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New computing architecture utilizing the noise of integrated circuit to realize indeterminate computing has been proposed previously to solve combinatorial optimization problems. But the solution accuracy of realizing indeterminate computing with circuit's noise performed significantly worse than that with external random number. Because large scale of time is spent to introduce randomness in reading memory cells by row, which reduces the effective computing time. This paper presents a novel structure to introduce probabilistic behavior with just one read operation. It improves the rate of effective computing time and can get close solution accuracy to the scheme using external random number but with less cost. Introduction Most combinatorial optimization problems belong to NP-hard class problems [1]. Generally, finding the global optimum solution to them in conventional computer needs exponential time. CMOS implementation of Ising computing has been proposed previously to solve this problem with its own convergence property [2]. It maps the problem to the coefficients of Ising model firstly and then activates the ground-state search by interaction between spins. Finally the solution is acquired through observing the ground state [3]. The purpose of Ising computer is to find a spin configuration that minimizes the energy of the system [4], which corresponds to the ground state [5]. But the energy profile of the Ising model has peaks and troughs as shown in Fig. 1. The energy goes down along the energy profile by interaction between spins but will fall into a local optimum and be stuck at these points in many cases [6]. Then the system needs to change to other states randomly to prevent being stuck at local optimum. 425 Advances in Computer Science Research (ACRS), volume 54 International Conference on Computer Networks and Communication Technology (CNCT2016)

A Novel Structure to Realize Memory Cell Fluctuation Under Voltage Control in Ising Chip