Towards Efficient Reconfiguration through Lightweight Input Inversion for MLC NVFPGAs
Author:
Affiliation:
1. School of Computer Science and Technology, Shandong University,China
Funder
National Key Research and Development Program of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10546498/10546499/10546880.pdf?arnumber=10546880
Reference20 articles.
1. From high-level deep neural models to FPGAs
2. Memory-Efficient Architecture for Accelerating Generative Networks on FPGA
3. DLAU: A Scalable Deep Learning Accelerator Unit on FPGA
4. A reconfigurable fabric for accelerating large-scale datacenter services
5. A survey on security analysis of machine learning-oriented hardware and software intellectual property
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