Targeting DNN Inference Via Efficient Utilization of Heterogeneous Precision DNN Accelerators

Author:

Spantidi Ourania1ORCID,Zervakis Georgios2ORCID,Alsalamin Sami3ORCID,Roman-Ballesteros Isai4ORCID,Henkel Jörg2ORCID,Amrouch Hussam2ORCID,Anagnostopoulos Iraklis1ORCID

Affiliation:

1. School of Electrical, Computer and Biomedical Engineering, Southern Illinois University, Carbondale, IL, USA

2. Chair for Embedded System (CES), Department of Computer Science, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany

3. Department of Electrical Engineering, Palestine Polytechnic University, Hebron, Palestine

4. Chair for Semiconductor Test and Reliability (STAR), in the Computer Science, Electrical Engineering Faculty, University of Stuttgart, Stuttgart, Germany

Funder

Deutsche Forschungsgemeinschaft

National Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Human-Computer Interaction,Information Systems,Computer Science (miscellaneous)

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. OmniBoost: Boosting Throughput of Heterogeneous Embedded Devices under Multi-DNN Workload;2023 60th ACM/IEEE Design Automation Conference (DAC);2023-07-09

2. The Perfect Match: Selecting Approximate Multipliers for Energy-Efficient Neural Network Inference;2023 IEEE 24th International Conference on High Performance Switching and Routing (HPSR);2023-06-05

3. Dynamic Image Difficulty-Aware DNN Pruning;Micromachines;2023-04-23

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