Low-Power Manycore Accelerator for Personalized Biomedical Applications
Author:
Affiliation:
1. University of Maryland, Baltimore County, Baltimore, MD, USA
2. George Mason University, Fairfax, VA, USA
Funder
National Science Foundation
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/2902961.2902986
Reference17 articles.
1. A 64-core platform for biomedical signal processing
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1. FPGA Implementation of IoT-Based Health Monitoring System;2021 15th International Conference on Telecommunication Systems, Services, and Applications (TSSA);2021-11-18
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3. Heterogeneous Scheduling of Deep Neural Networks for Low-power Real-time Designs;ACM Journal on Emerging Technologies in Computing Systems;2019-10-31
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