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SC 2019: Denver, CO, USA
- Michela Taufer, Pavan Balaji, Antonio J. Peña:
Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2019, Denver, Colorado, USA, November 17-19, 2019. ACM 2019, ISBN 978-1-4503-6229-0
ACM Gordon Bell finalists
- Alexandros Nikolaos Ziogas
, Tal Ben-Nun, Guillermo Indalecio Fernández, Timo Schneider, Mathieu Luisier
A data-centric approach to extreme-scale ab initio dissipative quantum transport simulations. 1:1-1:13 - Sambit Das
Fast, scalable and accurate finite-element based ab initio calculations using mixed precision computing: 46 PFLOPS simulation of a metallic dislocation system. 2:1-2:11
Technical papers: Better data systems via better data structures
- Jin Zhao, Yu Zhang, Xiaofei Liao, Ligang He, Bingsheng He
GraphM: an efficient storage system for high throughput of concurrent graph processing. 3:1-3:14 - HyeongSik Kim, Abhisha Bhattacharyya, Kemafor Anyanwu
Semantic query transformations for increased parallelization in distributed knowledge graph query processing. 4:1-4:14 - Wei Zhang
MIQS: metadata indexing and querying service for self-describing file formats. 5:1-5:24
Technical papers: Computational fluid dynamics
- Libin Lu, Matthew J. Morse, Abtin Rahimian, Georg Stadler, Denis Zorin:
Scalable simulation of realistic volume fraction red blood cell flows through vascular networks. 6:1-6:30 - Wenqian Dong
Adaptive neural network-based approximation to accelerate eulerian fluid simulation. 7:1-7:22 - Kiran Ravikumar
GPU acceleration of extreme scale pseudo-spectral simulations of turbulence using asynchronism. 8:1-8:22
Technical papers: Machine learning training
- Yang You, Jonathan Hseu, Chris Ying, James Demmel, Kurt Keutzer, Cho-Jui Hsieh:
Large-batch training for LSTM and beyond. 9:1-9:16 - Nikoli Dryden, Naoya Maruyama, Tim Moon, Tom Benson, Marc Snir, Brian Van Essen:
Channel and filter parallelism for large-scale CNN training. 10:1-10:20 - Cédric Renggli, Saleh Ashkboos, Mehdi Aghagolzadeh, Dan Alistarh, Torsten Hoefler:
SparCML: high-performance sparse communication for machine learning. 11:1-11:15
Technical papers: Cloud scheduling
- Xiongchao Tang, Haojie Wang, Xiaosong Ma, Nosayba El-Sayed, Jidong Zhai, Wenguang Chen, Ashraf Aboulnaga
Spread-n-share: improving application performance and cluster throughput with resource-aware job placement. 12:1-12:15 - Heyang Qin, Syed Zawad, Yanqi Zhou, Lei Yang, Dongfang Zhao, Feng Yan:
Swift machine learning model serving scheduling: a region based reinforcement learning approach. 13:1-13:23 - Krishna Giri Narra, Zhifeng Lin, Mehrdad Kiamari, Salman Avestimehr, Murali Annavaram
Slack squeeze coded computing for adaptive straggler mitigation. 14:1-14:16
Technical papers: High radix routing
- Nic McDonald, Mikhail Isaev
Practical and efficient incremental adaptive routing for HyperX networks. 15:1-15:13 - Daniele De Sensi, Salvatore Di Girolamo, Torsten Hoefler:
Mitigating network noise on Dragonfly networks through application-aware routing. 16:1-16:32 - Md. Shafayat Rahman, Saptarshi Bhowmik, Yevgeniy Ryasnianskiy, Xin Yuan, Michael Lang:
Topology-custom UGAL routing on dragonfly. 17:1-17:15
Technical papers: Performance tools
- Muhammad Aditya Sasongko, Milind Chabbi, Palwisha Akhtar, Didem Unat
ComDetective: a lightweight communication detection tool for threads. 18:1-18:21 - Pengfei Su, Shuyin Jiao, Milind Chabbi, Xu Liu:
Pinpointing performance inefficiencies via lightweight variance profiling. 19:1-19:19 - Abhinav Bhatele, Stephanie Brink, Todd Gamblin:
Hatchet: pruning the overgrowth in parallel profiles. 20:1-20:21
