ଟ͘ͷ֬తੜϞσϧͷֶशɾਪʹɼҰൠʹܭࢉίετ͕ߴ͍֬(ؔ)͔Βͷ αϯϓϦϯά͕ඞཁ • σόΠεҰൠʹॲཧೳྗ͕͍ͨΊɼσόΠε্ͰֶशɾਪΛ݁͢Δͷ͍͠ɽ ੜϞσϧͷֶश [1] R. Salakhutdinov and G. Hinton, “Deep Boltzmann Machines”, in Proceedings of the International Conference on Artificial Intelligence and Statistics, 2009, pp. 448-455. • ΤϯυσόΠεʹը૾ɾจষੜͷతλεΫҟৗݕɼ ऩूσʔλͷܽଛิɾϊΠζআڈͳͲ෯͍Ԡ༻ੑΛͨΒ͢ɽ ਂϘϧπϚϯϚγϯʹΑΔը૾ੜ[1] pθ (x) pdata (x) ਅͷ(σʔλ) ੜϞσϧ ੜϞσϧ Λσʔλ ʹ͚ۙͮΔΑ͏ʹֶश͢Δ pθ (x) pdata (x)
[1] S. H. Adachi and M. P. Henderson, “Application of Quantum Annealing to Training of Deep Neural Networks”, arXiv:1510.06356 2015. [2] D. Korenkevych et al., “Benchmarking Quantum Hardware for Training of Fully Visible Boltzmann Machines”, arXiv:1611.04528 2016. [3] W. Vinci et al., “A Path Towards Quantum Advantage in Training Deep Generative Models with Quantum Annealers”, arXiv:1912.02119 2019. • ϘϧπϚϯϚγϯ • ੍ݶϘϧπϚϯϚγϯ[1] • ՄࢹϊʔυͷΈͷϘϧπϚϯϚγϯ[2] • มΦʔτΤϯίʔμʢVAEʣ[3]
Quantum Hardware for Training of Fully Visible Boltzmann Machines”, arXiv:1611.04528 2016. [3] Z. Chen et al., “An empirical study of latency in an emerging class of edge computing applications for wearable cognitive assistance”, in Proceedings of the Second ACM/IEEE Symposium on Edge Computing, Oct. 2017, pp. 1-14. D-Wave 2000Q[1] • ྔࢠΞχʔϦϯάΛ׆༻ͨ͠ੜϞσϧͷֶशɾਪͷΈΛΤοδAI ʹద༻͢Δ߹ɼD-WaveϚγϯඅ༻ۃԹͷಈ࡞ڥΛཁ͢ΔͳͲͷ ཧ༝͔ΒΤοδྖҬͷஔࠔͰ͋Δɽ • D-WaveϚγϯΛར༻͢ΔࡍɼωοτϫʔΫΛܦ༝ͨ͠ΫϥυαʔϏε ͱͯ͠ར༻͢Δɽ • ΫϥυΛհͣ͞ΤοδଆͰֶशΛߦ͏͜ͱ͕Ͱ͖ͳ͍ͨΊɼσόΠεͱΫϥυؒͷཧత ͳڑʹىҼͨ͠௨৴Ԇ͕ൃੜ͢Δɽ • D-WaveϚγϯͷαϯϓϦϯάʹ͔͔Δ͕࣌ؒ֓ͶμsΦʔμʔ[2]Ͱ͋Δ͜ͱɼ͓ΑͼΫϥυ ͱͷ௨৴Ԇ͕֓ͶඦmsΦʔμʔ[3]Ͱ͋Δ͜ͱΛߟ͑ΔͱɼੜϞσϧͷֶशਪʹ͓͍ ͯ௨৴Ԇ͕ϘτϧωοΫʹͳΔɽ
Machine: an In-memory Computing Accelerator to Process Combinatorial Optimization Problems”, in IEEE Custom Integrated Circuits Conference (CICC), Apr. 2019, pp. 1-8. [2] M. Aramon et al., “Physics-Inspired Optimization for Quadratic Unconstrained Problems Using a Digital Annealer”, Front. Phys., vol. 7, no. 48, Apr. 2019. [3] E. Crosson and A. W. Harrow, “Simulated Quantum Annealing Can Be Exponentially Faster Than Classical Simulated Annealing”, in IEEE 57th Annual Symposium on Foundations of Computer Science (FOCS), Oct. 2016, pp. 714-723. • D-WaveϚγϯͷΑ͏ͳྔࢠϏοτͷৼΔ͍Λσδλϧճ࿏্ͰγϛϡϨʔτ͢Δͷͱͯ͠ɼ ΞχʔϦϯάϚγϯ͕͋Δɽ • ΞχʔϦϯάϚγϯ͜Ε·ͰʹɼݱߦͷD-WaveϚγϯͰղ͚ͳ͍αΠζΛ࣋ͭ߹ͤ ࠷దԽͷղ๏ͱͯ͠ɼͦͷ༗ޮੑ͕ࣔ͞Ε͍ͯΔɽ • ΞχʔϦϯάϚγϯɼD-WaveϚγϯͱൺͯখܕ͔ͭίετͰ͋ΓɼৗԹͰಈ࡞͢Δ ͱ͍͏ಛΛ༗͍ͯ͠Δɽ ※ ຊൃදʹ͓͚ΔΞχʔϦϯάϚγϯͷఆٛɼΠδϯάϞσϧͷجఈঢ়ଶ୳ࡧΛత ɹͱͨ͠ͷͰ͋ΓɼFPGAASICΛ༻͍ͨϋʔυΣΞ࣮[1,2]ʹՃ͑ɼGPUCPU ɹ্Ͱಈ࡞͢ΔιϑτΣΞ࣮[3]ؚΉ
ֶशσʔλͱͯ͠MNISTσʔληοτΛ༻͍ͯɼRBMͰը૾ͷੜաఔΛֶश͢Δɽ • ΞχʔϦϯάϚγϯ • σόΠε͔ΒͷαϯϓϦϯάཁٻΛड͚ɼܭࢉ݁ՌΛฦׂ͢ • αϯϓϦϯάͷॲཧʹɼSimulated Quantum Annealing(SQA)Λ༻͍Δɽ • SQAΛ࣮ͨ͠Sqaod[1]Λ༻͍ͯWeb APIΛߏஙͨ͠ɽ v 1 v 2 v 3 v n h 1 h 2 h m RBMͷάϥϑߏ ӅΕ m = 100 Մࢹ n = 784 ΞχʔϦϯάϚγϯ σόΠε CPU1ίΞ ϝϞϦ1GB CPU8ίΞ ϝϞϦ32GB αϯϓϦϯάཁٻ ܭࢉ݁ՌΛฦ͢ 20 Web API ֶशσʔλ [1] https://github.com/shinmorino/sqaod