I-Corps: Power Reduction for AI Computing

I-Corps：降低 AI 计算的功耗

• 批准号: 1940042
• 负责人: Rhonda Shrader
• 金额: $ 5万
• 依托单位: University of California-Berkeley
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-15 至 2020-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1940042&HistoricalAwards=false
• 关键词: Corps; Power; Reduction; AI; Computing

The broader impact/commercial potential of this I-Corps project is to advance artificial intelligence computing for a wide range of applications including in data centers and for unmanned autonomous vehicles. According to Forbes, in 2017 U.S. data centers consumed more than 90 Billion Kilowatt hours of energy. Due to Artificial Intelligence and Internet of Things, the expectation is that data center energy consumption will have grown by 2X by 2023, or 15% year-over-year increase. On the side of power-constrained machines, such as drones and robots, power consumption for computing is severely limited to milli-Watts of power. The impact to these industries, to enable AI inference computation is the power savings of 80X over traditional electronics.This I-Corps project develops ultra-low power reconfigurable nano-switches as memory. Artificial Intelligence inference cpmputing has high energy costs due to the large number of multiply-accumulate (MAC) functions required at each node in the neural network, often millions to hundreds of millions of operations for a single inference calculation. These ultra-low power reconfigurable switches store the AI model weights, and replace dynamic ram (DRAM) memory. Simulated results indicate 80X power reduction for each memory read needed for MAC operation. These switches are compatible with complementary metal-oxide semiconductor (CMOS) technology and can be produced at a minimal cost adder from a standard CMOS process.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.

这个I-Corps项目更广泛的影响/商业潜力是推进人工智能计算的广泛应用，包括数据中心和无人驾驶自动驾驶汽车。根据福布斯的数据，2017年美国数据中心消耗了超过900亿千瓦时的能源。 由于人工智能和物联网的发展，预计到2023年，数据中心的能源消耗将增长2倍，即同比增长15%。 在功率受限的机器方面，例如无人机和机器人，计算的功耗严格限制在毫瓦功率。 对这些行业的影响，使人工智能推理计算是节省80倍的电力比传统的电子产品。这个I-Corps项目开发超低功耗可重构纳米开关作为存储器。 人工智能推理计算由于在神经网络中的每个节点处需要大量的乘-累加（MAC）函数而具有高的能量成本，对于单个推理计算，通常需要数百万到数亿次操作。 这些超低功耗可重构开关存储AI模型权重，并取代动态RAM（DRAM）存储器。模拟结果表明，MAC操作所需的每个存储器读取的功率降低80倍。这些开关与互补金属氧化物半导体（CMOS）技术兼容，并可通过标准CMOS工艺以最低成本生产。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。