This work solves 3SAT, a classical NP-complete problem, on a CMOS-based Ising hardware chip with all-to-all connectivity. The paper addresses practical issues in going from algorithms to hardware. It considers several degrees of freedom in mapping the 3SAT problem to the chip-using multiple Ising formulations for 3SAT; exploring multiple strategies for decomposing large problems into subproblems that can be accommodated on the Ising chip; and executing a sequence of these subproblems on CMOS hardware to obtain the solution to the larger problem. These are evaluated within a software framework, and the results are used to identify the most promising formulations and decomposition techniques. These best approaches are then mapped to the all-to-all hardware, and the performance of 3SAT is evaluated on the chip. Experimental data shows that the deployed decomposition and mapping strategies impact SAT solution quality: without our methods, the CMOS hardware cannot achieve 3SAT solutions on SATLIB benchmarks. Under the assumption of some hardware improvements, our chip-based 3SAT solver demonstrates a remarkable 250 acceleration compared to Tabu search in dwave-hybrid on a CPU.
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http://dx.doi.org/10.1038/s41598-024-60316-y | DOI Listing |
Front Neurosci
December 2024
CIMAINA and Dipartimento di Fisica "A. Pontremoli", Università degli Studi di Milano, Milan, Italy.
The brain's ability to perform efficient and fault-tolerant data processing is strongly related to its peculiar interconnected adaptive architecture, based on redundant neural circuits interacting at different scales. By emulating the brain's processing and learning mechanisms, computing technologies strive to achieve higher levels of energy efficiency and computational performance. Although efforts to address neuromorphic solutions through hardware based on top-down CMOS-based technologies have obtained interesting results in terms of energetic efficiency improvement, the replication of brain's self-assembled and redundant architectures is not considered in the roadmaps of data processing electronics.
View Article and Find Full Text PDFNature
December 2024
Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
The demand for the three-dimensional (3D) integration of electronic components is steadily increasing. Despite substantial processing challenges, the through-silicon-via (TSV) technique emerges as the only viable method for integrating single-crystalline device components in a 3D format. Although monolithic 3D (M3D) integration schemes show promise, the seamless connection of single-crystalline semiconductors without intervening wafers has yet to be demonstrated.
View Article and Find Full Text PDFACS Nano
December 2024
Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, California 90089, United States.
The emergence of reconfigurable field effect transistors has introduced a more efficient method for realizing reconfigurable circuits, significantly lowering hardware overhead and enhancing versatility. However, these devices often suffer from asymmetric transfer curves, impacting logic gate performance and reliability. This work investigates the use of the van der Waals junction field effect transistor (JFET) for reconfigurable circuit applications.
View Article and Find Full Text PDFNanophotonics
July 2024
School of Electronics and Information Engineering, Sichuan University, Chengdu 610065, China.
Sensors (Basel)
November 2024
National Institute of Technology Delhi, Delhi 110036, India.
In this paper, a multichannel FIR filter design based on the Time Division Multiplex (TDM) approach that incorporates one multiply and add unit, regardless of the variable coefficient length and varying channels, by associating the resource sharing doctrine is suggested. A multiplier based on approximate distributed arithmetic (DA) circuits is employed for effective resource optimization. Although no explicit multiplication was conducted in this realization, the radix-8 and radix-4 Booth algorithms are utilized in the DA framework to curtail and optimize the partial products (PPs).
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