Collaborative Research: FET: Medium: Probabilistic Computing Through Integrated Nano-devices - A Device to Systems Approach

合作研究：FET：中：通过集成纳米设备进行概率计算 - 设备到系统的方法

基本信息

批准号：
2106260
负责人：
Kerem Camsari
金额：
$ 27万
依托单位：
University of California-Santa Barbara
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2021
资助国家：
美国
起止时间：
2021-07-01 至 2024-06-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2106260&HistoricalAwards=false
关键词：
Collaborative Research FET Medium Probabilistic

项目摘要

The world has seen a steady increase in demand for computational power, with no end in sight. Search engines that allow users to find answers to pretty much all of their questions are expected to deliver results in less than a second, while understanding the customer with a high probability based on just a few words of input. This is not the type of computation that is precise and gives the “correct” answer; it instead provides solutions that are more associative, mimicking the human way of addressing problems. In fact, many problems in the real world are probabilistic in nature, and conventional computing schemes are not optimized for these tasks. In 1982 Nobel Prize winner Richard Feynman stated in recognition of this fact: “The way to simulate a probabilistic nature might still be by a computer which itself is probabilistic... So, it becomes what I’ll call a probabilistic computer, in which the output is not a unique function of the input.” To promote the progress of science, this proposal aims to explore, model and build hardware components and circuits that ultimately enable such a probabilistic computer, which will greatly benefit the society as a whole. Moreover, educational tools, new courses and training opportunities both for undergraduate and graduate students are being created that expose them to a device-to-systems research program on probabilistic computing in order to prepare them for the new era of electronics.The project adopts a Device-to-Systems approach that covers experiments from single devices and small circuits all the way up to simulations with thousands of devices. It addresses the question of how to implement probabilistic functionality in hardware from a variety of different angles. The key objective of this proposal is to take the next step in the development of probabilistic computing by experimental demonstrations of integrated probabilistic bits (p-bits) and p-circuits and quantifying advantages of scaled probabilistic computers through key figures-of-merits in system-level applications based on experimental input. This is being achieved by employing unstable magnets in a magnetic tunneling junction (MTJ) configuration as random number generators that become tunable by the use of field-effect transistors in a suitable circuit layout. Initial projections estimate that if integrated MTJs coupled with conventional transistors can be scaled up, one can expect to achieve orders of magnitude improvements compared to what is achievable in conventional semiconductor technology in key figures-of-merits, such as the number of statistically independent samples per second (also referred to as flips per second) that a probabilistic sampler can go through.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

全世界对计算能力的需求稳定增加，没有任何目的。允许用户找到几乎所有问题的答案的搜索引擎预计将在不到一秒钟的时间内提供结果，同时仅基于几个输入单词来理解客户的概率很高。这不是精确的计算类型，并给出“正确”的答案；相反，它提供了更具关联的解决方案，模仿人类解决问题的方式。实际上，现实世界中的许多问题本质上都是概率的，常规计算方案并未针对这些任务进行优化。 1982年，诺贝尔奖获得者理查德·费曼（Richard Feynman）表示：“模拟概率性质的方法可能仍然是概率的计算机……因此，我称之为概率计算机，其中输出不是输入的独特功能。”为了促进科学的进步，该建议旨在探索，建模和建立硬件组件和电路，最终使这种概率计算机能够极大地使整个社会受益。此外，正在为本科和研究生提供教育工具，新课程和培训机会，使它们暴露于概率计算的设备对系统研究计划，以便为电子学时代的新时代做好准备。该项目适应了设备对系统的方法，该项目涵盖了单个设备和小型Circutites和Small Circuits and Small Cigruits and Small Cigruts and Simals insim sims insim sims insim sims nose sims nose simseptices of Simbults insim neims neims neims neims nose devations insims necys expectices oversections insim necyseptices。它解决了如何从各种不同角度实现硬件中概率功能的问题。该提案的关键目的是通过基于实验输入基于实验输入的系统级别应用中的关键合并，通过实验证明进行概率概率位（P-BITS）以及p-circuits和p circutits的实验证明（p-bits）以及量表概率计算机的优势来迈出概率计算的下一步。这是通过在磁性隧道连接（MTJ）配置中作为随机数发生器中使用不稳定的磁铁来实现的，这些发生器可以通过在合适的电路布局中使用现场效应晶体管来调谐。初始项目估计，如果与常规半导体技术相比，与传统的半导体技术相比，可以预期将MTJ与常规晶体管相结合，可以预期取得更大的改善使用基金会的智力优点和更广泛的影响标准，认为通过评估被认为是宝贵的支持。

项目成果

期刊论文数量（5）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

A Full-Stack View of Probabilistic Computing With p-Bits: Devices, Architectures, and Algorithms

DOI：
10.1109/jxcdc.2023.3256981
发表时间：
2023-02
期刊：
IEEE Journal on Exploratory Solid-State Computational Devices and Circuits
影响因子：
2.4
作者：
S. Chowdhury;Andrea Grimaldi;Navid Anjum Aadit;Shaila Niazi;M. Mohseni;S. Kanai;Hideo Ohno;S. F
通讯作者：
S. Chowdhury;Andrea Grimaldi;Navid Anjum Aadit;Shaila Niazi;M. Mohseni;S. Kanai;Hideo Ohno;S. F

Physics-inspired Ising Computing with Ring Oscillator Activated p-bits