10.1038/s41928-018-0054-8
Crossref journal-article
Springer Science and Business Media LLC
Nature Electronics (297)
Bibliography

Le Gallo, M., Sebastian, A., Mathis, R., Manica, M., Giefers, H., Tuma, T., Bekas, C., Curioni, A., & Eleftheriou, E. (2018). Mixed-precision in-memory computing. Nature Electronics, 1(4), 246–253.

Authors 9
  1. Manuel Le Gallo (first)
  2. Abu Sebastian (additional)
  3. Roland Mathis (additional)
  4. Matteo Manica (additional)
  5. Heiner Giefers (additional)
  6. Tomas Tuma (additional)
  7. Costas Bekas (additional)
  8. Alessandro Curioni (additional)
  9. Evangelos Eleftheriou (additional)
References 46 Referenced 387
  1. Strukov, D. B., Snider, G. S., Stewart, D. R. & Williams, R. S. The missing memristor found. Nature 453, 80–83 (2008). (10.1038/nature06932) / Nature by DB Strukov (2008)
  2. Chua, L. Resistance switching memories are memristors. Appl. Phys. A 102, 765–783 (2011). (10.1007/s00339-011-6264-9) / Appl. Phys. A by L Chua (2011)
  3. Wong, H.-S. P. & Salahuddin, S. Memory leads the way to better computing. Nat. Nanotech. 10, 191–194 (2015). (10.1038/nnano.2015.29) / Nat. Nanotech. by HSP Wong (2015)
  4. Di Ventra, M. & Pershin, Y. V. The parallel approach. Nat. Phys. 9, 200–202 (2013). (10.1038/nphys2566) / Nat. Phys. by M Di Ventra (2013)
  5. Traversa, F. L. & Ventra, M. Di Universal memcomputing machines. IEEE Trans. Neural Netw. Learn. Syst. 26, 2702–2715 (2015). (10.1109/TNNLS.2015.2391182) / IEEE Trans. Neural Netw. Learn. Syst. by FL Traversa (2015)
  6. Sebastian, A. et al. Temporal correlation detection using computational phase-change memory. Nat. Commun. 8, 1115 (2017). (10.1038/s41467-017-01481-9) / Nat. Commun. by A Sebastian (2017)
  7. Le Gallo, M., Sebastian, A., Cherubini, G., Giefers, H. & Eleftheriou, E. Compressed sensing recovery using computational memory. In Proc. IEEE Int. Electron Devices Meeting (IEDM) 28.3.1–28.3.4 (IEEE, 2017). (10.1109/IEDM.2017.8268469)
  8. Hu, M. et al. Dot-product engine for neuromorphic computing: programming 1T1M crossbar to accelerate matrix-vector multiplication. In Proc. 53rd Annual Design Automation Conf. (DAC) 19:1–19:6 (ACM, 2016). (10.1145/2897937.2898010)
  9. Li, C. et al. Analogue signal and image processing with large memristor crossbars. Nat. Electron. 1, 52–59 (2018). (10.1038/s41928-017-0002-z) / Nat. Electron. by C Li (2018)
  10. Xu, H. et al. The chemically driven phase transformation in a memristive abacus capable of calculating decimal fractions. Sci. Rep. 3, 1230 (2013). (10.1038/srep01230) / Sci. Rep. by H Xu (2013)
  11. Ievlev, A. et al. Intermittency, quasiperiodicity and chaos in probe-induced ferroelectric domain switching. Nat. Phys. 10, 59–66 (2014). (10.1038/nphys2796) / Nat. Phys. by A Ievlev (2014)
  12. Cassinerio, M., Ciocchini, N. & Ielmini, D. Logic computation in phase change materials by threshold and memory switching. Adv. Mater. 25, 5975–5980 (2013). (10.1002/adma.201301940) / Adv. Mater. by M Cassinerio (2013)
  13. Sebastian, A., Le Gallo, M. & Krebs, D. Crystal growth within a phase change memory cell. Nat. Commun. 5, 4314 (2014). (10.1038/ncomms5314) / Nat. Commun. by A Sebastian (2014)
  14. Loke, D. et al. Ultrafast phase-change logic device driven by melting processes. Proc. Natl Acad. Sci. USA 111, 13272–13277 (2014). (10.1073/pnas.1407633111) / Proc. Natl Acad. Sci. USA by D Loke (2014)
  15. 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) / Adv. Mater. by CD Wright (2011)
