Emerging Memory Devices for Neuromorphic Computing
University of Massachusetts Amherst
Abstract
Abstract A neuromorphic computing system may be able to learn and perform a task on its own by interacting with its surroundings. Combining such a chip with complementary metal–oxide–semiconductor (CMOS)‐based processors can potentially solve a variety of problems being faced by today's artificial intelligence (AI) systems. Although various architectures purely based on CMOS are designed to maximize the computing efficiency of AI‐based applications, the most fundamental operations including matrix multiplication and convolution heavily rely on the CMOS‐based multiply–accumulate units which are ultimately limited by the von Neumann bottleneck. Fortunately, many emerging memory devices can naturally perform…
Citation impact
- FWCI
- 27.85
- Percentile
- 100%
- References
- 75
Authors
6Topics & keywords
- Neuromorphic engineering
- Von Neumann architecture
- Computer science
- Bottleneck
- CMOS
- Matrix multiplication
- Unconventional computing
- Computer architecture
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