TY - GEN
T1 - FPGA Based High-Throughput Real-Time Feature Extraction for Modulation Classification
AU - Mack, Joshua
AU - Akoglu, Ali
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/5
Y1 - 2020/5
N2 - The spectral correlation density (SCD) function is a feature extraction method used in signal classification systems. Due to its computational complexity, SCD has not been a desirable method for systems under power and real-time constraints. In this study, we present results for a hardware implementation of key kernels of the SCD function on a Field Programmable Gate Array (FPGA). By analyzing profiling results for a state of the art GPU implementation, we developed a preliminary architecture that is able to accelerate the most computationally demanding aspects of the SCD algorithm. We find that this FPGA architecture is able to achieve a 2.03X speedup relative to state of the art GPU-based SCD implementations by coupling SCD's large-scale data-parallel nature with an architecture well suited for fine-grained control flow and data access patterns.
AB - The spectral correlation density (SCD) function is a feature extraction method used in signal classification systems. Due to its computational complexity, SCD has not been a desirable method for systems under power and real-time constraints. In this study, we present results for a hardware implementation of key kernels of the SCD function on a Field Programmable Gate Array (FPGA). By analyzing profiling results for a state of the art GPU implementation, we developed a preliminary architecture that is able to accelerate the most computationally demanding aspects of the SCD algorithm. We find that this FPGA architecture is able to achieve a 2.03X speedup relative to state of the art GPU-based SCD implementations by coupling SCD's large-scale data-parallel nature with an architecture well suited for fine-grained control flow and data access patterns.
UR - http://www.scopus.com/inward/record.url?scp=85087335942&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85087335942&partnerID=8YFLogxK
U2 - 10.1109/FCCM48280.2020.00073
DO - 10.1109/FCCM48280.2020.00073
M3 - Conference contribution
AN - SCOPUS:85087335942
T3 - Proceedings - 28th IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2020
SP - 240
BT - Proceedings - 28th IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 28th Annual IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2020
Y2 - 3 May 2020 through 6 May 2020
ER -