All-to-all reconfigurability with sparse and higher-order Ising machines (2312.08748v3)
Abstract: Domain-specific hardware to solve computationally hard optimization problems has generated tremendous excitement. Here, we evaluate probabilistic bit (p-bit) based Ising Machines (IM) on the 3-regular 3-Exclusive OR Satisfiability (3R3X), as a representative hard optimization problem. We first introduce a multiplexed architecture that emulates all-to-all network functionality while maintaining highly parallelized chromatic Gibbs sampling. We implement this architecture in single Field-Programmable Gate Arrays (FPGA) and show that running the adaptive parallel tempering algorithm demonstrates competitive algorithmic and prefactor advantages over alternative IMs by D-Wave, Toshiba, and Fujitsu. We also implement higher-order interactions that lead to better prefactors without changing algorithmic scaling for the XORSAT problem. Even though FPGA implementations of p-bits are still not quite as fast as the best possible greedy algorithms accelerated on Graphics Processing Units (GPU), scaled magnetic versions of p-bit IMs could lead to orders of magnitude improvements over the state of the art for generic optimization.
- Ising machines as hardware solvers of combinatorial optimization problems. Nature Reviews Physics, 4(6):363–379, 2022.
- An ising solver chip based on coupled ring oscillators with a 48-node all-to-all connected array architecture. Nature Electronics, pages 1–8, 2023.
- Scaling advantages of all-to-all connectivity in physical annealers: the coherent ising machine vs d-wave 2000q. Feedback, 1:a2, 2018.
- Combinatorial optimization by simulating adiabatic bifurcations in nonlinear hamiltonian systems. Science advances, 5(4):eaav2372, 2019.
- Physics-inspired optimization for quadratic unconstrained problems using a digital annealer. Frontiers in Physics, 7:48, 2019.
- Tianshi Wang. Oscillators do the hard bits. Nature Electronics, pages 1–2, 2023.
- Massively parallel probabilistic computing with sparse Ising machines. Nature Electronics, 5(7):460–468, 2022.
- Simulated annealing and Boltzmann machines: a stochastic approach to combinatorial optimization and neural computing. John Wiley & Sons, Inc., 1989.
- Itay Hen. Equation planting: a tool for benchmarking ising machines. Physical Review Applied, 12(1):011003, 2019.
- 3-regular three-xorsat planted solutions benchmark of classical and quantum heuristic optimizers. Quantum Science and Technology, 7(2):025008, 2022.
- Accelerating adaptive parallel tempering with fpga-based p-bits. In 2023 IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits), pages 1–2. IEEE, 2023.
- Nonequilibrium monte carlo for unfreezing variables in hard combinatorial optimization. arXiv preprint arXiv:2111.13628, 2021.
- Memcomputing for accelerated optimization. arXiv preprint arXiv:2003.10644, 2020.
- Digital annealer for high-speed solving of combinatorial optimization problems and its applications. In 2020 25th Asia and South Pacific Design Automation Conference (ASP-DAC), pages 667–672. IEEE, 2020.
- Next-generation topology of d-wave quantum processors. arXiv preprint arXiv:2003.00133, 2020.
- How we are leading a 3-xorsat challenge: From the energy landscape to the algorithm and its efficient implementation on gpus (a). Europhysics Letters, 133(6):60005, 2021.
- Improved distributed algorithms for random colorings. arXiv preprint arXiv:2309.07859, 2023.
- Integer factorization using stochastic magnetic tunnel junctions. Nature, 2019.
- Many-body effects-based invertible logic with a simple energy landscape and high accuracy. IEEE Journal on Exploratory Solid-State Computational Devices and Circuits, 2023.
- Accelerated quantum monte carlo with probabilistic computers. Communications Physics, 6(1):85, 2023a.
- A full-stack view of probabilistic computing with p-bits: devices, architectures and algorithms. IEEE Journal on Exploratory Solid-State Computational Devices and Circuits, 2023b.
- Daniel Brélaz. New methods to color the vertices of a graph. Communications of the ACM, 22(4):251–256, 1979.
- Scrambled linear pseudorandom number generators. ACM Transactions on Mathematical Software (TOMS), 47(4):1–32, 2021.
- Autonomous probabilistic coprocessing with petaflips per second. IEEE Access, 8:157238–157252, 2020.
- Magnetoresistive random access memory: Present and future. IEEE Transactions on Electron Devices, 67(4):1407–1419, 2020.
- Nanosecond random telegraph noise in in-plane magnetic tunnel junctions. Physical Review Letters, 126(11):117202, 2021.