29.2 Snap-SAT: A One-Shot Energy-Performance-Aware All-Digital Compute-in-Memory Solver for Large-Scale Hard Boolean Satisfiability Problems
Boolean satisfiability (SAT) is a non-deterministic polynomial time (NP)-complete problem with many practical and industrial data-intensive applications [1]. Examples (Fig. 29.2.1) include anti-aircraft mission planning in defense, gene prediction in vaccine development, network routing in the data...
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| Vydané v: | Digest of technical papers - IEEE International Solid-State Circuits Conference s. 420 - 422 |
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| Abstract | Boolean satisfiability (SAT) is a non-deterministic polynomial time (NP)-complete problem with many practical and industrial data-intensive applications [1]. Examples (Fig. 29.2.1) include anti-aircraft mission planning in defense, gene prediction in vaccine development, network routing in the data center, automatic test pattern generation in electronic design automation (EDA), and model checking in software. The objective of a SAT solver is to identify the values of n Boolean variables x_{i} that satisfy all clauses in a conjunctive normal form (CNF) [5]. However, the time required to determine the satisfiability of a SAT problem increases exponentially with respect to the variable size, which is energy and resource-consuming. A prior software SAT solver [3] requires frequent data transfer and memory access due to the CPU computations, solution-search, and repetitive variable updates, increasing the computational latency and energy cost. Another approach to designing a SAT solver is to leverage a continuous-time dynamical system using analog circuitry [5]. However, such dedicated analog arithmetic components incur a large area and energy overhead as they cannot be reused during non-SAT applications. Moreover, the analog SAT computations necessitate frequent SRAM read/write access which increase hardware implementation costs. Therefore, there is a critical need for advancing energy and area-efficient hardware SAT solver designs. |
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| AbstractList | Boolean satisfiability (SAT) is a non-deterministic polynomial time (NP)-complete problem with many practical and industrial data-intensive applications [1]. Examples (Fig. 29.2.1) include anti-aircraft mission planning in defense, gene prediction in vaccine development, network routing in the data center, automatic test pattern generation in electronic design automation (EDA), and model checking in software. The objective of a SAT solver is to identify the values of n Boolean variables x_{i} that satisfy all clauses in a conjunctive normal form (CNF) [5]. However, the time required to determine the satisfiability of a SAT problem increases exponentially with respect to the variable size, which is energy and resource-consuming. A prior software SAT solver [3] requires frequent data transfer and memory access due to the CPU computations, solution-search, and repetitive variable updates, increasing the computational latency and energy cost. Another approach to designing a SAT solver is to leverage a continuous-time dynamical system using analog circuitry [5]. However, such dedicated analog arithmetic components incur a large area and energy overhead as they cannot be reused during non-SAT applications. Moreover, the analog SAT computations necessitate frequent SRAM read/write access which increase hardware implementation costs. Therefore, there is a critical need for advancing energy and area-efficient hardware SAT solver designs. |
| Author | Kulkarni, Jaydeep P. Wang, Yipeng Lanham, S. Andrew Yang, Mengtian Oruganti, Sirish Xie, Shanshan Wang, Meizhi |
| Author_xml | – sequence: 1 givenname: Shanshan surname: Xie fullname: Xie, Shanshan organization: University of Texas,Austin,TX,United States – sequence: 2 givenname: Mengtian surname: Yang fullname: Yang, Mengtian organization: University of Texas,Austin,TX,United States – sequence: 3 givenname: S. Andrew surname: Lanham fullname: Lanham, S. Andrew organization: University of Texas,Austin,TX,United States – sequence: 4 givenname: Yipeng surname: Wang fullname: Wang, Yipeng organization: University of Texas,Austin,TX,United States – sequence: 5 givenname: Meizhi surname: Wang fullname: Wang, Meizhi organization: University of Texas,Austin,TX,United States – sequence: 6 givenname: Sirish surname: Oruganti fullname: Oruganti, Sirish organization: University of Texas,Austin,TX,United States – sequence: 7 givenname: Jaydeep P. surname: Kulkarni fullname: Kulkarni, Jaydeep P. organization: University of Texas,Austin,TX,United States |
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| Snippet | Boolean satisfiability (SAT) is a non-deterministic polynomial time (NP)-complete problem with many practical and industrial data-intensive applications [1].... |
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| Title | 29.2 Snap-SAT: A One-Shot Energy-Performance-Aware All-Digital Compute-in-Memory Solver for Large-Scale Hard Boolean Satisfiability Problems |
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