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1.1 Computing's energy problem (and what we can do about it)
Abstract
Our challenge is clear: The drive for performance and the end of voltage scaling have made power, and not the number of transistors, the principal factor limiting further improvements in computing performance. Continuing to scale compute performance will require the creation and effective use of new specialized compute engines, and will require the participation of application experts to be successful. If we play our cards right, and develop the tools that allow our customers to become part of the design process, we will create a new wave of innovative and efficient computing devices.
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Cited by
Efficient Processing of Deep Neural Networks: A Tutorial and Survey
Sze, V., Chen, Y.-H., Yang, T.-J., & Emer, J. S. (2017) · Proceedings of the IEEE · doi:10.1109/jproc.2017.2761740 · Cited by 4,215
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
Eyeriss: An Energy-Efficient Reconfigurable Accelerator for Deep Convolutional Neural Networks
Chen, Y.-H., Krishna, T., Emer, J. S., & Sze, V. (2017) · IEEE Journal of Solid-State Circuits · doi:10.1109/jssc.2016.2616357 · Cited by 3,247
Memory devices and applications for in-memory computing
Sebastian, A., Le Gallo, M., Khaddam-Aljameh, R., & Eleftheriou, E. (2020) · Nature Nanotechnology · doi:10.1038/s41565-020-0655-z · Cited by 2,289
In-memory computing with resistive switching devices
Ielmini, D., & Wong, H.-S. P. (2018) · Nature Electronics · doi:10.1038/s41928-018-0092-2 · Cited by 2,298
Metadata
- Authors
- Horowitz, M.
- Venue
- 2014 IEEE International Solid-State Circuits Conference Digest of Technical Papers (ISSCC)
- Publisher
- IEEE
- Published
- 2014-02
- Pages
- 10-14
- ISSN
- 0193-6530 (ISSN-L)
- OpenAlex
- W1999085092
- Cited by
- 2,069
- References
- 0
- FWCI
- 27.58
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Horowitz, M. (2014). 1.1 Computing's energy problem (and what we can do about it). 2014 IEEE International Solid-State Circuits Conference Digest of Technical Papers (ISSCC). https://doi.org/10.1109/isscc.2014.6757323
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
