Title :
Spinto: High-performance energy minimization in spin glasses
Author :
García, Héctor J. ; Markov, Igor L.
Author_Institution :
Univ. of Michigan, Ann Arbor, MI, USA
Abstract :
With the prospect of atomic-scale computing, we study cumulative energy profiles of spin-spin interactions in non-ferromagnetic lattices (Ising spin-glasses)-an established topic in solid-state physics that is now becoming relevant to atomic-scale EDA. Recent proposals suggest non-traditional computing devices based on nature´s ability to find min-energy states. Spinto utilizes EDA-inspired high-performance algorithms to (i) simulate natural energy minimization in spin systems and (ii) study its potential for solving hard computational problems. Unlike previous work, our algorithms are not limited to planar Ising topologies. In one CPU-day, our branch-and-bound algorithm finds min-energy (ground) states on 100 spins, while our local search approximates ground states on 1,000,000 spins. We use this computational tool to study the significance of hyper-couplings in the context of recently implemented adiabatic quantum computers.
Keywords :
Ising model; ground states; physics computing; spin glasses; spin systems; spin-spin interactions; tree searching; EDA-inspired high-performance algorithms; Ising spin-glasses; Spinto; adiabatic quantum computers; atomic-scale EDA; atomic-scale computing; branch-and-bound algorithm; cumulative energy profiles; high-performance energy minimization; hyper-couplings; min-energy ground states; natural energy minimization; nonferromagnetic lattices; planar Ising topologies; solid-state physics; spin glasses; spin systems; spin-spin interactions; Computational modeling; Electronic design automation and methodology; Glass; Lattices; Minimization methods; Physics computing; Proposals; Quantum computing; Solid state circuits; Topology;
Conference_Titel :
Design, Automation & Test in Europe Conference & Exhibition (DATE), 2010
Conference_Location :
Dresden
Print_ISBN :
978-1-4244-7054-9
DOI :
10.1109/DATE.2010.5457217