TY - GEN
T1 - Embedding binary perceptrons in FPGA to improve area, power and performance
AU - Wagle, Ankit
AU - Azari, Elham
AU - Vrudhula, Sarma
N1 - Funding Information:
We gratefully acknowledge the National Science Foundation for supporting this work under NSF PFI award no. #1701241.
Funding Information:
VIII. ACKNOWLEDGMENT We gratefully acknowledge the National Science Foundation for supporting this work under NSF PFI award no. #1701241.
Publisher Copyright:
© 2019 IEEE.
PY - 2019/11
Y1 - 2019/11
N2 - For the flexibility of implementing any given Boolean function(s), the FPGA uses re-configurable building blocks called LUTs. The price for this reconfigurability is a large number of registers and multiplexers required to construct the FPGA. While researchers have been working on complex LUT structures to reduce the area and power for several years, most of these implementations come at the cost of performance penalty. This paper demonstrates simultaneous improvement in area, power, and performance in an FPGA by using special logic cells called Threshold Logic Cells (TLCs) (also known as binary perceptrons). The TLCs are capable of implementing a complex threshold function, which if implemented using conventional gates would require several levels of logic gates. The TLCs only require 7 SRAM cells and are significantly faster than the conventional LUTs. The implementation of the proposed FPGA architecture has been done using 28nm FDSOI standard cells and has been evaluated using ISCAS-85, ISCAS-89, and a few large industrial designs. Experiments demonstrate that the proposed architecture can be used to get an average reduction of 18.1% in configuration registers, 18.1% reduction in multiplexer count, 12.3% in Basic Logic Element (BLE) area, 16.3% in BLE power, 5.9% improvement in operating frequency, with a slight reduction in track count, routing area and routing power. The improvements are also demonstrated on the physically designed version of the architecture.
AB - For the flexibility of implementing any given Boolean function(s), the FPGA uses re-configurable building blocks called LUTs. The price for this reconfigurability is a large number of registers and multiplexers required to construct the FPGA. While researchers have been working on complex LUT structures to reduce the area and power for several years, most of these implementations come at the cost of performance penalty. This paper demonstrates simultaneous improvement in area, power, and performance in an FPGA by using special logic cells called Threshold Logic Cells (TLCs) (also known as binary perceptrons). The TLCs are capable of implementing a complex threshold function, which if implemented using conventional gates would require several levels of logic gates. The TLCs only require 7 SRAM cells and are significantly faster than the conventional LUTs. The implementation of the proposed FPGA architecture has been done using 28nm FDSOI standard cells and has been evaluated using ISCAS-85, ISCAS-89, and a few large industrial designs. Experiments demonstrate that the proposed architecture can be used to get an average reduction of 18.1% in configuration registers, 18.1% reduction in multiplexer count, 12.3% in Basic Logic Element (BLE) area, 16.3% in BLE power, 5.9% improvement in operating frequency, with a slight reduction in track count, routing area and routing power. The improvements are also demonstrated on the physically designed version of the architecture.
KW - 28nm
KW - Digital Perceptron
KW - FDSOI
KW - FPGA
KW - High Performance
KW - Low Area
KW - Low Power
KW - PNAND
KW - Reconfigurable
KW - Threshold Logic
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U2 - 10.1109/ICCAD45719.2019.8942071
DO - 10.1109/ICCAD45719.2019.8942071
M3 - Conference contribution
AN - SCOPUS:85077792488
T3 - IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD
BT - 2019 IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2019 - Digest of Technical Papers
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 38th IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2019
Y2 - 4 November 2019 through 7 November 2019
ER -