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#Linpack benchmark results series
Besides solving linear systems, the RACBEM model can be used to perform a variety of linear algebra tasks relevant to many physical applications, such as computing spectral measures, time series generated by a Hamiltonian simulation, and thermal averages of the energy. The RACBEM model is efficient to be implemented on a quantum computer and can be designed to optimally adapt to any given quantum architecture, with relying on a black-box quantum compiler. Edit: this was an anomaly, higher score posted on page 2. To retrieve a copy send electronic mail to and by typing the message send performance from benchmark or from any machine on the. A detailed description as well as a list of performance results on a wide variety of machines is available in postscript form from netlib. I don't quite know how i managed to get such a top tier PC, I am not rich. The LINPACK Benchmark was introduced by Jack Dongarra.
#Linpack benchmark results pro
Below is an overview of the generalized performance for components where there is sufficient statistically significant data based upon user-uploaded results. Windows 11 pro 圆4 (Yes, it's genuinely a good OS) Benchmark Scores. We propose an input model called the Random Circuit Block-Encoded Matrix (RACBEM), which is a proper generalization of a dense random matrix in the quantum setting. metrics for this test profile configuration based on 60 public results since 6 March 2021 with the latest data as of 30 December 2021. These results are further compared to an optimized Fortran version of the standard Linpack benchmark. The success of the quantum LINPACK benchmark should be viewed as the minimal requirement for a quantum computer to perform a useful task of solving linear algebra problems, such as linear systems of equations. The use of this benchmark program is demonstrated by com-paring two different R execution environments, the standard open-source implementation 1 and a version optimized for Intel processors 18.
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We propose that a similar benchmark, called the quantum LINPACK benchmark, could be used to measure the whole machine performance of quantum computers. Runs the linpack benchmark on your system. Michael Heroux and others are working to hash out major kinks with the benchmark based on early results of tests. This is quite different than the problem that was used in the original LINPACK as that dealt with dense matrix problems. 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. With the new benchmark, it’s the sparse matrix problem that’s the focus. The LINPACK benchmark reports the performance of a computer for solving a system of linear equations with dense random matrices.