Technical papers: Frameworks & tools
- Benjamin Welton, Barton P. Miller:
Diogenes: looking for an honest CPU/GPU performance measurement tool. 21:1-21:20 - Nikhil Hegde, Qifan Chang, Milind Kulkarni:
D2P: from recursive formulations to distributed-memory codes. 22:1-22:22 - Michael Bauer, Michael Garland:
Legate NumPy: accelerated and distributed array computing. 23:1-23:23
Technical papers: Linear algebra algorithms
- Grzegorz Kwasniewski, Marko Kabic, Maciej Besta, Joost VandeVondele, Raffaele Solcà
Red-blue pebbling revisited: near optimal parallel matrix-matrix multiplication. 24:1-24:22 - Zhihao Li
AutoFFT: a template-based FFT codes auto-generation framework for ARM and X86 CPUs. 25:1-25:15 - Mark Gates
SLATE: design of a modern distributed and accelerated linear algebra library. 26:1-26:18
Technical papers: Power and scale
- Neha Gholkar, Frank Mueller, Barry Rountree:
Uncore power scavenger: a runtime for uncore power conservation on HPC systems. 27:1-27:23 - Huazhe Zhang, Henry Hoffmann:
PoDD: power-capping dependent distributed applications. 28:1-28:23 - Atilim Günes Baydin, Lei Shao, Wahid Bhimji
Etalumis: bringing probabilistic programming to scientific simulators at scale. 29:1-29:24
Technical papers: State of the practice
- David Jauk, Dai Yang, Martin Schulz
Predicting faults in high performance computing systems: an in-depth survey of the state-of-the-practice. 30:1-30:13 - Ignacio Laguna, Ryan J. Marshall, Kathryn M. Mohror, Martin Ruefenacht, Anthony Skjellum, Nawrin Sultana:
A large-scale study of MPI usage in open-source HPC applications. 31:1-31:14 - Ian Karlin, Yoonho Park, Bronis R. de Supinski, Peng Wang, Bert Still, David Beckingsale, Robert Blake, Tong Chen, Guojing Cong, Carlos H. A. Costa, Johann Dahm, Giacomo Domeniconi, Thomas Epperly, Aaron Fisher, Sara Kokkila Schumacher
Preparation and optimization of a diverse workload for a large-scale heterogeneous system. 32:1-32:17
Technical papers: Compression
- Xin Liang, Sheng Di, Sihuan Li, Dingwen Tao
Significantly improving lossy compression quality based on an optimized hybrid prediction model. 33:1-33:26 - Madhurima Vardhan, John Gounley
Moment representation in the lattice Boltzmann method on massively parallel hardware. 34:1-34:21 - Maciej Besta, Simon Weber
Slim graph: practical lossy graph compression for approximate graph processing, storage, and analytics. 35:1-35:25
Technical papers: Machine learning optimization
- Sangkug Lym, Esha Choukse, Siavash Zangeneh, Wei Wen, Sujay Sanghavi, Mattan Erez:
PruneTrain: fast neural network training by dynamic sparse model reconfiguration. 36:1-36:13 - Prasanna Balaprakash, Romain Egele
Scalable reinforcement-learning-based neural architecture search for cancer deep learning research. 37:1-37:33 - Ang Li, Tong Geng, Tianqi Wang, Martin C. Herbordt, Shuaiwen Leon Song, Kevin J. Barker
BSTC: a novel binarized-soft-tensor-core design for accelerating bit-based approximated neural nets. 38:1-38:30
Technical papers: Network evaluation
- Christopher Zimmer, Scott Atchley, Ramesh Pankajakshan, Brian E. Smith, Ian Karlin, Matthew L. Leininger, Adam Bertsch, Brian S. Ryujin, Jason Burmark, André Walker-Loud, Michael A. Clark, Olga Pearce:
An evaluation of the CORAL interconnects. 39:1-39:18 - Jens Domke, Satoshi Matsuoka, Ivan R. Ivanov
HyperX topology: first at-scale implementation and comparison to the fat-tree. 40:1-40:23 - George Michelogiannakis
Bandwidth steering in HPC using silicon nanophotonics. 41:1-41:25
Technical papers: Network congestion and offload
- Sudheer Chunduri
