Traversa F L, Bonani F, Pershin Y V, Di Ventra M
Department of Electronic Engineering, Universitat Autònoma de Barcelona, Spain. Department of Physics, University of California, San Diego, La Jolla, California 92093-0319, USA.
Nanotechnology. 2014 Jul 18;25(28):285201. doi: 10.1088/0957-4484/25/28/285201. Epub 2014 Jun 27.
The present von Neumann computing paradigm involves a significant amount of information transfer between a central processing unit and memory, with concomitant limitations in the actual execution speed. However, it has been recently argued that a different form of computation, dubbed memcomputing (Di Ventra and Pershin 2013 Nat. Phys. 9 200-2) and inspired by the operation of our brain, can resolve the intrinsic limitations of present day architectures by allowing for computing and storing of information on the same physical platform. Here we show a simple and practical realization of memcomputing that utilizes easy-to-build memcapacitive systems. We name this architecture dynamic computing random access memory (DCRAM). We show that DCRAM provides massively-parallel and polymorphic digital logic, namely it allows for different logic operations with the same architecture, by varying only the control signals. In addition, by taking into account realistic parameters, its energy expenditures can be as low as a few fJ per operation. DCRAM is fully compatible with CMOS technology, can be realized with current fabrication facilities, and therefore can really serve as an alternative to the present computing technology.
当前的冯·诺依曼计算范式涉及中央处理器与内存之间大量的信息传输,这同时也限制了实际的执行速度。然而,最近有人提出,一种受我们大脑运作启发的不同形式的计算方式——被称为忆阻计算(迪·文特拉和佩尔申,《自然·物理学》,2013年,第9卷,第200 - 2页),可以通过在同一物理平台上进行信息计算和存储,来解决当今架构的固有局限性。在此,我们展示了一种利用易于构建的忆容系统实现忆阻计算的简单且实用的方法。我们将这种架构命名为动态计算随机存取存储器(DCRAM)。我们表明,DCRAM提供大规模并行和多态数字逻辑,也就是说,通过仅改变控制信号,它可以在同一架构下实现不同的逻辑操作。此外,考虑到实际参数,其每次操作的能量消耗可低至几飞焦。DCRAM与CMOS技术完全兼容,可通过现有的制造设备实现,因此确实可以成为当前计算技术的替代方案。