Toward Human-Scale Brain Computing Using 3D Wafer Scale Integration

ACM JOURNAL ON EMERGING TECHNOLOGIES IN COMPUTING SYSTEMS

Article

Kumar, Arvind¹  Wan, Zhe²  Wilcke, Winfried W.³  Iyer, Subramanian S.² 

[1] IBM Thomas J Watson Res Ctr, POB 218, Yorktown Hts, NY 10598 USA.;Univ Calif Los Angeles, Dept Elect Engn, Henry Samueli Sch Engn & Appl Sci, 420 Westwood Plaza, Los Angeles, CA 90095 USA.;IBM Almaden Res Ctr, 650 Harry Rd, San Jose, CA 95120 USA.

关键词: Neuromorphic computing;    SMALL-WORLD;    NETWORK;    COMMUNICATION;    DESIGN;    MEMORY;   

DOI  :  10.1145/2976742

来源: SCIE

【 摘 要 】

The Von Neumann architecture, defined by strict and hierarchical separation of memory and processor, has been a hallmark of conventional computer design since the 1940s. It is becoming increasingly unsuitable for cognitive applications, which require massive parallel processing of highly interdependent data. Inspired by the brain, we propose a significantly different architecture characterized by a large number of highly interconnected simple processors intertwined with very large amounts of low-latency memory. We contend that this memory-centric architecture can be realized using 3D wafer scale integration for which the technology is nearing readiness, combined with current CMOS device technologies. The natural fault tolerance and lower power requirements of neuromorphic processing make 3D wafer stacking particularly attractive. In order to assess the performance of this architecture, we propose a specific embodiment of a neuronal system using 3D wafer scale integration; formulate a simple model of brain connectivity including short-and long-range connections; and estimate the memory, bandwidth, latency, and power requirements of the system using the connectivity model. We find that 3D wafer scale integration, combined with technologies nearing readiness, offers the potential for scaleup to a primate-scale brain, while further scaleup to a human-scale brain would require significant additional innovations.

【 授权许可】

Free