

  52. Optimizing Software-Directed Instruction Replication for GPU Error Detection Abdulrahman Mahmoud (University of Illinois) and Siva Kumar Sastry Hari, Michael B. Sullivan, Timothy Tsai, and Stephen W. Keckler (Nvidia Corporation)

  53. A Parallelism Profiler with What-If Analyses for OpenMP Programs Nader Boushehrinejadmoradi, Adarsh Yoga, and Santosh Nagarakatte (Rutgers University)

  54. ParSy: Inspection and Transformation of Sparse Matrix Computations for Parallelism Kazem Cheshmi (University of Toronto), Shoaib Kamil (Adobe Research), Michelle Mills Strout (University of Arizona), and Maryam Mehri Dehnavi (University of Toronto)

  55. Partial Redundancy in HPC Systems with Non-Uniform Node Reliabilities Zaeem Hussain, Taieb Znati, and Rami Melhem (University of Pittsburgh)

  56. Performance Evaluation of a Vector Supercomputer SX-Aurora TSUBASA Kazuhiko Komatsu (Tohoku University); Shintaro Momose, Yoko Isobe, Osamu Watanabe, and Akihiro Musa (Tohoku University, NEC Corporation); Mitsuo Yokokawa (Kobe University); Toshikazu Aoyama (NEC Corporation); and Masayuki Sato and Hiroaki Kobayashi (Tohoku University)

  57. Phase Asynchronous AMR Execution for Productive and Performant Astrophysical Flows Muhammad Nufail Farooqi (Koc University); Tan Nguyen, Weiqun Zhang, Ann S. Almgren, and John Shalf (Lawrence Berkeley National Laboratory); and Didem Unat (Koc University)

  58. PRISM: Predicting Resilience of GPU Applications Using Statistical Methods Charu Kalra, Fritz Previlon, and Xiangyu Li (Northeastern University); Norman Rubin (Nvidia Corporation); and David Kaeli (Northeastern University)

  59. PruneJuice: Pruning Trillion-Edge Graphs to a Precise Pattern-Matching Solution Tahsin Reza, Matei Ripeanu, and Nicolas Tripoul (University of British Columbia) and Geoffrey Sanders and Roger Pearce (Lawrence Livermore National Laboratory)

  60. Redesigning LAMMPS for Petascale and Hundred-Billion-Atom Simulation on Sunway TaihuLight Xiaohui Duan, Ping Gao, Tingjian Zhang, Meng Zhang, and Weiguo Liu (Shandong University); Wusheng Zhang, Wei Xue, Haohuan Fu, Lin Gan, and Dexun Chen (Tsinghua University); Xiangxu Meng (Shandong University); and Guangwen Yang (Tsinghua University)

  61. A Reference Architecture for Datacenter Scheduling: Design, Validation, and Experiments Georgios Andreadis (Delft University of Technology, Vrije University Amsterdam); Laurens Versluis (Vrije University Amsterdam); Fabian Mastenbroek (Delft University of Technology); and Alexandru Iosup (Vrije University Amsterdam, Delft University of Technology)

  62. RM-Replay: A High-Fidelity Tuning, Optimization and Exploration Tool for Resource Management Maxime Martinasso, Miguel Gila, Mauro Bianco, Sadaf R. Alam, Colin McMurtrie, and Thomas C. Schulthess (Swiss National Supercomputing Centre)

  63. Runtime Data Management on Non-Volatile Memory-Based Heterogeneous Memory for Task-Parallel Programs Kai Wu, Jie Ren, and Dong Li (University of California, Merced)

  64. Runtime-Assisted Cache Coherence Deactivation in Task Parallel Programs Paul Caheny (Barcelona Supercomputing Center, Polytechnic University of Catalonia); Lluc Alvarez (Barcelona Supercomputing Center); Mateo Valero and Miquel Moretó (Barcelona Supercomputing Center, Polytechnic University of Catalonia); and Marc Casas (Barcelona Supercomputing Center)

  65. Scaling Embedded In Situ Indexing with DeltaFS Qing Zheng, Charles D. Cranor, Danhao Guo, Gregory R. Ganger, George Amvrosiadis, and Garth A. Gibson (Carnegie Mellon University) and Bradley W. Settlemyer, Gary Grider, and Fan Guo (Los Alamos National Laboratory)

