| 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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PruneJuice: pruning trillion-edge graphs to a precise pattern-matching solution Tahsin Reza, Matei Ripeanu, Nicolas Tripoul, Geoffrey Sanders, Roger Pearce |
PruneJuice: pruning trillion-edge graphs to a precise pattern-matching solution Details |
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Energy efficiency modeling of parallel applications Mark Endrei, Chao Jin, Minh Ngoc Dinh, David Abramson, Heidi Poxon, Luiz DeRose, Bronis R. de Supinski |
Energy efficiency modeling of parallel applications Details |
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Aryan Eftekhari, Matthias Bollhöfer, Olaf Schenk |
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Extreme scale de novo metagenome assembly Evangelos Georganas, Rob Egan, Steven A. Hofmeyr, Eugene Goltsman, Bill Arndt, Andrew Tritt, Aydin Buluç, Leonid Oliker, Katherine A. Yelick |
Extreme scale de novo metagenome assembly Details |
Artifacts for some papers are reviewed by an artifact evaluation, reproducibility,
or similarly named committee. This is one such paper that passed review.
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A year in the life of a parallel file system Glenn K. Lockwood, Shane Snyder, Teng Wang, Suren Byna, Philip H. Carns, Nicholas J. Wright |
A year in the life of a parallel file system Details |
Artifacts for some papers are reviewed by an artifact evaluation, reproducibility,
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Unless exact reproducibility is desired, more up-to-date code and datasets are available through the Zenodo links.
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GPU age-aware scheduling to improve the reliability of leadership jobs on Titan Christopher Zimmer, Don Maxwell, Stephen McNally, Scott Atchley, Sudharshan S. Vazhkudai |
GPU age-aware scheduling to improve the reliability of leadership jobs on Titan Details |
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Gregory H. Bauer, Brett M. Bode, Jeremy Enos, William T. Kramer, Scott Lathrop, Celso L. Mendes, Robert Sisneros |
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FlipTracker: understanding natural error resilience in HPC applications Luanzheng Guo, Dong Li, Ignacio Laguna, Martin Schulz |
FlipTracker: understanding natural error resilience in HPC applications Details |
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Phase asynchronous AMR execution for productive and performant astrophysical flows Muhammed Nufail Farooqi, Tan Nguyen, Weiqun Zhang, Ann S. Almgren, John Shalf, Didem Unat |
Phase asynchronous AMR execution for productive and performant astrophysical flows Details |
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Exascale deep learning for climate analytics Thorsten Kurth, Sean Treichler, Joshua Romero, Mayur Mudigonda, Nathan Luehr, Everett H. Phillips, Ankur Mahesh, Michael Matheson, Jack Deslippe, Massimiliano Fatica, Prabhat, Michael Houston |
Exascale deep learning for climate analytics Details |
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Cooperative rendezvous protocols for improved performance and overlap Sourav Chakraborty, Mohammadreza Bayatpour, Jahanzeb Maqbool Hashmi, Hari Subramoni, Dhabaleswar K. Panda |
Cooperative rendezvous protocols for improved performance and overlap Details |
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RM-replay: a high-fidelity tuning, optimization and exploration tool for resource management Maxime Martinasso, Miguel Gila, Mauro Bianco, Sadaf R. Alam, Colin McMurtrie, Thomas C. Schulthess |
RM-replay: a high-fidelity tuning, optimization and exploration tool for resource management Details |
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Evaluating and accelerating high-fidelity error injection for HPC Chun-Kai Chang, Sangkug Lym, Nicholas Kelly, Michael B. Sullivan, Mattan Erez |
Evaluating and accelerating high-fidelity error injection for HPC Details |
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CosmoFlow: using deep learning to learn the universe at scale Amrita Mathuriya, Deborah Bard, Peter Mendygral, Lawrence Meadows, James Arnemann, Lei Shao, Siyu He, Tuomas Kärnä, Diana Moise, Simon J. Pennycook, Kristyn J. Maschhoff, Jason Sewall, Nalini Kumar, Shirley Ho, Michael F. Ringenburg, Prabhat, Victor W. Lee |
CosmoFlow: using deep learning to learn the universe at scale Details |
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Distributed-memory hierarchical compression of dense SPD matrices Chenhan D. Yu, Severin Reiz, George Biros |
Distributed-memory hierarchical compression of dense SPD matrices Details |
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bespoKV: application tailored scale-out key-value stores Ali Anwar, Yue Cheng, Hai Huang, Jingoo Han, Hyogi Sim, Dongyoon Lee, Fred Douglis, Ali Raza Butt |
bespoKV: application tailored scale-out key-value stores Details |
Artifacts for some papers are reviewed by an artifact evaluation, reproducibility,
or similarly named committee. This is one such paper that passed review.
