Parallel computation with molecular-motor-propelled agents in nanofabricated networks
Parallel computation with molecular-motor-propelled agents in nanofabricated networks
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DOI：
10.1073/pnas.1510825113
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发表时间：
2016-03-08
影响因子：
11.1
通讯作者：
Nicolau, Dan V.
中科院分区：
文献类型：
--
作者：
Nicolau, Dan V., Jr.;Lard, Mercy;Nicolau, Dan V.
许多重要的数学问题，包括非确定性多项式时间（NP）完全问题的组合性质，对传统的顺序操作的电子计算机可以解决的问题的大小施加了严格的限制。在过去，人们在构思并行计算方法方面做出了巨大的努力，例如：DNA计算，量子计算和基于微流体的计算。然而，到目前为止，这些方法还没有被证明从制造和操作的角度来看是可扩展的和实用的。在这里，我们报告的基础上，一个给定的组合问题被编码成一个图形化的，模块化的网络，嵌入在一个纳米制造的平面设备的另一种并行计算系统。使用大量独立的、分子马达驱动的试剂以并行方式探索网络，然后解决数学问题。这种方法使用的能量比传统计算机少几个数量级，从而解决了与功耗和散热相关的问题。我们提供了一个概念验证演示这样一个设备，通过解决，在一个并行的方式，小实例{2，5，9}的子集和问题，这是一个基准NP完全问题。最后，我们讨论了必要的技术进步，使我们的系统可扩展性与目前可用的技术。
The combinatorial nature of many important mathematical problems, including nondeterministic-polynomial-time (NP)-complete problems, places a severe limitation on the problem size that can be solved with conventional, sequentially operating electronic computers. There have been significant efforts in conceiving parallel-computation approaches in the past, for example: DNA computation, quantum computation, and microfluidics-based computation. However, these approaches have not proven, so far, to be scalable and practical from a fabrication and operational perspective. Here, we report the foundations of an alternative parallel-computation system in which a given combinatorial problem is encoded into a graphical, modular network that is embedded in a nanofabricated planar device. Exploring the network in a parallel fashion using a large number of independent, molecular-motor-propelled agents then solves the mathematical problem. This approach uses orders of magnitude less energy than conventional computers, thus addressing issues related to power consumption and heat dissipation. We provide a proof-of-concept demonstration of such a device by solving, in a parallel fashion, the small instance {2, 5, 9} of the subset sum problem, which is a benchmark NP-complete problem. Finally, we discuss the technical advances necessary to make our system scalable with presently available technology.