DaDianNao: A Machine-Learning Supercomputer
Inner Mongolia University · Institut national de recherche en informatique et en automatique
Abstract
Many companies are deploying services, either for consumers or industry, which are largely based on machine-learning algorithms for sophisticated processing of large amounts of data. The state-of-the-art and most popular such machine-learning algorithms are Convolutional and Deep Neural Networks (CNNs and DNNs), which are known to be both computationally and memory intensive. A number of neural network accelerators have been recently proposed which can offer high computational capacity/area ratio, but which remain hampered by memory accesses. However, unlike the memory wall faced by processors on general-purpose workloads, the CNNs and DNNs memory footprint, while large, is not beyond the capability of the on…
Citation impact
- FWCI
- 66.24
- Percentile
- 100%
- References
- 61
Authors
11Topics & keywords
- Computer science
- Supercomputer
- Memory footprint
- Convolutional neural network
- Speedup
- Parallel computing
- Artificial neural network
- Deep learning
- Affordable and clean energy