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Partial redundancy in HPC systems with non-uniform node reliabilities Zaeem Hussain, Taieb Znati, Rami G. Melhem |
Partial redundancy in HPC systems with non-uniform node reliabilities Details |
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Azzam Haidar, Stanimire Tomov, Jack J. Dongarra, Nicholas J. Higham |
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SP-cache: load-balanced, redundancy-free cluster caching with selective partition Yinghao Yu, Renfei Huang, Wei Wang, Jun Zhang, Khaled Ben Letaief |
SP-cache: load-balanced, redundancy-free cluster caching with selective partition Details |
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Tsuyoshi Ichimura, Kohei Fujita, Takuma Yamaguchi, Akira Naruse, Jack C. Wells, Thomas C. Schulthess, Tjerk P. Straatsma, Christopher Zimmer, Maxime Martinasso, Kengo Nakajima, Muneo Hori, Lalith Maddegedara |
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Exploring flexible communications for streamlining DNN ensemble training pipelines Randall Pittman, Hui Guan, Xipeng Shen, Seung-Hwan Lim, Robert M. Patton |
Exploring flexible communications for streamlining DNN ensemble training pipelines Details |
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DRAGON: breaking GPU memory capacity limits with direct NVM access Pak Markthub, Mehmet E. Belviranli, Seyong Lee, Jeffrey S. Vetter, Satoshi Matsuoka |
DRAGON: breaking GPU memory capacity limits with direct NVM access Details |
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A parallelism profiler with what-if analyses for OpenMP programs Nader Boushehrinejadmoradi, Adarsh Yoga, Santosh Nagarakatte |
A parallelism profiler with what-if analyses for OpenMP programs Details |
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or similarly named committee. This is one such paper that passed review.
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Wayne Joubert, Deborah A. Weighill, David Kainer, Sharlee Climer, Amy Justice, Kjiersten Fagnan, Daniel A. Jacobson |
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Adaptive anonymization of data using b-edge cover Arif Khan, Krzysztof Choromanski, Alex Pothen, S. M. Ferdous, Mahantesh Halappanavar, Antonino Tumeo |
Adaptive anonymization of data using b-edge cover Details |
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Runtime-assisted cache coherence deactivation in task parallel programs Paul Caheny, Lluc Alvarez, Mateo Valero, Miquel Moretó, Marc Casas |
Runtime-assisted cache coherence deactivation in task parallel programs Details |
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A reference architecture for datacenter scheduling: design, validation, and experiments Georgios Andreadis, Laurens Versluis, Fabian Mastenbroek, Alexandru Iosup |
A reference architecture for datacenter scheduling: design, validation, and experiments Details |
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Doomsday: predicting which node will fail when on supercomputers Anwesha Das, Frank Mueller, Paul Hargrove, Eric Roman, Scott B. Baden |
Doomsday: predicting which node will fail when on supercomputers Details |
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Simulating the weak death of the Neutron in a femtoscale universe with near-exascale computing Evan Berkowitz, Michael A. Clark, Arjun Singh Gambhir, Kenneth McElvain, Amy Nicholson, Enrico Rinaldi, Pavlos Vranas, André Walker-Loud, Chia-Cheng Chang, Bálint Joó, Thorsten Kurth, Kostas Orginos |
Simulating the weak death of the Neutron in a femtoscale universe with near-exascale computing Details |
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Performance evaluation of a vector supercomputer SX-aurora TSUBASA Kazuhiko Komatsu, Shintaro Momose, Yoko Isobe, Osamu Watanabe, Akihiro Musa, Mitsuo Yokokawa, Toshikazu Aoyama, Masayuki Sato, Hiroaki Kobayashi |
Performance evaluation of a vector supercomputer SX-aurora TSUBASA Details |
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iSpan: parallel identification of strongly connected components with spanning trees Yuede Ji, Hang Liu, H. Howie Huang |
iSpan: parallel identification of strongly connected components with spanning trees Details |
