PFI:AIR - TT: Memory Processing Unit: A Low Power Processor for Analytics Applications

University Of Wisconsin-Madison, Madison WI

Investigators

Abstract

This PFI: AIR Technology Translation project focuses on translating 3D chip-stacking technology to develop a new microprocessor architecture called Memory Processing Unit (MPU). The new architecture offers the promise of faster, more energy efficient calculations than current solutions. This is important because there is a large body of applications such as deep-learning, big-data analytics, and data science that all require significant processing capability. While capability requirements continue to increase to meet the needs of these new applications, the rate of improvement of power efficiency of the microprocessors is decreasing (in other words, the trends predicted by Moore's Law are beginning to slow). This project will result in a prototype chip-design of the MPU with complete software API (Application Programming Interface) for end-to-end application demonstrations based on real-time speech recognition and big-data analytics for Internet search capabilities. The MPU includes the following unique features: an energy-efficient simple core implementation (including exploration of mechanisms for pipeline organization, virtual-memory, and coherence), an implementation that connects 128 such cores together, cores connected through 3D links to memory, and end-to-end software implementation. Compared to state-of-art server chips in the market, the MPU architecture provides two-fold to 12-fold calculation speedup while reducing energy consumption by 10-fold. This project addresses the following two technology gaps as it translates from research discovery toward commercial application: a) the difficulty of developing end-to end software on this new highly concurrent architecture and the determination of the mechanisms required, and b) Extensive exploration of various application domains (initially demonstrating speech recognition and internet search capabilities) to determine quantitatively the benefits of this architecture over the state-of-the-art. Personnel involved in this project, including graduate students and undergraduates, will receive innovation and entrepreneurship experiences through the technology commercialization activities, customer interviews, and business development. In addition the team will work with entrepreneurship programs like D2P at UW-Madison.