Efficient Data-Parallel Primitives on Heterogeneous Systems
Zhuohang LAI (Hong Kong University of Science and Technology), Qiong LUO (Hong Kong University of Science and Technology), Xiaolong XIE (Alibaba Inc.)
Accelerated Work Stealing
D. Brian Larkins (Rhodes College), John Snyder (Duke University), James Dinan (Intel Corporation)
Runtime Adaptive Task Inlining on Asynchronous Multitasking Runtime Systems
Bibek Wagle (Louisiana State University), Mohammad Alaul Haque Monil (University Of Oregon), Kevin Huck (University Of Oregon), Allen D. Malony (University Of Oregon), Adrian Serio (Louisiana State University), Hartmut Kaiser (Louisiana State University)
HOPE: A Parallel Execution Model Based on Hierarchical Omission
Masahiro Yasugi (Kyushu Institute of Technology), Daisuke Muraoka (Kyushu Institute of Technology), Tasuku Hiraishi (Kyoto University), Seiji Umatani (Kanagawa University), Kento Emoto (Kyushu Institute of Technology)
Session T7B: Performance Modeling
Date: – , Thursday, August 8th
Location: Room-1
Chair: Toshio Endo
Performance, Energy, and Scalability Analysis and Improvement of Parallel Cancer Deep Learning CANDLE Benchmarks
Xingfu Wu (Argonne National Laboratory, University of Chicago), Valerie Taylor (Argonne National Laboratory, University of Chicago), Justin M. Wozniak (Argonne National Laboratory, University of Chicago), Rick Stevens (Argonne National Laboratory, University of Chicago), Thomas Brettin (Argonne National Laboratory), Fangfang Xia (Argonne National Laboratory)
Adaptive Learning for Concept Drift in Application Performance Modeling(Video presentation)
Sandeep Madireddy (Argonne National Laboratory), Prasanna Balaprakash (Argonne National Laboratory), Philip Carns (Argonne National Laboratory), Robert Latham (Argonne National Laboratory), Glenn K. Lockwood (Lawrence Berkeley National Laboratory), Robert Ross (Argonne National Laboratory), Shane Snyder (Argonne National Laboratory), Stefan M. Wild (Argonne National Laboratory)
I/O Characterization and Performance Evaluation of BeeGFS for Deep Learning
Fahim Tahmid Chowdhury (Florida State University), Yue Zhu (Florida State University), Todd Heer (Lawrence Livermore National Laboratory), Saul Paredes (Florida State University), Adam Moody (Lawrence Livermore National Laboratory), Robin Goldstone (Lawrence Livermore National Laboratory), Kathryn Mohror (Lawrence Livermore National Laboratory), Weikuan Yu (Florida State University)
Performance Models for Data Transfers: A Case Study with Molecular Chemistry Kernels
Suraj Kumar (Pacific Northwest National Laboratory), Lionel Eyraud-Dubois (Inria Bordeaux Sud-Ouest), Sriram Krishnamoorthy (Pacific Northwest National Laboratory)
Session T7C: Simulation Techniques
Date: – , Thursday, August 8th
Location: Room-2
Chair: Richard Vuduc
OSP: Overlapping Computation and Communication in Parameter Server for Fast Machine Learning
Haozhao Wang (Huazhong University of Science and Technology, PolyU: The Hong Kong Polytechnic University), Song Guo (The Hong Kong Polytechnic University), Ruixuan Li (Huazhong University of Science and Technology)
Automatic Differentiation for Adjoint Stencil Loops*Best Paper Candidate
Jan Huckelheim (Imperial College London), Navjot Kukreja (Imperial College London), Sri Hari Krishna Narayanan (Argonne National Laboratory), Fabio Luporini (Imperial College London), Gerard Gorman (Imperial College London), Paul Hovland (Argonne National Laboratory)
Spatially-aware Parallel I/O for Particle Data
Sidharth Kumar (University of Alabama at Birmingham), Steve Petruzza (University of Utah), Will Usher (University of Utah), Valerio Pascucci (University of Utah)
The Communication-Overlapped Hybrid Decomposition Parallel Algorithm for Multi-Scale Fluid Simulations(Video presentation)
Yi Liu (National University of Defense Technology), Xiao-Wei Guo (National University of Defense Technology), Chao Li (National University of Defense Technology), Canqun Yang (National University of Defense Technology), Xinbiao Gan (National University of Defense Technology), Peng Zhang (National University of Defense Technology), Yi Wang (National University of Defense Technology), Ran Zhao (National University of Defense Technology), Sijiang Fan (National University of Defense Technology)