  16. Hosseini, P., Sebastian, A., Papandreou, N., Wright, C. D. & Bhaskaran, H. Accumulation-based computing using phase-change memories with FET access devices. IEEE Electron. Dev. Lett. 36, 975–977 (2015). (10.1109/LED.2015.2457243) / IEEE Electron. Dev. Lett. by P Hosseini (2015)
  17. Borghetti, J. et al. ‘Memristive’ switches enable ‘stateful’ logic operations via material implication. Nature 464, 873–876 (2010). (10.1038/nature08940) / Nature by J Borghetti (2010)
  18. Kvatinsky, S. et al. MAGIC: memristor-aided logic. IEEE Trans. Circ. Syst. II: Express Briefs 61, 895–899 (2014). / IEEE Trans. Circ. Syst. II: Express Briefs by S Kvatinsky (2014)
  19. Bojnordi, M. N. & Ipek, E. Memristive Boltzmann machine: a hardware accelerator for combinatorial optimization and deep learning. In Proc. IEEE Int. Symp. on High Performance Computer Architecture (HPCA) 1–13 (IEEE, 2016). (10.1109/HPCA.2016.7446049)
  20. Shafiee, A. et al. ISAAC: a convolutional neural network accelerator with in-situ analog arithmetic in crossbars. In Proc. 43rd Int. Symp. on Computer Architecture 14–26 (IEEE, 2016). (10.1145/3007787.3001139)
  21. Sheridan, P. M. et al. Sparse coding with memristor networks. Nat. Nanotech. 12, 784–789 (2017). (10.1038/nnano.2017.83) / Nat. Nanotech. by PM Sheridan (2017)
  22. Choi, S., Sheridan, P. & Lu, W. D. Data clustering using memristor networks. Sci. Rep. 5, 10492 (2015). (10.1038/srep10492) / Sci. Rep. by S Choi (2015)
  23. Ambrogio, S. et al. Statistical fluctuations in HfOx resistive-switching memory: Part I—set/reset variability. IEEE Trans. Electron. Dev. 61, 2912–2919 (2014). (10.1109/TED.2014.2330200) / IEEE Trans. Electron. Dev. by S Ambrogio (2014)
  24. Fantini, A. et al. Intrinsic switching variability in HfO2 RRAM. In 5th IEEE International Memory Workshop 30–33 (IEEE, 2013). (10.1109/IMW.2013.6582090)
  25. Le Gallo, M., Tuma, T., Zipoli, F., Sebastian, A. & Eleftheriou, E. Inherent stochasticity in phase-change memory devices. In Proc. Eur. Solid-State Device Research Conf. (ESSDERC) 373–376 (IEEE, 2016). (10.1109/ESSDERC.2016.7599664)
  26. Gaba, S., Sheridan, P., Zhou, J., Choi, S. & Lu, W. Stochastic memristive devices for computing and neuromorphic applications. Nanoscale 5, 5872–5878 (2013). (10.1039/c3nr01176c) / Nanoscale by S Gaba (2013)
  27. Tuma, T., Pantazi, A., Le Gallo, M., Sebastian, A. & Eleftheriou, E. Stochastic phase-change neurons. Nat. Nanotech. 11, 693–699 (2016). (10.1038/nnano.2016.70) / Nat. Nanotech. by T Tuma (2016)
  28. Bekas, C., Curioni, A. & Fedulova, I. Low cost high performance uncertainty quantification. In Proc. 2nd Workshop on High Performance Computational Finance 8:1–8:8 (ACM, 2009). (10.1145/1645413.1645421)
  29. Klavík, P., Malossi, A. C. I., Bekas, C. & Curioni, A. Changing computing paradigms towards power efficiency. Phil. Trans. R. Soc. Lond. A 372, 20130278 (2014). (10.1098/rsta.2013.0278) / Phil. Trans. R. Soc. Lond. A by P Klavík (2014)
  30. Saad, Y. Iterative Methods for Sparse Linear Systems (Siam, Philadelphia, 2003). (10.1137/1.9780898718003)
  31. Higham, N. J. Accuracy and Stability of Numerical Algorithms (Siam, Philadelphia, 2002). (10.1137/1.9780898718027)
  32. Burr, G. W. et al. Recent progress in phase-change memory technology. IEEE J. Emerg. Sel. Top. Circuits Syst. 6, 146–162 (2016). (10.1109/JETCAS.2016.2547718) / IEEE J. Emerg. Sel. Top. Circuits Syst. by GW Burr (2016)
  33. Koelmans, W. W. Projected phase-change memory devices. Nat. Commun. 6, 8181 (2015). (10.1038/ncomms9181) / Nat. Commun. by WW Koelmans (2015)
