Ising Processing Units: Potential and Challenges for Discrete Optimization

07/02/2017
by   Carleton Coffrin, et al.
0

The recent emergence of novel computational devices, such as adiabatic quantum computers, CMOS annealers, and optical parametric oscillators, presents new opportunities for hybrid-optimization algorithms that leverage these kinds of specialized hardware. In this work, we propose the idea of an Ising processing unit as a computational abstraction for these emerging tools. Challenges involved in using and benchmarking these devices are presented, and open-source software tools are proposed to address some of these challenges. The proposed benchmarking tools and methodology are demonstrated by conducting a baseline study of established solution methods to a D-Wave 2X adiabatic quantum computer, one example of a commercially available Ising processing unit.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
11/28/2022

Benchmarking simulated and physical quantum processing units using quantum and hybrid algorithms

Powerful hardware services and software libraries are vital tools for qu...
research
01/21/2021

Noisy intermediate-scale quantum (NISQ) algorithms

A universal fault-tolerant quantum computer that can solve efficiently p...
research
05/16/2022

A BenchCouncil View on Benchmarking Emerging and Future Computing

The measurable properties of the artifacts or objects in the computer, m...
research
02/22/2022

SupermarQ: A Scalable Quantum Benchmark Suite

The emergence of quantum computers as a new computational paradigm has b...
research
10/29/2019

Quantum Computing based Hybrid Solution Strategies for Large-scale Discrete-Continuous Optimization Problems

Quantum computing (QC) has gained popularity due to its unique capabilit...
research
04/07/2021

Single-Qubit Fidelity Assessment of Quantum Annealing Hardware

As a wide variety of quantum computing platforms become available, metho...

Please sign up or login with your details

Forgot password? Click here to reset