STATICA: A 512-Spin 0.25M-Weight Annealing Processor With an All-Spin-Updates-at-Once Architecture for Combinatorial Optimization With Complete Spin–Spin Interactions

This article presents a high-performance annealing processor named STochAsTIc Cellular automata Annealer (STATICA) for solving combinatorial optimization problems represented by fully connected graphs. Supporting fully connected graphs is strongly required for dealing with realistic optimization problems. Unlike previous annealing processors that follow Glauber dynamics, our proposed annealer can update multiple states of fully connected spins simultaneously by introducing different dynamics called stochastic cellular automata annealing. It allows us to utilize the pipeline-level and memory-bank-level parallelization in addition to the PE-level parallelization originally adopted in the previous annealers. The STATICA prototype chip, which supports 512-spin fully connected graph, has been fabricated with the 65-nm CMOS technology and realized as a 3 mm $\times \,\,{4}$ mm chip. Using the fabricated 512-spin chip and numerical projections for a 2048-spin chip, we have conducted experiments to reveal the annealing performance of STATICA and examined how to control its annealing process efficiently.

[2]  Takashi Takemoto,et al.  CMOS Annealing Machine: A Domain-Specific Architecture for Combinatorial Optimization Problem , 2020, 2020 25th Asia and South Pacific Design Automation Conference (ASP-DAC).

[3]  Atsuyoshi Nakamura,et al.  Minor-embedding heuristics for large-scale annealing processors with sparse hardware graphs of up to 102,400 nodes , 2020, Soft Computing.

[4]  Benedetto Scoppola,et al.  Sampling from a Gibbs Measure with Pair Interaction by Means of PCA , 2012 .

[5]  Takayuki Shibasaki,et al.  Digital Annealer for High-Speed Solving of Combinatorial optimization Problems and Its Applications , 2020, 2020 25th Asia and South Pacific Design Automation Conference (ASP-DAC).

[6]  Toshiyuki Miyazawa,et al.  Physics-Inspired Optimization for Quadratic Unconstrained Problems Using a Digital Annealer , 2018, Front. Phys..

[7]  Daniel A. Lidar,et al.  Evidence for quantum annealing with more than one hundred qubits , 2013, Nature Physics.

[8]  Hayato Goto,et al.  FPGA-Based Simulated Bifurcation Machine , 2019, 2019 29th International Conference on Field Programmable Logic and Applications (FPL).

[9]  Masato Motomura,et al.  7.3 STATICA: A 512-Spin 0.25M-Weight Full-Digital Annealing Processor with a Near-Memory All-Spin-Updates-at-Once Architecture for Combinatorial Optimization with Complete Spin-Spin Interactions , 2020, 2020 IEEE International Solid- State Circuits Conference - (ISSCC).

[10]  Andrew Lucas,et al.  Ising formulations of many NP problems , 2013, Front. Physics.

[11]  M. W. Johnson,et al.  Quantum annealing with manufactured spins , 2011, Nature.

[12]  H. Nishimori,et al.  Quantum annealing in the transverse Ising model , 1998, cond-mat/9804280.

[13]  Hayato Goto,et al.  Combinatorial optimization by simulating adiabatic bifurcations in nonlinear Hamiltonian systems , 2019, Science Advances.

[14]  Hiroyuki Mizuno,et al.  A 20k-Spin Ising Chip to Solve Combinatorial Optimization Problems With CMOS Annealing , 2016, IEEE Journal of Solid-State Circuits.

[15]  Aidan Roy,et al.  A practical heuristic for finding graph minors , 2014, ArXiv.

[16]  B. Chakrabarti,et al.  Colloquium : Quantum annealing and analog quantum computation , 2008, 0801.2193.

[17]  E. Farhi,et al.  A Quantum Adiabatic Evolution Algorithm Applied to Random Instances of an NP-Complete Problem , 2001, Science.

[18]  Daniel A. Lidar,et al.  Defining and detecting quantum speedup , 2014, Science.

[19]  Hiroyuki Mizuno,et al.  24.3 20k-spin Ising chip for combinational optimization problem with CMOS annealing , 2015, 2015 IEEE International Solid-State Circuits Conference - (ISSCC) Digest of Technical Papers.

[20]  Hayato Goto Bifurcation-based adiabatic quantum computation with a nonlinear oscillator network , 2015, Scientific Reports.

[21]  Franz Rendl,et al.  A Spectral Bundle Method for Semidefinite Programming , 1999, SIAM J. Optim..

[22]  Ken-ichi Kawarabayashi,et al.  Binary optimization by momentum annealing. , 2019, Physical review. E.

[23]  Ken-ichi Kawarabayashi,et al.  A coherent Ising machine for 2000-node optimization problems , 2016, Science.