Cheng Li

Orcid: 0000-0002-9991-4472

Affiliations:

University of Illinois Urbana-Champaign, IL, USA

According to our database¹, Cheng Li authored at least 20 papers between 2016 and 2020.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

Legend:

Book

In proceedings

Article

PhD thesis

Dataset

Other

Bibliography

2020

Performance benchmarking, analysis, and optimization of deep learning inference

[BibT_eX]

[DOI]

Cheng Li

PhD thesis, 2020

MLModelScope: A Distributed Platform for Model Evaluation and Benchmarking at Scale.

[BibT_eX]

[DOI]

CoRR, 2020

DLBricks: Composable Benchmark Generation to Reduce Deep Learning Benchmarking Effort on CPUs.

[BibT_eX]

[DOI]

Proceedings of the ICPE '20: ACM/SPEC International Conference on Performance Engineering, 2020

DLSpec: A Deep Learning Task Exchange Specification.

[BibT_eX]

[DOI]

Proceedings of the 2020 USENIX Conference on Operational Machine Learning, 2020

Benanza: Automatic μBenchmark Generation to Compute "Lower-bound" Latency and Inform Optimizations of Deep Learning Models on GPUs.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2020

XSP: Across-Stack Profiling and Analysis of Machine Learning Models on GPUs.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2020

The Design and Implementation of a Scalable Deep Learning Benchmarking Platform.

[BibT_eX]

[DOI]

Proceedings of the 13th IEEE International Conference on Cloud Computing, 2020

2019

The Design and Implementation of a Scalable DL Benchmarking Platform.

[BibT_eX]

[DOI]

CoRR, 2019

AI Matrix: A Deep Learning Benchmark for Alibaba Data Centers.

[BibT_eX]

[DOI]

CoRR, 2019

Across-Stack Profiling and Characterization of Machine Learning Models on GPUs.

[BibT_eX]

[DOI]

CoRR, 2019

Challenges and Pitfalls of Reproducing Machine Learning Artifacts.

[BibT_eX]

[DOI]

CoRR, 2019

Evaluating Characteristics of CUDA Communication Primitives on High-Bandwidth Interconnects.

[BibT_eX]

[DOI]

Proceedings of the 2019 ACM/SPEC International Conference on Performance Engineering, 2019

MLModelScope: Evaluate and Introspect Cognitive Pipelines.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE World Congress on Services, 2019

Accelerating reduction and scan using tensor core units.

[BibT_eX]

[DOI]

Proceedings of the ACM International Conference on Supercomputing, 2019

TrIMS: Transparent and Isolated Model Sharing for Low Latency Deep Learning Inference in Function-as-a-Service.

[BibT_eX]

[DOI]

Abdul Dakkak

Cheng Li

Simon Garcia De Gonzalo

Jinjun Xiong

Wen-Mei Hwu

Proceedings of the 12th IEEE International Conference on Cloud Computing, 2019

2018

MLModelScope: Evaluate and Measure ML Models within AI Pipelines.

[BibT_eX]

[DOI]

CoRR, 2018

TrIMS: Transparent and Isolated Model Sharing for Low Latency Deep LearningInference in Function as a Service Environments.

[BibT_eX]

[DOI]

Abdul Dakkak

Cheng Li

Simon Garcia De Gonzalo

Jinjun Xiong

Wen-Mei W. Hwu

CoRR, 2018

SCOPE: C3SR Systems Characterization and Benchmarking Framework.

[BibT_eX]

[DOI]

CoRR, 2018

2017

RAI: A Scalable Project Submission System for Parallel Programming Courses.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Parallel and Distributed Processing Symposium Workshops, 2017

2016

KLAP: Kernel launch aggregation and promotion for optimizing dynamic parallelism.

[BibT_eX]

[DOI]

Proceedings of the 49th Annual IEEE/ACM International Symposium on Microarchitecture, 2016

Cheng Li

Timeline

Legend:

Links

Online presence:

On csauthors.net:

Bibliography

Loading...