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Dynamic data race detection for OpenMP programs Yizi Gu, John M. Mellor-Crummey |
Dynamic data race detection for OpenMP programs Details |
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Dac-Man: data change management for scientific datasets on HPC systems Devarshi Ghoshal, Lavanya Ramakrishnan, Deborah A. Agarwal |
Dac-Man: data change management for scientific datasets on HPC systems Details |
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Simulating the Wenchuan earthquake with accurate surface topography on Sunway TaihuLight Bingwei Chen, Haohuan Fu, Yanwen Wei, Conghui He, Wenqiang Zhang, Yuxuan Li, Wubin Wan, Wei Zhang, Lin Gan, Wei Zhang, Zhenguo Zhang, Guangwen Yang, Xiaofei Chen |
Simulating the Wenchuan earthquake with accurate surface topography on Sunway TaihuLight Details |
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Many-core graph workload analysis Stijn Eyerman, Wim Heirman, Kristof Du Bois, Joshua B. Fryman, Ibrahim Hur |
Many-core graph workload analysis Details |
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A divide and conquer algorithm for DAG scheduling under power constraints Gökalp Demirci, Ivana Marincic, Henry Hoffmann |
A divide and conquer algorithm for DAG scheduling under power constraints Details |
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Topology-aware space-shared co-analysis of large-scale molecular dynamics simulations Preeti Malakar, Todd Munson, Christopher Knight, Venkatram Vishwanath, Michael E. Papka |
Topology-aware space-shared co-analysis of large-scale molecular dynamics simulations Details |
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Qiao Xiang, J. Jensen Zhang, X. Tony Wang, Y. Jace Liu, Chin Guok, Franck Le, John MacAuley, Harvey Newman, Yang Richard Yang |
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Exploiting idle resources in a high-radix switch for supplemental storage Matthias A. Blumrich, Nan Jiang, Larry R. Dennison |
Exploiting idle resources in a high-radix switch for supplemental storage Details |
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Optimizing high performance distributed memory parallel hash tables for DNA k-mer counting Tony C. Pan, Sanchit Misra, Srinivas Aluru |
Optimizing high performance distributed memory parallel hash tables for DNA k-mer counting Details |
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TriCore: parallel triangle counting on GPUs Yang Hu, Hang Liu, H. Howie Huang |
TriCore: parallel triangle counting on GPUs Details |
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Framework for scalable intra-node collective operations using shared memory Surabhi Jain, Rashid Kaleem, Marc Gamell Balmana, Akhil Langer, Dmitry Durnov, Alexander Sannikov, Maria Garzaran |
Framework for scalable intra-node collective operations using shared memory Details |
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Computing planetary interior normal modes with a highly parallel polynomial filtering eigensolver Jia Shi, Ruipeng Li, Yuanzhe Xi, Yousef Saad, Maarten V. de Hoop |
Computing planetary interior normal modes with a highly parallel polynomial filtering eigensolver Details |
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Mitigating inter-job interference using adaptive flow-aware routing Staci A. Smith, Clara E. Cromey, David K. Lowenthal, Jens Domke, Nikhil Jain, Jayaraman J. Thiagarajan, Abhinav Bhatele |
Mitigating inter-job interference using adaptive flow-aware routing Details |
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PRISM: predicting resilience of GPU applications using statistical methods Cham Kalra, Fritz Previlon, Xiangyu Li, Norman Rubin, David R. Kaeli |
PRISM: predicting resilience of GPU applications using statistical methods Details |
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PRISM provides a systematic approach to predict failures in GPU programs. PRISM extracts micro-architecture agnostic features to characterize program resiliency, and serves as an effective predictor to drive our statistical model. PRISM can predict failures in applications without running exhaustive fault injection campaigns, thereby reducing the error estimation effort.
