Drawing insights from quantum computing, oscillator-based computing leverages continuous-time operation and massive parallelism to accelerate challenging computational tasks. This work advances the field to demonstrat...
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ISBN:
(纸本)9798350388138;9798350388145
Drawing insights from quantum computing, oscillator-based computing leverages continuous-time operation and massive parallelism to accelerate challenging computational tasks. This work advances the field to demonstrate a Combinatorial Optimization Problem (COP) engine for efficient, robust, one-shot oscillator-based soft decoding of LDPC codes for the first time. We present a 28nm CMOS prototype that achieves a Frame, Bit Error Rate (FER, BER) of 1.38 x 10(-5), 1.25 x 10(-6) respectively at 7dB SNR and an energy efficiency of 5.26 pJ/bit, which surpasses the normalized efficiencies of recent state-of-the-art decoders [1][2][3] by 11x, 3x, 1.5x respectively. Tested with more than 100 million frame decodings, the prototype demonstrates consistent performance across a range of SNRs, supply voltages, and temperatures.
Nondeterministic polynomial time hard (NP-hard) combinatorial optimization problems (COPs) are intractable to solve using a traditional computer as the time to find a solution increases very rapidly with the number of...
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Nondeterministic polynomial time hard (NP-hard) combinatorial optimization problems (COPs) are intractable to solve using a traditional computer as the time to find a solution increases very rapidly with the number of variables. An efficient alternative computing method uses coupled spin networks to solve COP. This work presents a first-of-its-kind coupled ring oscillator (ROSC)-based scalable probabilistic Ising computer to solve NP-hard COPs. An integrated coupled oscillator network was designed with 560 ROSCs that mimic a coupled spin network. Each ROSC can be coupled to any of its neighbors using programmable back-to-back (B2B) inverter-based coupling mechanism. The ROSC-based spins and B2B inverter-based coupling were optimized to work under a wide range of system noise as well as voltage and temperature variations. Randomly generated 1000 max-cut problems were mapped and solved in the hardware. The integrated Ising computer produced satisfactory solutions of max-cut problems when compared with commercial software running on a CPU. Experiments show that the integrated CMOS-based Ising computer can find the solution to NP-hard problems with an accuracy of 82%-100%. In addition, the repeated measurements of the same problem showed that the Ising computer can traverse through several local minima to find high-quality solutions under various voltage and temperature variation conditions. The experimental results show that ROSCs are a potential candidate for a dedicated hardware accelerator aiming to solve a wide range of COPs.
NP-hard combinatorial optimization problems (COPs) are very expensive to solve with traditional computers. COPs can be mapped to a coupled spin network where the ground state of the system is the solution. We propose ...
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ISBN:
(纸本)9781728199429
NP-hard combinatorial optimization problems (COPs) are very expensive to solve with traditional computers. COPs can be mapped to a coupled spin network where the ground state of the system is the solution. We propose a scalable truly coupled CMOS oscillator-based integrated system mimicking a spin network to solve COPs in hardware. Our simple latch-based coupling design finds solutions of max-cut problems with 85%-100% accuracy 104-106 times faster than commercial software running on a CPU.
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