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The success of the quantum LINPACK benchmark should be viewed as the minimal requirement for a quantum computer to perform a useful task more » of solving linear algebra problems, such as linear systems of equations. We propose that a similar benchmark, called the quantum LINPACK benchmark, could be used to measure the whole machine performance of quantum computers. Although this task was not designed with a real application directly in mind, the LINPACK benchmark has been used to define the list of TOP500 supercomputers since the debut of the list in 1993. The LINPACK benchmark reports the performance of a computer for solving a system of linear equations with dense random matrices. We present a study of how random disorder in the effective Coulomb interaction strength affects the superconducting transition temperature in the Hubbard model.
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On a system with 49 thousand processors we achieved a sustained performance of 409 TFlop/s. On the Cray XT4 systems of the Oak Ridge National Laboratory (ORNL), for example, we currently run production jobs on 31 thousand processors and thereby routinely achieve a sustained performance that exceeds 200 TFlop/s. By implementing delayed Monte Carlo updates and a mixed single-/double precision mode, we are able to dramatically increase the efficiency of the code. Significant algorithmic improvements have been made to make effective more » use of current supercomputing architectures.
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Linpack benchmark cnet code#
The simulation code is written with a generic and extensible approach and is tuned to perform well at scale. Here we report the algorithmic and computational advances that enable us to study the effect of disorder and nano-scale inhomogeneities on the pair-formation and the superconducting transition temperature necessary to understand real materials. Staggering computational and algorithmic advances in recent years now make possible systematic Quantum Monte Carlo (QMC) simulations of high temperature (high-Tc) superconductivity in a microscopic model, the two dimensional (2D) Hubbard model, with parameters relevant to the cuprate materials.