Calculating with light using a chip-scale all-optical abacus

J. Feldmann; M. Stegmaier; N. Gruhler; C. Ríos; H. Bhaskaran; C. D. Wright; W. H. P. Pernice

doi:10.1038/s41467-017-01506-3

journal article Open Access Nov 02, 2017

Calculating with light using a chip-scale all-optical abacus

J. Feldmann M. Stegmaier N. Gruhler C. Ríos H. Bhaskaran C. D. Wright W. H. P. Pernice

Nature Communications Vol. 8 No. 1 · Springer Science and Business Media LLC

View at Publisher Save 10.1038/s41467-017-01506-3

Abstract

AbstractMachines that simultaneously process and store multistate data at one and the same location can provide a new class of fast, powerful and efficient general-purpose computers. We demonstrate the central element of an all-optical calculator, a photonic abacus, which provides multistate compute-and-store operation by integrating functional phase-change materials with nanophotonic chips. With picosecond optical pulses we perform the fundamental arithmetic operations of addition, subtraction, multiplication, and division, including a carryover into multiple cells. This basic processing unit is embedded into a scalable phase-change photonic network and addressed optically through a two-pulse random access scheme. Our framework provides first steps towards light-based non-von Neumann arithmetic.

Topics

No keywords indexed for this article. Browse by subject →

References

35

[1]

Georges, I. The Universal History of Computing: From the Abacus to the Quantum Computer (Wiley, New York, 2001).

[2]

The missing memristor found

Dmitri B. Strukov, Gregory S. Snider, Duncan R. Stewart et al.

Nature 2008 10.1038/nature06932

[3]

Borghetti, J. et al. ‘Memristive’ switches enable ‘stateful’ logic operations via material implication. Nature 464, 873–876 (2010). 10.1038/nature08940

[4]

Jeong, D. S., Kim, K. M., Kim, S., Choi, B. J. & Hwang, C. S. Memristors for energy-efficient new computing paradigms. Adv. Electron. Mater. 2, 1600090 (2016). 10.1002/aelm.201600090

[5]

Traversa, F. L. & Di Ventra, M. Universal memcomputing machines. IEEE Trans. Neural Networks Learn. Syst. 26, 2702–2715 (2015). 10.1109/tnnls.2015.2391182

[6]

Gallo, M. Le. et al. Mixed-Precision ‘Memcomputing’. Preprint at http://arxiv.org/abs/1701.04279 (2017).

[7]

Alduino, A. & Paniccia, M. Interconnects: wiring electronics with light. Nat. Photon. 1, 153–155 (2007). 10.1038/nphoton.2007.17

[8]

Phase-change materials for rewriteable data storage

Matthias Wuttig, Noboru Yamada

Nature Materials 2007 10.1038/nmat2009

[9]

Raoux, S., Xiong, F., Wuttig, M. & Pop, E. Phase change materials and phase change memory. MRS Bull. 39, 703–710 (2014). 10.1557/mrs.2014.139

[10]

Burr, G. W. et al. Recent progress in phase-change memorytechnology. IEEE J. Emerg. Sel. Top Circuits Syst. 6, 146–162 (2016). 10.1109/jetcas.2016.2547718

[11]

Rios, C., Hosseini, P., Wright, C. D., Bhaskaran, H. & Pernice, W. H. P. On-chip photonic memory elements employing phase-change materials. Adv. Mater. 26, 1372–1377 (2014). 10.1002/adma.201304476

[12]

Rios, C. et al. Integrated all-photonic non-volatile multi-level memory. Nat. Photon. 9, 725–732 (2015). 10.1038/nphoton.2015.182

[13]

Raoux, S. & Wuttig, M. Phase Change Materials-Science and Applications (Springer, US, 2009). 10.1007/978-0-387-84874-7

[14]

Wright, C. D., Liu, Y., Kohary, K. I., Aziz, M. M. & Hicken, R. J. Arithmetic and biologically-inspired computing using phase-change materials. Adv. Mater. 23, 3408–3413 (2011). 10.1002/adma.201101060

[15]

Wang, Q. et al. Optically reconfigurable metasurfaces and photonic devices based on phase change materials. Nat. Photonics 10, 60–65 (2015). 10.1038/nphoton.2015.247

[16]

Siegel, J., Schropp, A., Solis, J., Afonso, C. N. & Wuttig, M. Rewriteable phase-change optical recording in Ge2Sb2Te5 films induced by picosecond laser pulses. Appl. Phys. Lett. 84, 2250–2252 (2004). 10.1063/1.1689756

[17]

Nonvolatile All‐Optical 1 × 2 Switch for Chipscale Photonic Networks

Matthias Stegmaier, Carlos Rios, Harish Bhaskaran et al.

