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The first two benchmarks also benefit many cores, with FSI being pure compute.
In Handbrake, the profiles with a high PL1 benefit.
In Python and even more so Octave, Intel is the measure of all things, but all profiles are quite close to each other.
The next workload uses Octave, a programming language for scientific computing, to solve a variety of mathematical operations. The differences between the bar lengths of the profiles are much smaller than expected.
CalculiX is based on a free finite element program for three-dimensional structural calculations and focuses on speed. We already know that clock speed comes before cache and core count.
Convolution is a benchmark for a sub-area of function analysis in which a new, third function is created as the product of two functions (convolution, convolution). The clock rate and number of cores scale equally well here and the high PL1 helps two profiles in particular.
The FFTW test shows: The fast cores are once again in charge. And how… well, as long as they are well stuffed with energy. Here, Extreme and Insane run as if unleashed.
The underground structure of the earth can be determined using seismic processing. One of the four basic steps is Kirchhoff migration, which uses mathematical operations to model an image from the available data. The benchmark used, including the calculations included, shows the same picture: 125 watts is not a good calculation, you need a high PL1.
The Poisson equation is an elliptic, partial differential equation of the second order, which is used as part of boundary value problems in many areas of physics.
This workload deals with the processing of seismic data. It implements a Surface-Related Multiples Prediction (SRMP) algorithm written by Evgeny Kurin of GEOLAB Ltd. to remove multiples from seismic data. The differences are not that big now and we are done with it.
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