COLUMNUS-an architecture for multi-spin-coding algorithms

M. Neschen
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引用次数: 1

Abstract

In order to improve performance when large systems of simple discrete variables are simulated on general-purpose-computers, multi-spin-coding algorithms have been developed. In this paper, a new architecture is proposed which exploits that kind of SIMD parallelism to a high degree using a large array of cheap memory chips which is directly connected to an army of bit-sequential processors. As each processor can perform different operations simultaneously on the incoming bits, an SIMD*MISD architecture for bit operations results. Many applications including lattice-oriented spin simulations and attractor neural network are presented and discussed for efficiency on this structure. As neural network simulations can be largely accelerated by restricting operations to flipped spins, special hardware is suggested which allows the generation of their indices at a maximum rate.<>
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column_多旋转编码算法的架构
为了提高在通用计算机上模拟由简单离散变量组成的大型系统时的性能,多旋编码算法得到了发展。本文提出了一种新的架构,利用大量廉价的存储芯片阵列直接连接到大量的位顺序处理器,从而高度利用了SIMD的并行性。由于每个处理器可以同时对输入的位执行不同的操作,因此产生了位操作的SIMD*MISD体系结构。为了提高这种结构的效率,提出并讨论了许多应用,包括面向晶格的自旋模拟和吸引子神经网络。由于神经网络模拟可以通过将操作限制在翻转自旋上而大大加速,因此建议使用特殊的硬件以最大速率生成它们的指标。
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