GPCNeT: designing a benchmark suite for inducing and measuring contention in HPC networks. 42:1-42:33 - Philip Taffet, John M. Mellor-Crummey
Understanding congestion in high performance interconnection networks using sampling. 43:1-43:24 - Haiyang Shi, Xiaoyi Lu:
TriEC: tripartite graph based erasure coding NIC offload. 44:1-44:34
Technical papers: Partitioning & scheduling
- Wonchan Lee, Manolis Papadakis, Elliott Slaughter, Alex Aiken:
A constraint-based approach to automatic data partitioning for distributed memory execution. 45:1-45:24 - Serif Yesil, Azin Heidarshenas, Adam Morrison, Josep Torrellas:
Understanding priority-based scheduling of graph algorithms on a shared-memory platform. 46:1-46:14 - Shumpei Shiina, Kenjiro Taura
Almost deterministic work stealing. 47:1-47:16
Technical papers: Sparse computations
- Athena Elafrou, Georgios I. Goumas, Nectarios Koziris:
Conflict-free symmetric sparse matrix-vector multiplication on multicore architectures. 48:1-48:15 - Israt Nisa, Jiajia Li
An efficient mixed-mode representation of sparse tensors. 49:1-49:25 - Oguz Selvitopi, Cevdet Aykanat:
Regularizing irregularly sparse point-to-point communications. 50:1-50:14
Technical papers: GPU
- Lingda Li
Compiler assisted hybrid implicit and explicit GPU memory management under unified address space. 51:1-51:16 - Tuowen Zhao
Exploiting reuse and vectorization in blocked stencil computations on CPUs and GPUs. 52:1-52:44 - Peng Chen
A versatile software systolic execution model for GPU memory-bound kernels. 53:1-53:81
Technical papers: Network and memory specialization
- Whit Schonbein, Ryan E. Grant, Matthew G. F. Dosanjh, Dorian C. Arnold:
INCA: in-network compute assistance. 54:1-54:13 - Daichi Fujiki
Near-memory data transformation for efficient sparse matrix multi-vector multiplication. 55:1-55:17 - Salvatore Di Girolamo, Konstantin Taranov, Andreas Kurth
Network-accelerated non-contiguous memory transfers. 56:1-56:14
Technical papers: Software infrastructures for applications
- Francesco Di Natale, Harsh Bhatia, Timothy S. Carpenter, Chris Neale, Sara Kokkila Schumacher
A massively parallel infrastructure for adaptive multiscale simulations: modeling RAS initiation pathway for cancer. 57:1-57:16 - Chao Chen, Greg Eisenhauer, Santosh Pande
CARE: compiler-assisted recovery from soft failures. 58:1-58:23 - Martin Bauer, Johannes Hötzer, Dominik Ernst, Julian Hammer, Marco Seiz
Code generation for massively parallel phase-field simulations. 59:1-59:32
Technical papers: Algorithmic techniques for large-scale applications
- Arnur Nigmetov
Local-global merge tree computation with local exchanges. 60:1-60:13 - Masado Ishii, Milinda Fernando, Kumar Saurabh
Solving PDEs in space-time: 4D tree-based adaptivity, mesh-free and matrix-free approaches. 61:1-61:61 - Gregor Daiß
From piz daint to the stars: simulation of stellar mergers using high-level abstractions. 62:1-62:37
Technical papers: Improved performance through monitoring and fine-tuned orchestration
- Sarp Oral
End-to-end I/O portfolio for the summit supercomputing ecosystem. 63:1-63:14 - Alessio Netti, Micha Müller, Axel Auweter, Carla Guillén, Michael Ott
From facility to application sensor data: modular, continuous and holistic monitoring with DCDB. 64:1-64:27 - Tirthak Patel
Revisiting I/O behavior in large-scale storage systems: the expected and the unexpected. 65:1-65:13
Technical papers: Molecular dynamics
- Tingjian Zhang, Yuxuan Li, Ping Gao, Qi Shao, Mingshan Shao, Meng Zhang, Jinxiao Zhang, Xiaohui Duan, Zhao Liu, Lin Gan, Haohuan Fu, Wei Xue, Weiguo Liu, Guangwen Yang:
SW_GROMACS: accelerate GROMACS on Sunway TaihuLight. 66:1-66:14 - Chen Yang, Tong Geng, Tianqi Wang, Rushi Patel, Qingqing Xiong, Ahmed Sanaullah, Chunshu Wu, Jiayi Sheng, Charles Lin, Vipin Sachdeva
Fully integrated FPGA molecular dynamics simulations. 67:1-67:31 - Kun Li
OpenKMC: a KMC design for hundred-billion-atom simulation using millions of cores on Sunway Taihulight. 68:1-68:16
Technical papers: Resilience and fault injection
- Zitao Chen
BinFI: an efficient fault injector for safety-critical machine learning systems. 69:1-69:23 - Chun-Kai Chang, Wenqi Yin, Mattan Erez:
Assessing the impact of timing errors on HPC applications. 70:1-70:19 - Sihuan Li, Hongbo Li, Xin Liang, Jieyang Chen, Elisabeth Giem, Kaiming Ouyang, Kai Zhao
FT-iSort: efficient fault tolerance for introsort. 71:1-71:17
Technical papers: Graph and tensor computations
- Patrick Flick, Srinivas Aluru:
Distributed enhanced suffix arrays: efficient algorithms for construction and querying. 72:1-72:17 - George M. Slota, Jonathan W. Berry, Simon D. Hammond, Stephen L. Olivier
Scalable generation of graphs for benchmarking HPC community-detection algorithms. 73:1-73:14 - Rui Li
Analytical cache modeling and tilesize optimization for tensor contractions. 74:1-74:13
Technical papers: Improving next-generation performance and resilience
- Jacob Alter, Ji Xue, Alma Dimnaku, Evgenia Smirni:
SSD failures in the field: symptoms, causes, and prediction models. 75:1-75:14 - Michèle Weiland
An early evaluation of Intel's optane DC persistent memory module and its impact on high-performance scientific applications. 76:1-76:19 - Tapasya Patki, Jayaraman J. Thiagarajan, Alexis Ayala, Tanzima Z. Islam
Performance optimality or reproducibility: that is the question. 77:1-77:30
Technical papers: Quantum applications
- Alexandros Nikolaos Ziogas
Optimizing the data movement in quantum transport simulations via data-centric parallel programming. 78:1-78:17 - Weile Jia, Lin-Wang Wang, Lin Lin:
Parallel transport time-dependent density functional theory calculations with hybrid functional on summit. 79:1-79:23 - Xin-Chuan Wu, Sheng Di, Emma Maitreyee Dasgupta, Franck Cappello, Hal Finkel, Yuri Alexeev
Full-state quantum circuit simulation by using data compression. 80:1-80:24
Technical papers: Heterogeneous systems
- Tal Ben-Nun, Johannes de Fine Licht
Stateful dataflow multigraphs: a data-centric model for performance portability on heterogeneous architectures. 81:1-81:14 - Tiziano De Matteis
Streaming message interface: high-performance distributed memory programming on reconfigurable hardware. 82:1-82:33 - Kun Yang, Yi-Fan Chen, Georgios Roumpos, Chris Colby, John R. Anderson:
High performance Monte Carlo simulation of ising model on TPU clusters. 83:1-83:15
Technical papers: Image reconstruction
- Peng Chen
iFDK: a scalable framework for instant high-resolution image reconstruction. 84:1-84:24 - Mert Hidayetoglu
MemXCT: memory-centric X-ray CT reconstruction with massive parallelization. 85:1-85:56 - Xiao Wang
Consensus equilibrium framework for super-resolution and extreme-scale CT reconstruction. 86:1-86:23
Technical papers: The fewer tiers, the fewer tears
- Shaohua Duan, Pradeep Subedi, Philip E. Davis, Manish Parashar:
Addressing data resiliency for staging based scientific workflows. 87:1-87:22 - Yingjin Qian, Xi Li, Shuichi Ihara, Andreas Dilger, Carlos Thomaz, Shilong Wang, Wen Cheng, Chunyan Li, Lingfang Zeng
LPCC: hierarchical persistent client caching for lustre. 88:1-88:14 - Anne Benoit
Replication is more efficient than you think. 89:1-89:14
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