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ORCIDCheng Li 0014
Person information
- affiliation: University of Illinois Urbana-Champaign, IL, USA
Other persons with the same name
- Cheng Li — disambiguation page
- Cheng Li 0001
![[0000-0001-7064-6120]](https://dblp.dagstuhl.de/img/orcid-mark.12x12.png "0000-0001-7064-6120")
— University of Science and Technology of China (USTC), China (and 1 more) - Cheng Li 0002 — Hong Kong University of Science and Technology, Department of Electronic and Computer Engineering, Clear Water Bay, Hong Kong
- Cheng Li 0003 — Deakin University, Center for Pattern Recognition and Data Analytics (PRaDA), Geelong, Australia
- Cheng Li 0004 — Shanghai Jiao Tong University, Department of Electronic Engineering, Institute of Wireless Communications Technology, China
- Cheng Li 0005 — Memorial University of Newfoundland, Department of Electrical and Computer Engineering, St. John's, NL, Canada
- Cheng Li 0006 — College of William and Mary, Department of Computer Science, Williamsburg, VA, USA
- Cheng Li 0007 — Beihang University, School of Instrumentation Science and Opto-electronics Engineering, Beijing, China
- Cheng Li 0008 — Chinese Academy of Sciences, Shenzhen Institutes of Advanced Technology, Paul C. Lauterbur Research Center for Biomedical Imaging, China
- Cheng Li 0009 — SenseTime Research, Beijing, China (and 1 more)
- Cheng Li 0010 — University of California, Davis, CA, USA (and 1 more)
- Cheng Li 0011 — University of Rochester, Department of Electrical and Computer Engineering, NY, USA (and 1 more)
- Cheng Li 0012 — Google, Mountain View, CA, USA (and 1 more)
- Cheng Li 0013 — University of Kent, UK
- Cheng Li 0015 — Harbin Institute of Technology, Department of Control Science and Engineering, China (and 1 more)
- Cheng Li 0016 — Peking University, Center For Biolnformatics, Beijing, China (and 3 more)
- Cheng Li 0017 — Xidian University, Institute of Intelligent Control and Image Engineering, Xi'an, China
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Books and Theses
- 2020
[b1]Cheng Li:
Performance benchmarking, analysis, and optimization of deep learning inference. University of Illinois Urbana-Champaign, USA, 2020
Conference and Workshop Papers
- 2020
- [c11]Cheng Li, Abdul Dakkak, Jinjun Xiong, Wen-Mei W. Hwu:
The Design and Implementation of a Scalable Deep Learning Benchmarking Platform. CLOUD 2020: 414-425 - [c10]Cheng Li, Abdul Dakkak, Jinjun Xiong, Wei Wei, Lingjie Xu, Wen-Mei Hwu:
XSP: Across-Stack Profiling and Analysis of Machine Learning Models on GPUs. IPDPS 2020: 326-327 - [c9]Cheng Li, Abdul Dakkak, Jinjun Xiong, Wen-Mei Hwu:
Benanza: Automatic μBenchmark Generation to Compute "Lower-bound" Latency and Inform Optimizations of Deep Learning Models on GPUs. IPDPS 2020: 440-450 - [c8]Abdul Dakkak, Cheng Li, Jinjun Xiong, Wen-mei W. Hwu:
DLSpec: A Deep Learning Task Exchange Specification. OpML 2020 - [c7]Cheng Li, Abdul Dakkak, Jinjun Xiong, Wen-Mei Hwu:
DLBricks: Composable Benchmark Generation to Reduce Deep Learning Benchmarking Effort on CPUs. ICPE 2020: 202-209 - 2019
- [c6]Abdul Dakkak, Cheng Li, Simon Garcia De Gonzalo, Jinjun Xiong, Wen-Mei Hwu:
TrIMS: Transparent and Isolated Model Sharing for Low Latency Deep Learning Inference in Function-as-a-Service. CLOUD 2019: 372-382 - [c5]Abdul Dakkak, Cheng Li, Jinjun Xiong, Isaac Gelado, Wen-Mei W. Hwu:
Accelerating reduction and scan using tensor core units. ICS 2019: 46-57 - [c4]Cheng Li, Abdul Dakkak, Jinjun Xiong, Wen-Mei Hwu:
MLModelScope: Evaluate and Introspect Cognitive Pipelines. SERVICES 2019: 335-338 - [c3]Carl Pearson, Abdul Dakkak, Sarah Hashash, Cheng Li, I-Hsin Chung, Jinjun Xiong, Wen-Mei Hwu:
Evaluating Characteristics of CUDA Communication Primitives on High-Bandwidth Interconnects. ICPE 2019: 209-218 - 2017
- [c2]Abdul Dakkak, Carl Pearson, Cheng Li, Wen-mei W. Hwu:
RAI: A Scalable Project Submission System for Parallel Programming Courses. IPDPS Workshops 2017: 315-322 - 2016
- [c1]Izzat El Hajj, Juan Gómez-Luna, Cheng Li, Li-Wen Chang, Dejan S. Milojicic, Wen-mei W. Hwu:
KLAP: Kernel launch aggregation and promotion for optimizing dynamic parallelism. MICRO 2016: 13:1-13:12
Informal and Other Publications
- 2020
- [i12]Abdul Dakkak, Cheng Li, Jinjun Xiong, Wen-Mei Hwu:
MLModelScope: A Distributed Platform for Model Evaluation and Benchmarking at Scale. CoRR abs/2002.08295 (2020) - [i11]Abdul Dakkak, Cheng Li, Jinjun Xiong, Wen-Mei Hwu:
DLSpec: A Deep Learning Task Exchange Specification. CoRR abs/2002.11262 (2020) - 2019
- [i10]Cheng Li, Abdul Dakkak, Jinjun Xiong, Wen-Mei Hwu:
Challenges and Pitfalls of Reproducing Machine Learning Artifacts. CoRR abs/1904.12437 (2019) - [i9]Cheng Li, Abdul Dakkak, Jinjun Xiong, Wei Wei, Lingjie Xu, Wen-Mei Hwu:
Across-Stack Profiling and Characterization of Machine Learning Models on GPUs. CoRR abs/1908.06869 (2019) - [i8]Wei Zhang, Wei Wei, Lingjie Xu, Lingling Jin, Cheng Li:
AI Matrix: A Deep Learning Benchmark for Alibaba Data Centers. CoRR abs/1909.10562 (2019) - [i7]Cheng Li, Abdul Dakkak, Jinjun Xiong, Wen-Mei Hwu:
Benanza: Automatic μBenchmark Generation to Compute "Lower-bound" Latency and Inform Optimizations of Deep Learning Models on GPUs. CoRR abs/1911.06922 (2019) - [i6]Cheng Li, Abdul Dakkak, Jinjun Xiong, Wen-Mei W. Hwu:
DLBricks: Composable Benchmark Generation to Reduce Deep Learning Benchmarking Effort on CPUs. CoRR abs/1911.07967 (2019) - [i5]Cheng Li, Abdul Dakkak, Jinjun Xiong, Wen-Mei W. Hwu:
The Design and Implementation of a Scalable DL Benchmarking Platform. CoRR abs/1911.08031 (2019) - 2018
- [i4]Carl Pearson, Abdul Dakkak, Cheng Li, Sarah Hashash, Jinjun Xiong, Wen-Mei W. Hwu:
SCOPE: C3SR Systems Characterization and Benchmarking Framework. CoRR abs/1809.08311 (2018) - [i3]Abdul Dakkak, Cheng Li, Simon Garcia De Gonzalo, Jinjun Xiong, Wen-Mei W. Hwu:
TrIMS: Transparent and Isolated Model Sharing for Low Latency Deep LearningInference in Function as a Service Environments. CoRR abs/1811.09732 (2018) - [i2]Abdul Dakkak, Cheng Li, Isaac Gelado, Jinjun Xiong, Wen-Mei W. Hwu:
Accelerating Reduction and Scan Using Tensor Core Units. CoRR abs/1811.09736 (2018) - [i1]Abdul Dakkak, Cheng Li, Abhishek Srivastava, Jinjun Xiong, Wen-Mei W. Hwu:
MLModelScope: Evaluate and Measure ML Models within AI Pipelines. CoRR abs/1811.09737 (2018)
Coauthor Index
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