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ShenTu: processing multi-trillion edge graphs on millions of cores in seconds Heng Lin, Xiaowei Zhu, Bowen Yu, Xiongchao Tang, Wei Xue, Wenguang Chen, Lufei Zhang, Torsten Hoefler, Xiaosong Ma, Xin Liu, Weimin Zheng, Jingfang Xu |
ShenTu: processing multi-trillion edge graphs on millions of cores in seconds Details |
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Lessons learned from analyzing dynamic promotion for user-level threading Shintaro Iwasaki, Abdelhalim Amer, Kenjiro Taura, Pavan Balaji |
Lessons learned from analyzing dynamic promotion for user-level threading Details |
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Siena: exploring the design space of heterogeneous memory systems Ivy Bo Peng, Jeffrey S. Vetter |
Siena: exploring the design space of heterogeneous memory systems Details |
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Martin Winter, Daniel Mlakar, Rhaleb Zayer, Hans-Peter Seidel, Markus Steinberger |
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High-performance dense tucker decomposition on GPU clusters Jee W. Choi, Xing Liu, Venkatesan T. Chakaravarthy |
High-performance dense tucker decomposition on GPU clusters Details |
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A lightweight model for right-sizing master-worker applications Nathaniel Kremer-Herman, Benjamín Tovar, Douglas Thain |
A lightweight model for right-sizing master-worker applications Details |
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Anatomy of high-performance deep learning convolutions on SIMD architectures Evangelos Georganas, Sasikanth Avancha, Kunal Banerjee, Dhiraj D. Kalamkar, Greg Henry, Hans Pabst, Alexander Heinecke |
Anatomy of high-performance deep learning convolutions on SIMD architectures Details |
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Characterization of MPI usage on a production supercomputer Sudheer Chunduri, Scott Parker, Pavan Balaji, Kevin Harms, Kalyan Kumaran |
Characterization of MPI usage on a production supercomputer Details |
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Fault tolerant one-sided matrix decompositions on heterogeneous systems with GPUs Jieyang Chen, Hongbo Li, Sihuan Li, Xin Liang, Panruo Wu, Dingwen Tao, Kaiming Ouyang, Yuanlai Liu, Kai Zhao, Qiang Guan, Zizhong Chen |
Fault tolerant one-sided matrix decompositions on heterogeneous systems with GPUs Details |
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Accelerating quantum chemistry with vectorized and batched integrals Hua Huang, Edmond Chow |
Accelerating quantum chemistry with vectorized and batched integrals Details |
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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, Sergei V. Kalinin |
167-PFlops deep learning for electron microscopy: from learning physics to atomic manipulation Details |
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Dynamically negotiating capacity between on-demand and batch clusters Feng Liu, Kate Keahey, Pierre Riteau, Jon B. Weissman |
Dynamically negotiating capacity between on-demand and batch clusters Details |
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HiCOO: hierarchical storage of sparse tensors Jiajia Li, Jimeng Sun, Richard W. Vuduc |
HiCOO: hierarchical storage of sparse tensors Details |
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Redesigning LAMMPS for peta-scale and hundred-billion-atom simulation on Sunway TaihuLight Xiaohui Duan, Ping Gao, Tingjian Zhang, Meng Zhang, Weiguo Liu, Wusheng Zhang, Wei Xue, Haohuan Fu, Lin Gan, Dexun Chen, Xiangxu Meng, Guangwen Yang |
Redesigning LAMMPS for peta-scale and hundred-billion-atom simulation on Sunway TaihuLight Details |
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Optimizing software-directed instruction replication for GPU error detection Abdulrahman Mahmoud, Siva Kumar Sastry Hari, Michael B. Sullivan, Timothy Tsai, Stephen W. Keckler |
Optimizing software-directed instruction replication for GPU error detection Details |