  66. ShenTu: Processing Multi-Trillion Edge Graphs on Millions of Cores in Seconds Heng Lin (Tsinghua University, Fma Technology); Xiaowei Zhu (Tsinghua University, Qatar Computing Research Institute); Bowen Yu (Tsinghua University); Xiongchao Tang (Tsinghua University, Qatar Computing Research Institute); Wei Xue and Wenguang Chen (Tsinghua University); Lufei Zhang (State Key Laboratory of Mathematical Engineering and Advanced Computing); Torsten Hoefler (ETH Zurich); Xiaosong Ma (Qatar Computing Research Institute); Xin Liu (National Research Centre of Parallel Computer Engineering and Technology); Weimin Zheng (Tsinghua University); and Jingfang Xu (Beijing Sogou Technology Development Company)

  67. Siena: Exploring the Design Space of Heterogeneous Memory Systems Ivy B. Peng and Jeffrey S. Vetter (Oak Ridge National Laboratory)

  68. Simulating the Weak Death of the Neutron in a Femtoscale Universe with Near-Exascale Computing Evan Berkowitz (Forschungszentrum Juelich); M.A. Clark (Nvidia Corporation); Arjun Gambhir (Lawrence Livermore National Laboratory, Lawrence Berkeley National Laboratory); Ken McElvain (University of California, Berkeley; Lawrence Berkeley National Laboratory); Amy Nicholson (University of North Carolina); Enrico Rinaldi (RIKEN BNL Research Center, Lawrence Berkeley National Laboratory); Pavlos Vranas (Lawrence Livermore National Laboratory, Lawrence Berkeley National Laboratory); André Walker-Loud (Lawrence Berkeley National Laboratory, Lawrence Livermore National Laboratory); Chia Cheng Chang (Lawrence Berkeley National Laboratory, RIKEN); Bálint Joó (Thomas Jefferson National Accelerator Facility); Thorsten Kurth (Lawrence Berkeley National Laboratory); and Kostas Orginos (College of William & Mary, Thomas Jefferson National Accelerator Facility)

  69. Simulating the Wenchuan Earthquake with Accurate Surface Topography on Sunway TaihuLight Bingwei Chen, Haohuan Fu, Yanwen Wei, and Conghui He (Tsinghua University; National Supercomputing Center, Wuxi); Wenqiang Zhang (University of Science and Technology of China); Yuxuan Li (Tsinghua University; National Supercomputing Center, Wuxi); Wubin Wan and Wei Zhang (National Supercomputing Center, Wuxi); Lin Gan (Tsinghua University; National Supercomputing Center, Wuxi); Wei Zhang and Zhenguo Zhang (Southern University of Science and Technology, China); Guangwen Yang (Tsinghua University; National Supercomputing Center, Wuxi); and Xiaofei Chen (Southern University of Science and Technology, China)

  70. SP-Cache: Load-Balanced, Redundancy-Free Cluster Caching with Selective Partition Yinghao Yu, Renfei Huang, Wei Wang, Jun Zhang, and Khaled Ben Letaief (Hong Kong University of Science and Technology)

  71. Stacker: An Autonomic Data Movement Engine for Extreme-Scale Data Staging-Based In Situ Workflows Pradeep Subedi, Philip Davis, and Shaohua Duan (Rutgers University); Scott Klasky (Oak Ridge National Laboratory); Hemanth Kolla (Sandia National Laboratories); and Manish Parashar (Rutgers University)

  72. Topology-Aware Space-Shared Co-Analysis of Large-Scale Molecular Dynamics Simulations Preeti Malakar (Indian Institute of Technology Kanpur); Todd Munson, Christopher Knight, and Venkatram Vishwanath (Argonne National Laboratory); and Michael E. Papka (Argonne National Laboratory, Northern Illinois University)

  73. TriCore: Parallel Triangle Counting on GPUs Yang Hu (George Washington University); Hang Liu (University of Massachusetts, Lowell); and H. Howie Huang (George Washington University)

  74. A Year in the Life of a Parallel File System Glenn K. Lockwood (Lawrence Berkeley National Laboratory), Shane Snyder (Argonne National Laboratory), Teng Wang and Suren Byna (Lawrence Berkeley National Laboratory), Philip Carns (Argonne National Laboratory), and Nicholas J. Wright (Lawrence Berkeley National Laboratory)

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