Advanced Optical Materials 2017 10.1002/adom.201600346

[18]

Shportko, K. et al. Resonant bonding in crystalline phase-change materials. Nat. Mater. 7, 653–658 (2008). 10.1038/nmat2226

[19]

Backus, J. Can programming be liberated from the von Neumann style? A functional style and its algebra of programs. Commun. ACM 21, 613–641 (1978). 10.1145/359576.359579

[20]

McMahon, P. L. et al. A fully programmable 100-spin coherent Ising machine with all-to-all connections. Science 354, 614–617 (2016). 10.1126/science.aah5178

[21]

Rudé, M. et al. Optical switching at 1.55 µm in silicon racetrack resonators using phase change materials. Appl. Phys. Lett. 103, 141119 (2013). 10.1063/1.4824714

[22]

Asghari, M. & Krishnamoorthy, A. V. Silicon Photonics: Energy-efficient communication. Nat. Photon. 5, 268–270 (2011). 10.1038/nphoton.2011.68

[23]

Sun, C. et al. Single-chip microprocessor that communicates directly using light. Nature 528, 534–538 (2015). 10.1038/nature16454

[24]

Lim, A. E. J. et al. Review of silicon photonics foundry efforts. IEEE J. Sel. Top Quantum Electron. 20, 8300112 (2014). 10.1109/jstqe.2013.2293274

[25]

Hochberg, M. & Baehr-Jones, T. Towards fabless silicon photonics. Nat. Photon. 4, 492–494 (2010). 10.1038/nphoton.2010.172

[26]

Pershin, Y. V., Castelano, L. K., Hartmann, F., Lopez-Richard, V. & Di Ventra, M. A Memristive Pascaline. IEEE Trans. Circuits Syst. II Express Briefs 63, 558–562 (2016). 10.1109/tcsii.2016.2530378

[27]

Shacham, A., Bergman, K. & Carloni, L. P. Photonic networks-on-chip for future generations of chip multiprocessors. IEEE Trans. Comput. 57, 1246–1260 (2008). 10.1109/tc.2008.78

[28]

Kim, J., Kim, J. M., Noh, S. H., Min, S. L. & Cho, Y. A space-efficient flash translation layer for compactflash systems. IEEE Trans. Consum. Electron. 48, 366–375 (2002). 10.1109/tce.2002.1010085

[29]

Compact spectrometer based on a disordered photonic chip

Brandon Redding, Seng Fatt Liew, Raktim Sarma et al.

Nature Photonics 2013 10.1038/nphoton.2013.190

[30]

Luo, L.-W. et al. WDM-compatible mode-division multiplexing on a silicon chip. Nat. Commun. 5, 3069 (2014).

[31]

Time-domain separation of optical properties from structural transitions in resonantly bonded materials

Lutz Waldecker, Timothy A. Miller, Miquel Rudé et al.

Nature Materials 2015 10.1038/nmat4359

[32]

Stegmaier, M., Rios, C., Bhaskaran, H. & Pernice, W. H. P. Thermo-optical Effect in Phase-Change Nanophotonics. ACS Photon. 3, 828–835 (2016). 10.1021/acsphotonics.6b00032

[33]

Breaking the Speed Limits of Phase-Change Memory

D. Loke, T. H. Lee, W. J. Wang et al.

Science 2012 10.1126/science.1221561

[34]

Xiong, F., Liao, A. D., Estrada, D. & Pop, E. Low-power switching of phase-change materials with carbon nanotube electrodes. Science 332, 568–570 (2011). 10.1126/science.1201938

[35]

Kim, I. S. et al. High performance PRAM cell scalable to sub-20nm technology with below 4F2 cell size, extendable to DRAM applications. Dig. Tech. Pap. - Symp. VLSI Technol. 203–204 (2010). 10.1109/vlsit.2010.5556228

Cited By

246

Full-cycle device-scale simulations of memory materials with a tailored atomic-cluster-expansion potential

Yuxing Zhou, Daniel F. Thomas du Toit · 2025

Nature Communications

Zero-power optoelectronic synaptic devices

Wen Huang, Pengjie Hang · 2020

Nano Energy

Toward non-volatile photonic memory: concept, material and design

Yongbiao Zhai, Jia-Qin Yang · 2018

Materials Horizons

Metrics

246

Citations

35

References

Details

Published: Nov 02, 2017
Vol/Issue: 8(1)
License: View

Authors

Cite This Article

J. Feldmann, M. Stegmaier, N. Gruhler, et al. (2017). Calculating with light using a chip-scale all-optical abacus. Nature Communications, 8(1). https://doi.org/10.1038/s41467-017-01506-3

Calculating with light using a chip-scale all-optical abacus

You May Also Like