Spintronics-based Reconfigurable Ising Model Architecture

被引:0
|
作者
Mondal, Ankit [1 ]
Srivastava, Ankur [1 ]
机构
[1] Univ Maryland, College Pk, MD 20742 USA
基金
美国国家科学基金会;
关键词
Ising Model; NP-hard Problems; Magnetic Tunnel Junctions; Reconfigurable Architectures (FPGA); Simulated Annealing; COMBINATORIAL OPTIMIZATION;
D O I
10.1109/isqed48828.2020.9137043
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The Ising model has been explored as a framework for modeling NP-hard problems, with several diverse systems proposed to solve it. The Magnetic Tunnel Junction (MTJ)-based Magnetic RAM is capable of replacing CMOS in memory chips. In this paper, we propose the use of MTJs for representing the units of an Ising model and leveraging its intrinsic physics for finding the ground state of the system through annealing. We design the structure of a basic MTJ-based Ising cell capable of performing the functions essential to an Ising solver. A technique to use the basic Ising cell for scaling to large problems is described. We then go on to propose Ising-FPGA, a parallel and reconfigurable architecture that can be used to map a large class of NP-hard problems, and show how a standard Place and Route tool can be utilized to program the Ising-FPGA. The effects of this hardware platform on our proposed design are characterized and methods to overcome these effects are prescribed. We discuss how two representative NP-hard problems can be mapped to the Ising model. Simulation results show the effectiveness of MTJs as Ising units by producing solutions close/comparable to the optimum, and demonstrate that our design methodology holds the capability to account for the effects of the hardware.
引用
收藏
页码:134 / 140
页数:7
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