Stop the war!Остановите войну!
for scientists:
default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDShuaiwen Song
Shuaiwen Leon Song
Person information
- affiliation: University of Sydney, Australia
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2023
[c71]Chengying Huan
, Shuaiwen Leon Song, Santosh Pandey, Hang Liu, Yongchao Liu, Baptiste Lepers, Changhua He, Kang Chen, Jinlei Jiang, Yongwei Wu:
TEA: A General-Purpose Temporal Graph Random Walk Engine. EuroSys 2023: 182-198- [c70]Yu Wen, Chenhao Xie, Shuaiwen Leon Song, Xin Fu:
Post0-VR: Enabling Universal Realistic Rendering for Modern VR via Exploiting Architectural Similarity and Data Sharing. HPCA 2023: 390-402 - [i21]Chengming Zhang, Shaden Smith, Baixi Sun, Jiannan Tian, Jonathan Soifer, Xiaodong Yu, Shuaiwen Leon Song, Yuxiong He, Dingwen Tao:
HEAT: A Highly Efficient and Affordable Training System for Collaborative Filtering Based Recommendation on CPUs. CoRR abs/2304.07334 (2023) - 2022
- [j16]Yiding Liu, Xingyao Zhang, Donglin Zhuang, Xin Fu, Shuaiwen Song:
DynamAP: Architectural Support for Dynamic Graph Traversal on the Automata Processor. ACM Trans. Archit. Code Optim. 19(4): 60:1-60:26 (2022) - [j15]Jidong Zhai, Liyan Zheng, Feng Zhang, Xiongchao Tang, Haojie Wang, Teng Yu, Yuyang Jin, Shuaiwen Leon Song, Wenguang Chen:
Detecting Performance Variance for Parallel Applications Without Source Code. IEEE Trans. Parallel Distributed Syst. 33(10): 4239-4255 (2022) - [c69]Chengying Huan, Shuaiwen Leon Song, Yongchao Liu, Heng Zhang, Hang Liu, Charles He, Kang Chen, Jinlei Jiang, Yongwei Wu:
T-GCN: A Sampling Based Streaming Graph Neural Network System with Hybrid Architecture. PACT 2022: 69-82 - [c68]Zhen Zheng, Xuanda Yang, Pengzhan Zhao, Guoping Long, Kai Zhu, Feiwen Zhu, Wenyi Zhao, Xiaoyong Liu, Jun Yang, Jidong Zhai, Shuaiwen Leon Song, Wei Lin:
AStitch: enabling a new multi-dimensional optimization space for memory-intensive ML training and inference on modern SIMT architectures. ASPLOS 2022: 359-373 - [c67]Chengying Huan, Hang Liu, Mengxing Liu, Yongchao Liu, Changhua He, Kang Chen, Jinlei Jiang, Yongwei Wu, Shuaiwen Leon Song:
TeGraph: A Novel General-Purpose Temporal Graph Computing Engine. ICDE 2022: 578-592 - [c66]Heng Zhang, Lingda Li, Hang Liu, Donglin Zhuang, Rui Liu, Chengying Huan, Shuang Song, Dingwen Tao, Yongchao Liu, Charles He, Yanjun Wu, Shuaiwen Leon Song:
Bring orders into uncertainty: enabling efficient uncertain graph processing via novel path sampling on multi-accelerator systems. ICS 2022: 11:1-11:14 - [c65]Donglin Zhuang, Xingyao Zhang, Shuaiwen Song, Sara Hooker:
Randomness in Neural Network Training: Characterizing the Impact of Tooling. MLSys 2022 - [c64]Liyan Zheng, Jidong Zhai, Xiongchao Tang, Haojie Wang, Teng Yu, Yuyang Jin, Shuaiwen Leon Song, Wenguang Chen:
Vapro: performance variance detection and diagnosis for production-run parallel applications. PPoPP 2022: 150-162 - [c63]Shaoshan Liu, Jianda Wang, Zhendong Wang, Bo Yu, Wei Hu, Yahui Liu, Jie Tang, Shuaiwen Leon Song, Cong Liu, Yang Hu:
Brief Industry Paper: The Necessity of Adaptive Data Fusion in Infrastructure-Augmented Autonomous Driving System. RTAS 2022: 293-296 - [i20]Shaoshan Liu, Jianda Wang, Zhendong Wang, Bo Yu, Wei Hu, Yahui Liu, Jie Tang, Shuaiwen Leon Song, Cong Liu, Yang Hu:
Brief Industry Paper: The Necessity of Adaptive Data Fusion in Infrastructure-Augmented Autonomous Driving System. CoRR abs/2207.00737 (2022) - [i19]Zhendong Wang, Xiaoming Zeng, Shuaiwen Leon Song, Yang Hu:
Towards Efficient Architecture and Algorithms for Sensor Fusion. CoRR abs/2209.06272 (2022) - [i18]Jieyang Chen, Chenhao Xie, Jesun Sahariar Firoz, Jiajia Li, Shuaiwen Leon Song, Kevin J. Barker, Mark Raugas, Ang Li:
MSREP: A Fast yet Light Sparse Matrix Framework for Multi-GPU Systems. CoRR abs/2209.07552 (2022) - 2021
- [j14]Cody Rivera, Jieyang Chen, Nan Xiong, Jing Zhang, Shuaiwen Leon Song, Dingwen Tao:
TSM2X: High-performance tall-and-skinny matrix-matrix multiplication on GPUs. J. Parallel Distributed Comput. 151: 70-85 (2021) - [j13]Sian Jin, Chengming Zhang, Xintong Jiang, Yunhe Feng, Hui Guan, Guanpeng Li, Shuaiwen Song, Dingwen Tao:
COMET: A Novel Memory-Efficient Deep Learning Training Framework by Using Error-Bounded Lossy Compression. Proc. VLDB Endow. 15(4): 886-899 (2021) - [j12]Xingyao Zhang, Xin Fu, Donglin Zhuang, Chenhao Xie, Shuaiwen Leon Song:
Enabling Highly Efficient Capsule Networks Processing Through Software-Hardware Co-Design. IEEE Trans. Computers 70(4): 495-510 (2021) - [c62]Chenhao Xie, Xie Li, Yang Hu, Huwan Peng, Michael B. Taylor, Shuaiwen Leon Song:
Q-VR: system-level design for future mobile collaborative virtual reality. ASPLOS 2021: 587-599 - [c61]Chenhao Xie, Jieyang Chen, Jesun Firoz, Jiajia Li, Shuaiwen Leon Song, Kevin J. Barker, Mark Raugas, Ang Li:
Fast and Scalable Sparse Triangular Solver for Multi-GPU Based HPC Architectures. ICPP 2021: 53:1-53:11 - [c60]Chengming Zhang, Geng Yuan, Wei Niu, Jiannan Tian, Sian Jin, Donglin Zhuang, Zhe Jiang, Yanzhi Wang, Bin Ren, Shuaiwen Leon Song, Dingwen Tao:
ClickTrain: efficient and accurate end-to-end deep learning training via fine-grained architecture-preserving pruning. ICS 2021: 266-278 - [c59]Xingyao Zhang, Haojun Xia, Donglin Zhuang, Hao Sun, Xin Fu, Michael B. Taylor, Shuaiwen Leon Song:
η-LSTM: Co-Designing Highly-Efficient Large LSTM Training via Exploiting Memory-Saving and Architectural Design Opportunities. ISCA 2021: 567-580 - [c58]Qiyu Wan, Haojun Xia, Xingyao Zhang, Lening Wang, Shuaiwen Leon Song, Xin Fu:
Shift-BNN: Highly-Efficient Probabilistic Bayesian Neural Network Training via Memory-Friendly Pattern Retrieving. MICRO 2021: 885-897 - [c57]Heng Zhang, Lingda Li, Donglin Zhuang, Rui Liu, Shuang Song, Dingwen Tao, Yanjun Wu, Shuaiwen Leon Song:
An efficient uncertain graph processing framework for heterogeneous architectures. PPoPP 2021: 477-479 - [c56]Sian Jin, Guanpeng Li, Shuaiwen Leon Song, Dingwen Tao:
A novel memory-efficient deep learning training framework via error-bounded lossy compression. PPoPP 2021: 485-487 - [c55]Anil Gaihre, Da Zheng, Scott Weitze, Lingda Li, Shuaiwen Leon Song, Caiwen Ding, Xiaoye S. Li, Hang Liu:
Dr. Top-k: delegate-centric Top-k on GPUs. SC 2021: 39 - [c54]Kiran Ranganath, Joshua D. Suetterlein, Joseph B. Manzano, Shuaiwen Leon Song, Daniel Wong:
MAPA: multi-accelerator pattern allocation policy for multi-tenant GPU servers. SC 2021: 99 - [c53]Jialiang Tan, Yu Chen, Zhenming Liu, Bin Ren, Shuaiwen Leon Song, Xipeng Shen, Xu Liu:
Toward efficient interactions between Python and native libraries. ESEC/SIGSOFT FSE 2021: 1117-1128 - [i17]Chenhao Xie, Xie Li, Yang Hu, Huwan Peng, Michael B. Taylor, Shuaiwen Leon Song:
Q-VR: System-Level Design for Future Mobile Collaborative Virtual Reality. CoRR abs/2102.13191 (2021) - [i16]Donglin Zhuang, Xingyao Zhang, Shuaiwen Leon Song, Sara Hooker:
Randomness In Neural Network Training: Characterizing The Impact of Tooling. CoRR abs/2106.11872 (2021) - [i15]Jialiang Tan, Yu Chen, Zhenming Liu, Bin Ren, Shuaiwen Leon Song, Xipeng Shen, Xu Liu:
Toward Efficient Interactions between Python and Native Libraries. CoRR abs/2107.00064 (2021) - [i14]Anil Gaihre, Da Zheng, Scott Weitze, Lingda Li, Shuaiwen Leon Song, Caiwen Ding, Xiaoye S. Li, Hang Liu:
Dr. Top-k: Delegate-Centric Top-k on GPUs. CoRR abs/2109.08219 (2021) - [i13]Kiran Ranganath, Joshua D. Suetterlein, Joseph B. Manzano, Shuaiwen Leon Song, Daniel Wong:
MAPA: Multi-Accelerator Pattern Allocation Policy for Multi-Tenant GPU Servers. CoRR abs/2110.03214 (2021) - [i12]Qiyu Wan, Haojun Xia, Xingyao Zhang, Lening Wang, Shuaiwen Leon Song, Xin Fu:
Shift-BNN: Highly-Efficient Probabilistic Bayesian Neural Network Training via Memory-Friendly Pattern Retrieving. CoRR abs/2110.03553 (2021) - [i11]Sian Jin, Chengming Zhang, Xintong Jiang, Yunhe Feng, Hui Guan, Guanpeng Li, Shuaiwen Leon Song, Dingwen Tao:
COMET: A Novel Memory-Efficient Deep Learning Training Framework by Using Error-Bounded Lossy Compression. CoRR abs/2111.09562 (2021) - 2020
- [j11]Jingweijia Tan, Kaige Yan, Shuaiwen Leon Song, Xin Fu:
Energy-Efficient GPU L2 Cache Design Using Instruction-Level Data Locality Similarity. ACM Trans. Design Autom. Electr. Syst. 25(6): 52:1-52:18 (2020) - [j10]Ang Li, Shuaiwen Leon Song, Jieyang Chen, Jiajia Li, Xu Liu, Nathan R. Tallent, Kevin J. Barker:
Evaluating Modern GPU Interconnect: PCIe, NVLink, NV-SLI, NVSwitch and GPUDirect. IEEE Trans. Parallel Distributed Syst. 31(1): 94-110 (2020) - [c52]Xingyao Zhang, Shuaiwen Leon Song, Chenhao Xie, Jing Wang, Weigong Zhang, Xin Fu:
Enabling Highly Efficient Capsule Networks Processing Through A PIM-Based Architecture Design. HPCA 2020: 542-555 - [i10]Chenhao Xie, Xin Fu, Mingsong Chen, Shuaiwen Leon Song:
OO-VR: NUMA Friendly Object-Oriented VR Rendering Framework For Future NUMA-Based Multi-GPU Systems. CoRR abs/2001.03537 (2020) - [i9]Cody Rivera, Jieyang Chen, Nan Xiong, Shuaiwen Leon Song, Dingwen Tao:
ISM2: Optimizing Irregular-Shaped Matrix-Matrix Multiplication on GPUs. CoRR abs/2002.03258 (2020) - [i8]Fangtian Zhong, Xiuzhen Cheng, Dongxiao Yu, Bei Gong, Shuaiwen Song, Jiguo Yu:
MalFox: Camouflaged Adversarial Malware Example Generation Based on C-GANs Against Black-Box Detectors. CoRR abs/2011.01509 (2020) - [i7]Sian Jin, Guanpeng Li, Shuaiwen Leon Song, Dingwen Tao:
A Novel Memory-Efficient Deep Learning Training Framework via Error-Bounded Lossy Compression. CoRR abs/2011.09017 (2020) - [i6]Chengming Zhang, Geng Yuan, Wei Niu, Jiannan Tian, Sian Jin, Donglin Zhuang, Zhe Jiang, Yanzhi Wang, Bin Ren, Shuaiwen Leon Song, Dingwen Tao:
An Efficient End-to-End Deep Learning Training Framework via Fine-Grained Pattern-Based Pruning. CoRR abs/2011.10170 (2020) - [i5]Chenhao Xie, Jieyang Chen, Jesun Sahariar Firoz, Jiajia Li, Shuaiwen Leon Song, Kevin J. Barker, Mark Raugas, Ang Li:
Fast and Scalable Sparse Triangular Solver for Multi-GPU Based HPC Architectures. CoRR abs/2012.06959 (2020)
2010 – 2019
- 2019
- [j9]Kiran Ranganath, AmirAli Abdolrashidi, Shuaiwen Leon Song, Daniel Wong:
Speeding up Collective Communications Through Inter-GPU Re-Routing. IEEE Comput. Archit. Lett. 18(2): 128-131 (2019) - [c51]Tong Geng, Tianqi Wang, Chunshu Wu, Chen Yang, Shuaiwen Leon Song, Ang Li, Martin C. Herbordt:
LP-BNN: Ultra-low-Latency BNN Inference with Layer Parallelism. ASAP 2019: 9-16 - [c50]Jingweijia Tan, Kaige Yan, Shuaiwen Leon Song, Xin Fu:
LoSCache: Leveraging Locality Similarity to Build Energy-Efficient GPU L2 Cache. DATE 2019: 1190-1195 - [c49]Chenhao Xie, Xingyao Zhang, Ang Li, Xin Fu, Shuaiwen Song:
PIM-VR: Erasing Motion Anomalies In Highly-Interactive Virtual Reality World with Customized Memory Cube. HPCA 2019: 609-622 - [c48]Chenhao Xie, Xin Fu, Mingsong Chen, Shuaiwen Leon Song:
OO-VR: NUMA friendly object-oriented VR rendering framework for future NUMA-based multi-GPU systems. ISCA 2019: 53-65 - [c47]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. SC 2019: 38:1-38:30 - [i4]Ang Li, Shuaiwen Leon Song, Jieyang Chen, Jiajia Li, Xu Liu, Nathan R. Tallent, Kevin J. Barker:
Evaluating Modern GPU Interconnect: PCIe, NVLink, NV-SLI, NVSwitch and GPUDirect. CoRR abs/1903.04611 (2019) - [i3]Xingyao Zhang, Shuaiwen Leon Song, Chenhao Xie, Jing Wang, Weigong Zhang, Xin Fu:
Enabling Highly Efficient Capsule Networks Processing Through A PIM-Based Architecture Design. CoRR abs/1911.03451 (2019) - 2018
- [j8]Probir Roy, Shuaiwen Leon Song, Sriram Krishnamoorthy, Abhinav Vishnu, Dipanjan Sengupta, Xu Liu:
NUMA-Caffe: NUMA-Aware Deep Learning Neural Networks. ACM Trans. Archit. Code Optim. 15(2): 24:1-24:26 (2018) - [c46]Probir Roy, Shuaiwen Leon Song, Sriram Krishnamoorthy, Xu Liu:
Lightweight detection of cache conflicts. CGO 2018: 200-213 - [c45]Du Shen, Shuaiwen Leon Song, Ang Li, Xu Liu:
CUDAAdvisor: LLVM-based runtime profiling for modern GPUs. CGO 2018: 214-227 - [c44]Chenhao Xie, Xin Fu, Shuaiwen Song:
Perception-Oriented 3D Rendering Approximation for Modern Graphics Processors. HPCA 2018: 362-374 - [c43]Ang Li, Weifeng Liu, Linnan Wang, Kevin J. Barker, Shuaiwen Leon Song:
Warp-Consolidation: A Novel Execution Model for GPUs. ICS 2018: 53-64 - [c42]Ang Li, Shuaiwen Leon Song, Jieyang Chen, Xu Liu, Nathan R. Tallent, Kevin J. Barker:
Tartan: Evaluating Modern GPU Interconnect via a Multi-GPU Benchmark Suite. IISWC 2018: 191-202 - [c41]Shuaiwen Leon Song, Natalie J. Bates, Ang Li:
Introduction to HPPAC 2018. IPDPS Workshops 2018: 674 - [c40]Linnan Wang, Jinmian Ye, Yiyang Zhao, Wei Wu, Ang Li, Shuaiwen Leon Song, Zenglin Xu, Tim Kraska:
Superneurons: dynamic GPU memory management for training deep neural networks. PPoPP 2018: 41-53 - [i2]Linnan Wang, Jinmian Ye, Yiyang Zhao, Wei Wu, Ang Li, Shuaiwen Leon Song, Zenglin Xu, Tim Kraska:
SuperNeurons: Dynamic GPU Memory Management for Training Deep Neural Networks. CoRR abs/1801.04380 (2018) - 2017
- [c39]Ang Li, Shuaiwen Leon Song, Weifeng Liu, Xu Liu, Akash Kumar, Henk Corporaal:
Locality-Aware CTA Clustering for Modern GPUs. ASPLOS 2017: 297-311 - [c38]Chenhao Xie, Shuaiwen Leon Song, Jing Wang, Weigong Zhang, Xin Fu:
Processing-in-Memory Enabled Graphics Processors for 3D Rendering. HPCA 2017: 637-648 - [c37]Junqiao Qiu, Zhijia Zhao, Bo Wu, Abhinav Vishnu, Shuaiwen Leon Song:
Enabling scalability-sensitive speculative parallelization for FSM computations. ICS 2017: 2:1-2:10 - [c36]Shuaiwen Leon Song, Richard W. Vuduc:
HPPAC Workshop Introduction. IPDPS Workshops 2017: 952 - [c35]Shuaiwen Leon Song, Torsten Hoefler:
IPDRM Workshop Introduction. IPDPS Workshops 2017: 1284 - [c34]Ang Li, Wenfeng Zhao, Shuaiwen Leon Song:
BVF: enabling significant on-chip power savings via bit-value-favor for throughput processors. MICRO 2017: 532-545 - [c33]Ang Li, Weifeng Liu, Mads Ruben Burgdorff Kristensen, Brian Vinter, Hao Wang, Kaixi Hou, Andres Marquez, Shuaiwen Leon Song:
Exploring and analyzing the real impact of modern on-package memory on HPC scientific kernels. SC 2017: 26 - [c32]Ning Zhang, Chuntao Jiang, Xian-He Sun, Shuaiwen Leon Song:
Evaluating GPGPU Memory Performance Through the C-AMAT Model. MCHPC@SC 2017: 35-39 - [c31]Dipanjan Sengupta, Shuaiwen Leon Song:
EvoGraph: On-the-Fly Efficient Mining of Evolving Graphs on GPU. ISC 2017: 97-119 - 2016
- [j7]Li Tan, Zizhong Chen, Shuaiwen Leon Song:
Scalable Energy Efficiency with Resilience for High Performance Computing Systems: A Quantitative Methodology. ACM Trans. Archit. Code Optim. 12(4): 35:1-35:27 (2016) - [c30]Jingweijia Tan, Shuaiwen Leon Song, Kaige Yan, Xin Fu, Andrès Márquez, Darren J. Kerbyson:
Combating the Reliability Challenge of GPU Register File at Low Supply Voltage. PACT 2016: 3-15 - [c29]Ang Li, Shuaiwen Leon Song, Akash Kumar, Eddy Z. Zhang, Daniel G. Chavarría-Miranda, Henk Corporaal:
Critical points based register-concurrency autotuning for GPUs. DATE 2016: 1273-1278 - [c28]Dingwen Tao, Shuaiwen Leon Song, Sriram Krishnamoorthy, Panruo Wu, Xin Liang, Eddy Z. Zhang, Darren J. Kerbyson, Zizhong Chen:
New-Sum: A Novel Online ABFT Scheme For General Iterative Methods. HPDC 2016: 43-55 - [c27]Probir Roy, Xu Liu, Shuaiwen Leon Song:
SMT-Aware Instantaneous Footprint Optimization. HPDC 2016: 267-279 - [c26]Ang Li, Shuaiwen Leon Song, Mark Wijtvliet, Akash Kumar, Henk Corporaal:
SFU-Driven Transparent Approximation Acceleration on GPUs. ICS 2016: 15:1-15:14 - [c25]Lingda Li, Ari B. Hayes, Shuaiwen Leon Song, Eddy Z. Zhang:
Tag-Split Cache for Efficient GPGPU Cache Utilization. ICS 2016: 43:1-43:12 - [c24]Ang Li, Shuaiwen Leon Song, Eric Brugel, Akash Kumar, Daniel G. Chavarría-Miranda, Henk Corporaal:
X: A Comprehensive Analytic Model for Parallel Machines. IPDPS 2016: 242-252 - [c23]Barry Rountree, Shuaiwen Leon Song:
HPPAC Introduction and Committees. IPDPS Workshops 2016: 1089 - [c22]Shuaiwen Leon Song, Todd Gamblin:
IPDRM Introduction and Committees. IPDPS Workshops 2016: 1726 - [c21]Ari B. Hayes, Lingda Li, Daniel G. Chavarría-Miranda, Shuaiwen Leon Song, Eddy Z. Zhang:
Orion: A Framework for GPU Occupancy Tuning. Middleware 2016: 18 - [i1]Lingda Li, Ari B. Hayes, Stephen A. Hackler, Eddy Z. Zhang, Mario Szegedy, Shuaiwen Leon Song:
A Graph-based Model for GPU Caching Problems. CoRR abs/1605.02043 (2016) - 2015
- [j6]Yang You, Haohuan Fu, Shuaiwen Leon Song, Amanda Peters Randles, Darren J. Kerbyson, Andres Marquez, Guangwen Yang, Adolfy Hoisie:
Scaling Support Vector Machines on modern HPC platforms. J. Parallel Distributed Comput. 76: 16-31 (2015) - [c20]Sunil Shrestha, Joseph B. Manzano, Andrès Márquez, Stéphane Zuckerman, Shuaiwen Song, Guang R. Gao:
Gregarious Data Re-structuring in a Many Core Architecture. HPCC/CSS/ICESS 2015: 712-720 - [c19]Chao Li, Shuaiwen Leon Song, Hongwen Dai, Albert Sidelnik, Siva Kumar Sastry Hari, Huiyang Zhou:
Locality-Driven Dynamic GPU Cache Bypassing. ICS 2015: 67-77 - [c18]Dipanjan Sengupta, Kapil Agarwal, Shuaiwen Leon Song, Karsten Schwan:
GraphReduce: Large-Scale Graph Analytics on Accelerator-Based HPC Systems. IPDPS Workshops 2015: 604-609 - [c17]Li Tan, Shuaiwen Leon Song, Panruo Wu, Zizhong Chen, Rong Ge, Darren J. Kerbyson:
Investigating the Interplay between Energy Efficiency and Resilience in High Performance Computing. IPDPS 2015: 786-796 - [c16]Dipanjan Sengupta, Shuaiwen Leon Song, Kapil Agarwal, Karsten Schwan:
GraphReduce: processing large-scale graphs on accelerator-based systems. SC 2015: 28:1-28:12 - 2014
- [j5]Yang You, Haohuan Fu, Shuaiwen Leon Song, Maryam Mehri Dehnavi, Lin Gan, Xiaomeng Huang, Guangwen Yang:
Evaluating multi-core and many-core architectures through accelerating the three-dimensional Lax-Wendroff correction stencil. Int. J. High Perform. Comput. Appl. 28(3): 301-318 (2014) - [j4]Bo Li, Hung-Ching Chang, Shuaiwen Song, Chun-Yi Su, Timmy Meyer, John Mooring, Kirk W. Cameron:
Extending PowerPack for Profiling and Analysis of High-Performance Accelerator-Based Systems. Parallel Process. Lett. 24(4) (2014) - [c15]Andres Marquez, Joseph B. Manzano, Shuaiwen Leon Song, Benoît Meister, Sunil Shrestha, Thomas St. John, Guang R. Gao:
ACDT: Architected Composite Data Types trading-in unfettered data access for improved execution. ICPADS 2014: 289-297 - [c14]Yang You, Shuaiwen Leon Song, Darren J. Kerbyson:
An adaptive cross-architecture combination method for graph traversal. ICS 2014: 169 - [c13]Yang You, Shuaiwen Leon Song, Haohuan Fu, Andres Marquez, Maryam Mehri Dehnavi, Kevin J. Barker, Kirk W. Cameron, Amanda Peters Randles, Guangwen Yang:
MIC-SVM: Designing a Highly Efficient Support Vector Machine for Advanced Modern Multi-core and Many-Core Architectures. IPDPS 2014: 809-818 - [c12]Bo Li, Hung-Ching Chang, Shuaiwen Song, Chun-Yi Su, Timmy Meyer, John Mooring, Kirk W. Cameron:
The Power-Performance Tradeoffs of the Intel Xeon Phi on HPC Applications. IPDPS Workshops 2014: 1448-1456 - 2013
- [j3]Abhinav Vishnu, Shuaiwen Song, Andres Marquez, Kevin J. Barker, Darren J. Kerbyson, Kirk W. Cameron, Pavan Balaji:
Designing energy efficient communication runtime systems: a view from PGAS models. J. Supercomput. 63(3): 691-709 (2013) - [c11]Bo Li, Shuaiwen Leon Song, Ivona Bezáková, Kirk W. Cameron:
EDR: An energy-aware runtime load distribution system for data-intensive applications in the cloud. CLUSTER 2013: 1-8 - [c10]Shuaiwen Song, Chun-Yi Su, Barry Rountree, Kirk W. Cameron:
A Simplified and Accurate Model of Power-Performance Efficiency on Emergent GPU Architectures. IPDPS 2013: 673-686 - [c9]Shuaiwen Leon Song, Kevin J. Barker, Darren J. Kerbyson:
Unified performance and power modeling of scientific workloads. E2SC@SC 2013: 4:1-4:8 - 2012
- [c8]Shuaiwen Song, Kirk W. Cameron:
System-level power-performance efficiency modeling for emergent GPU architectures. PACT 2012: 473-474 - [c7]Bo Li, Shuaiwen Song, Ivona Bezáková, Kirk W. Cameron:
Energy-Aware Replica Selection for Data-Intensive Services in Cloud. MASCOTS 2012: 504-506 - [c6]Shuaiwen Leon Song, Chun-Yi Su, Barry Rountree, Kirk W. Cameron:
Abstract: Three Steps to Model Power-Performance Efficiency for Emergent GPU-Based Parallel Systems. SC Companion 2012: 1344-1345 - [c5]Shuaiwen Leon Song:
Poster: Three Steps to Model Power-Performance Efficiency for Emergent GPU-Based Parallel Systems. SC Companion 2012: 1346 - 2011
- [c4]Shuaiwen Song, Matthew Grove, Kirk W. Cameron:
An ISO-Energy-Efficient Approach to Scalable System Power-Performance Optimization. CLUSTER 2011: 262-271 - [c3]Shuaiwen Song, Chun-Yi Su, Rong Ge, Abhinav Vishnu, Kirk W. Cameron:
Iso-Energy-Efficiency: An Approach to Power-Constrained Parallel Computation. IPDPS 2011: 128-139 - 2010
- [j2]Rong Ge, Xizhou Feng, Shuaiwen Song, Hung-Ching Chang, Dong Li, Kirk W. Cameron:
PowerPack: Energy Profiling and Analysis of High-Performance Systems and Applications. IEEE Trans. Parallel Distributed Syst. 21(5): 658-671 (2010) - [c2]Abhinav Vishnu, Shuaiwen Song, Andres Marquez, Kevin J. Barker, Darren J. Kerbyson, Kirk W. Cameron, Pavan Balaji:
Designing Energy Efficient Communication Runtime Systems for Data Centric Programming Models. GreenCom/CPSCom 2010: 229-236 - [c1]Abhinav Vishnu, Huub J. J. Van Dam, Wibe de Jong, Pavan Balaji, Shuaiwen Song:
Fault-tolerant communication runtime support for data-centric programming models. HiPC 2010: 1-9
2000 – 2009
- 2009
- [j1]Shuaiwen Song, Rong Ge, Xizhou Feng, Kirk W. Cameron:
Energy Profiling and Analysis of the HPC Challenge Benchmarks. Int. J. High Perform. Comput. Appl. 23(3): 265-276 (2009)
Coauthor Index