The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Broadcast and Weight: An Integrated Network For Scalable Photonic Spike Processing
Abstract
We propose an on-chip optical architecture to support massive parallel communication among high-performance spiking laser neurons. Designs for a network protocol, computational element, and waveguide medium are described, and novel methods are considered in relation to prior research in optical on-chip networking, neural networking, and computing. Broadcast-and-weight is a new approach for combining neuromorphic processing and optoelectronic physics, a pairing that is found to yield a variety of advantageous features. We discuss properties and design considerations for architectures for scalable wavelength reuse and biologically relevant organizational capabilities, in addition to aspects of practical feasibility. Given recent developments commercial photonic systems integration and neuromorphic computing, we suggest that a novel approach to photonic spike processing represents a promising opportunity in unconventional computing.
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Cites
Jalali, B., & Fathpour, S. (2006) · Journal of Lightwave Technology · doi:10.1109/jlt.2006.885782 · Cited by 1,423
Modular and hierarchically modular organization of brain networks
Meunier, D., Lambiotte, R., & Bullmore, E. T. (2010) · Frontiers in Neuroscience · doi:10.3389/fnins.2010.00200 · Cited by 1,156
Analog Versus Digital: Extrapolating from Electronics to Neurobiology
Sarpeshkar, R. (1998) · Neural Computation · doi:10.1162/089976698300017052 · Cited by 496
Hybrid Integrated Platforms for Silicon Photonics
Liang, D., Roelkens, G., Baets, R., & Bowers, J. (2010) · Materials · doi:10.3390/ma3031782 · Cited by 316
Cited by
Deep learning with coherent nanophotonic circuits
Shen, Y., Harris, N. C., Skirlo, S., Prabhu, M., Baehr-Jones, T., Hochberg, M., Sun, X., Zhao, S., Larochelle, H., Englund, D., et al. (2017) · Nature Photonics · doi:10.1038/nphoton.2017.93 · Cited by 3,340
Photonics for artificial intelligence and neuromorphic computing
Shastri, B. J., Tait, A. N., Ferreira de Lima, T., Pernice, W. H. P., Bhaskaran, H., Wright, C. D., & Prucnal, P. R. (2021) · Nature Photonics · doi:10.1038/s41566-020-00754-y · Cited by 1,756
Self-citationAll-optical spiking neurosynaptic networks with self-learning capabilities
Feldmann, J., Youngblood, N., Wright, C. D., Bhaskaran, H., & Pernice, W. H. P. (2019) · Nature · doi:10.1038/s41586-019-1157-8 · Cited by 1,529
Neuromorphic photonic networks using silicon photonic weight banks
Tait, A. N., de Lima, T. F., Zhou, E., Wu, A. X., Nahmias, M. A., Shastri, B. J., & Prucnal, P. R. (2017) · Scientific Reports · doi:10.1038/s41598-017-07754-z · Cited by 849
Self-citationContinuous-variable quantum neural networks
Killoran, N., Bromley, T. R., Arrazola, J. M., Schuld, M., Quesada, N., & Lloyd, S. (2019) · Physical Review Research · doi:10.1103/physrevresearch.1.033063 · Cited by 418
Metadata
- Authors
- Tait, A. N., Nahmias, M. A., Shastri, B. J., & Prucnal, P. R.
- Venue
- Journal of Lightwave Technology
- Published
- 2014-11-01
- Volume
- 32
- Issue
- 21
- Pages
- 4029-4041
- ISSN
- 0733-8724 (ISSN-L)
- 1558-2213
- OpenAlex
- W2051270432
- Cited by
- 457
- References
- 4
- FWCI
- 16.18
- Type
- journal article
- Language
- en
- Open access
- closed
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- Tait, A. N., Nahmias, M. A., Shastri, B. J., & Prucnal, P. R. (2014). Broadcast and Weight: An Integrated Network For Scalable Photonic Spike Processing. Journal of Lightwave Technology. https://doi.org/10.1109/jlt.2014.2345652
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