TY - GEN
T1 - HW-BCP
T2 - 26th Asia and South Pacific Design Automation Conference, ASP-DAC 2021
AU - Park, Soowang
AU - Nam, Jae Won
AU - Gupta, Sandeep K.
N1 - Publisher Copyright:
© 2021 Association for Computing Machinery.
PY - 2021/1/18
Y1 - 2021/1/18
N2 - Boolean Satisfiability (SAT) has broad usage in Electronic Design Automation (EDA), artificial intelligence (AI), and theoretical studies. Further, as an NP-complete problem, acceleration of SAT will also enable acceleration of a wide range of combinatorial problems. We propose a completely new custom hardware design to accelerate SAT. Starting with the well-known fact that Boolean Constraint Propagation (BCP) takes most of the SAT solving time (80-90%), we focus on accelerating BCP. By profiling a widely-used software SAT solver, MiniSAT v2.2.0 (MiniSAT2) [1], we identify opportunities to accelerate BCP via parallelization and elimination of von Neumann overheads, especially data movement. The proposed hardware for BCP (HW-BCP) achieves these goals via a customized combination of content-addressable memory (CAM) cells, SRAM cells, logic circuitry, and optimized interconnects. In 65nm technology, on the largest SAT instances in the SAT Competition 2017 benchmark suite, our HW-BCP dramatically accelerates BCP (4.5ns per BCP in simulations) and hence provides a 62-185x speedup over optimized software implementation running on general purpose processors. Finally, we extrapolate our HW-BCP design to 7nm technology and estimate area and delay. The analysis shows that in 7nm, in a realistic chip size, HW-BCP would be large enough for the largest SAT instances in the benchmark suite.
AB - Boolean Satisfiability (SAT) has broad usage in Electronic Design Automation (EDA), artificial intelligence (AI), and theoretical studies. Further, as an NP-complete problem, acceleration of SAT will also enable acceleration of a wide range of combinatorial problems. We propose a completely new custom hardware design to accelerate SAT. Starting with the well-known fact that Boolean Constraint Propagation (BCP) takes most of the SAT solving time (80-90%), we focus on accelerating BCP. By profiling a widely-used software SAT solver, MiniSAT v2.2.0 (MiniSAT2) [1], we identify opportunities to accelerate BCP via parallelization and elimination of von Neumann overheads, especially data movement. The proposed hardware for BCP (HW-BCP) achieves these goals via a customized combination of content-addressable memory (CAM) cells, SRAM cells, logic circuitry, and optimized interconnects. In 65nm technology, on the largest SAT instances in the SAT Competition 2017 benchmark suite, our HW-BCP dramatically accelerates BCP (4.5ns per BCP in simulations) and hence provides a 62-185x speedup over optimized software implementation running on general purpose processors. Finally, we extrapolate our HW-BCP design to 7nm technology and estimate area and delay. The analysis shows that in 7nm, in a realistic chip size, HW-BCP would be large enough for the largest SAT instances in the benchmark suite.
KW - BCP
KW - CAM
KW - Custom hardware
KW - SAT
KW - von Neumann machine
UR - http://www.scopus.com/inward/record.url?scp=85100548621&partnerID=8YFLogxK
U2 - 10.1145/3394885.3431413
DO - 10.1145/3394885.3431413
M3 - Conference contribution
AN - SCOPUS:85100548621
T3 - Proceedings of the Asia and South Pacific Design Automation Conference, ASP-DAC
SP - 29
EP - 34
BT - Proceedings of the 26th Asia and South Pacific Design Automation Conference, ASP-DAC 2021
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 18 January 2021 through 21 January 2021
ER -