Conference item
On-chip phase-change photonic memory and computing
- Abstract:
- The use of photonics in computing is a hot topic of interest, driven by the need for ever-increasing speed along with reduced power consumption. In existing computing architectures, photonic data storage would dramatically improve the performance by reducing latencies associated with electrical memories. At the same time, the rise of ‘big data’ and ‘deep learning’ is driving the quest for non-von Neumann and brain-inspired computing paradigms. To succeed in both aspects, we have demonstrated non-volatile multi-level photonic memory avoiding the von Neumann bottleneck in the existing computing paradigm and a photonic synapse resembling the biological synapses for brain-inspired computing using phase-change materials (Ge2Sb2Te5).
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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Access Document
- Files:
-
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(Preview, Accepted manuscript, pdf, 463.2KB, Terms of use)
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- Publisher copy:
- 10.1117/12.2272127
Authors
- Publisher:
- Society of Photo-optical Instrumentation Engineers
- Host title:
- SPIE Nanoscience + Engineering, 2017, San Diego, California, United States
- Journal:
- SPIE NANOSCIENCE + ENGINEERING More from this journal
- Publication date:
- 2017-08-24
- Acceptance date:
- 2017-07-14
- Event location:
- San Diego, California, United States
- DOI:
- ISBN:
- 9781510611474
- Pubs id:
-
pubs:726823
- UUID:
-
uuid:6a897414-b5eb-416f-9bf3-452877a6465c
- Local pid:
-
pubs:726823
- Source identifiers:
-
726823
- Deposit date:
-
2017-09-11
- ARK identifier:
Terms of use
- Copyright holder:
- © (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE)
- Copyright date:
- 2017
- Notes:
- This is the author accepted manuscript following peer review version of the article. The final version is available online from Society of Photo-optical Instrumentation Engineers at: 10.1117/12.2272127
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