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Scaling embedded in-situ indexing with deltaFS Qing Zheng, Charles D. Cranor, Danhao Guo, Gregory R. Ganger, George Amvrosiadis, Garth A. Gibson, Bradley W. Settlemyer, Gary Grider, Fan Guo |
Scaling embedded in-situ indexing with deltaFS Details |
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Large-scale hierarchical k-means for heterogeneous many-core supercomputers Liandeng Li, Teng Yu, Wenlai Zhao, Haohuan Fu, Chenyu Wang, Li Tan, Guangwen Yang, John Thomson |
Large-scale hierarchical k-means for heterogeneous many-core supercomputers Details |
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ADAPT: algorithmic differentiation applied to floating-point precision tuning Harshitha Menon, Michael O. Lam, Daniel Osei-Kuffuor, Markus Schordan, Scott Lloyd, Kathryn Mohror, Jeffrey Hittinger |
ADAPT: algorithmic differentiation applied to floating-point precision tuning Details |
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Evaluation of an interference-free node allocation policy on fat-tree clusters Samuel D. Pollard, Nikhil Jain, Stephen Herbein, Abhinav Bhatele |
Evaluation of an interference-free node allocation policy on fat-tree clusters Details |
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Detecting MPI usage anomalies via partial program symbolic execution Fangke Ye, Jisheng Zhao, Vivek Sarkar |
Detecting MPI usage anomalies via partial program symbolic execution Details |
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ParSy: inspection and transformation of sparse matrix computations for parallelism Kazem Cheshmi, Shoaib Kamil, Michelle Mills Strout, Maryam Mehri Dehnavi |
ParSy: inspection and transformation of sparse matrix computations for parallelism Details |
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Associative instruction reordering to alleviate register pressure Prashant Singh Rawat, Aravind Sukumaran-Rajam, Atanas Rountev, Fabrice Rastello, Louis-Noël Pouchet, P. Sadayappan |
Associative instruction reordering to alleviate register pressure Details |
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Light-weight protocols for wire-speed ordering Hans Eberle, Larry Dennison |
Light-weight protocols for wire-speed ordering Details |
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Stacker: an autonomic data movement engine for extreme-scale data staging-based in-situ workflows Pradeep Subedi, Philip E. Davis, Shaohua Duan, Scott Klasky, Hemanth Kolla, Manish Parashar |
Stacker: an autonomic data movement engine for extreme-scale data staging-based in-situ workflows Details |
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The design, deployment, and evaluation of the CORAL pre-exascale systems Sudharshan S. Vazhkudai, Bronis R. de Supinski, Arthur S. Bland, Al Geist, James C. Sexton, Jim Kahle, Christopher Zimmer, Scott Atchley, Sarp Oral, Don E. Maxwell, Verónica G. Vergara Larrea, Adam Bertsch, Robin Goldstone, Wayne Joubert, Chris Chambreau, David Appelhans, Robert Blackmore, Ben Casses, George Chochia, Gene Davison, Matthew A. Ezell, Tom Gooding, Elsa Gonsiorowski, Leopold Grinberg, Bill Hanson, Bill Hartner, Ian Karlin, Matthew L. Leininger, Dustin Leverman, Chris Marroquin, Adam Moody, Martin Ohmacht, Ramesh Pankajakshan, Fernando Pizzano, James H. Rogers, Bryan S. Rosenburg, Drew Schmidt, Mallikarjun Shankar, Feiyi Wang, Py Watson, Bob Walkup, Lance D. Weems, Junqi Yin |
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HPL and DGEMM performance variability on the Xeon Platinum 8160 processor John D. McCalpin |
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Dynamic tracing: memoization of task graphs for dynamic task-based runtimes Wonchan Lee, Elliott Slaughter, Michael Bauer, Sean Treichler, Todd Warszawski, Michael Garland, Alex Aiken |
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Lessons learned from memory errors observed over the lifetime of Cielo Scott Levy, Kurt B. Ferreira, Nathan DeBardeleben, Taniya Siddiqua, Vilas Sridharan, Elisabeth Baseman |
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Runtime data management on non-volatile memory-based heterogeneous memory for task-parallel programs Kai Wu, Jie Ren, Dong Li |
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