  34. Sebastian, A., Krebs, D., Le Gallo, M., Pozidis, H. & Eleftheriou, E. A collective relaxation model for resistance drift in phase change memory cells. in International Reliability Physics Symp. (IRPS) MY.5.1–MY.5.6 (IEEE, 2015). (10.1109/IRPS.2015.7112808)
  35. Gallo, M. L., Sebastian, A., Krebs, D., Stanisavljevic, M. & Eleftheriou, E. The complete time/temperature dependence of I–V drift in PCM devices. In Int. Reliability Physics Symp. (IRPS) MY-1-1–MY-1-6 (IEEE, 2016). (10.1109/IRPS.2016.7574617)
  36. Mathew, R., Karantza-Wadsworth, V. & White, E. Role of autophagy in cancer. Nat. Rev. Cancer 7, 961–967 (2007). (10.1038/nrc2254) / Nat. Rev. Cancer by R Mathew (2007)
  37. Yang, Z. J., Chee, C. E., Huang, S. & Sinicrope, F. A. The role of autophagy in cancer: therapeutic implications. Mol. Cancer Ther. 10, 1533–1541 (2011). (10.1158/1535-7163.MCT-11-0047) / Mol. Cancer Ther. by ZJ Yang (2011)
  38. West, J., Bianconi, G., Severini, S. & Teschendorff, A. E. Differential network entropy reveals cancer system hallmarks. Sci. Rep. 2, 802 (2012). (10.1038/srep00802) / Sci. Rep. by J West (2012)
  39. Schramm, G., Kannabiran, N. & König, R. Regulation patterns in signaling networks of cancer. BMC Syst. Biol. 4, 1 (2010). (10.1186/1752-0509-4-162) / BMC Syst. Biol. by G Schramm (2010)
  40. Hong, S., Chen, X., Jin, L. & Xiong, M. Canonical correlation analysis for RNA-seq co-expression networks. Nucleic Acids Res. 41, e95–e95 (2013). (10.1093/nar/gkt145) / Nucleic Acids Res. by S Hong (2013)
  41. Feinberg, B., Wang, S. & Ipek, E. Making memristive neural network accelerators reliable. In Proc. IEEE Int. Symp. on High Performance Computer Architecture (HPCA) (IEEE, 2018). (10.1109/HPCA.2018.00015)
  42. Anzt, H., Heuveline, V. & Rocker, B. in Applied Parallel and Scientific Computing 237–247 (Springer, New York, 2012). (10.1007/978-3-642-28145-7_24)
  43. Nandakumar, S. R. et al. Mixed-precision training of deep neural networks using computational memory. Preprint at http://arXiv.org/abs/1712.01192 (2017).
  44. Breitwisch, M. et al. Novel lithography-independent pore phase change memory. In Proc. IEEE Symp. on VLSI Technology 100–101 (IEEE, 2007). (10.1109/VLSIT.2007.4339743)
  45. Papandreou, N. et al. Programming algorithms for multilevel phase-change memory. In Proc. Int. Symp. on Circuits and Systems (ISCAS) 329–332 (IEEE, 2011). (10.1109/ISCAS.2011.5937569)
  46. Li, B. & Dewey, C. N. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics 12, 323 (2011). (10.1186/1471-2105-12-323) / BMC Bioinformatics by B Li (2011)
Dates
Type When
Created 7 years, 4 months ago (April 11, 2018, 4:57 a.m.)
Deposited 1 month, 3 weeks ago (July 3, 2025, 11:41 a.m.)
Indexed 1 day, 21 hours ago (Aug. 27, 2025, 12:15 p.m.)
Issued 7 years, 4 months ago (April 17, 2018)
Published 7 years, 4 months ago (April 17, 2018)
Published Online 7 years, 4 months ago (April 17, 2018)
Funders 0

None

@article{Le_Gallo_2018, title={Mixed-precision in-memory computing}, volume={1}, ISSN={2520-1131}, url={http://dx.doi.org/10.1038/s41928-018-0054-8}, DOI={10.1038/s41928-018-0054-8}, number={4}, journal={Nature Electronics}, publisher={Springer Science and Business Media LLC}, author={Le Gallo, Manuel and Sebastian, Abu and Mathis, Roland and Manica, Matteo and Giefers, Heiner and Tuma, Tomas and Bekas, Costas and Curioni, Alessandro and Eleftheriou, Evangelos}, year={2018}, month=apr, pages={246–253} }