Evaluation of the Medium-sized Neural Network using Approximative Computations on Zynq FPGA
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F23%3A00366854" target="_blank" >RIV/68407700:21240/23:00366854 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1109/MECO58584.2023.10155065" target="_blank" >https://doi.org/10.1109/MECO58584.2023.10155065</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/MECO58584.2023.10155065" target="_blank" >10.1109/MECO58584.2023.10155065</a>
Alternative languages
Result language
angličtina
Original language name
Evaluation of the Medium-sized Neural Network using Approximative Computations on Zynq FPGA
Original language description
Integrating artificial intelligence technologies into embedded systems requires efficient implementation of neural networks in hardware. The paper presents a Zynq 7020 FPGA implementation and evaluation of a middle-sized dense neural network based on approximate computation by linearly approximated functions. Three famous benchmarks were used for classification accuracy evaluation and hardware testing. We use our highly pipelined neural hardware architecture that takes weights from block RAMs to save logic resources and enables their update from the processing system. The architecture reaches excellent design scalability, allowing us to estimate the number of neurons implemented in programmable logic based on single-neuron resources. We reached nearly full chip utilization while preserving the high clock frequency for the FPGA used.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20206 - Computer hardware and architecture
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of 2023 12th Mediterranean Conference on Embedded Computing (MECO)
ISBN
979-8-3503-2291-0
ISSN
2637-9511
e-ISSN
2637-9511
Number of pages
4
Pages from-to
1-4
Publisher name
IEEE
Place of publication
Piscataway
Event location
Budva
Event date
Jun 6, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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