Data of Newton method of "A unifying framework for ADI-like methods for linear matrix equations and beneficial consequences" (Q6709932)

This deposit contains the datasets generated by the Newton method for the paper: J. Schulze, J. Saak: "A unifying framework for ADI-like methods for linear matrix equations and beneficial consequences". Download the individual files and store them inside the directory data/newton-adi/. The file names are structured as follows. Rail5177: Steel Profile benchmark problem of dimension 5177 adi_initprev=true|false: whether the initial ADI iterate was set to the solution of the previous Newton step (or zero) adi_kwargs=...: keyword arguments passed to ADI method maxiters=1000: maximum number of iterations shifts=...: shift strategy newton_kwargs=...: keyword arguments passed to Newton method inexact=true|false: whether to use inexact Newton method inexact_hybrid=true|false: whether to switch back to classical Newton method in later iterations (only present ifinexact=true) linesearch=true|false: whether to employ line search reltol=1e-10: relative tolerance to reason about convergence =1000: scaling of the quadratic term in the ARE .jld2: file suffix. All file have been generated withJLD2.jl version 0.4.38 Load the dataset via using JLD2 and file = load(FILENAME). This will yield a dictionary having the following entries: file["newton_metrics"]: data frame containing execution metrics of Newton iterations file["adi_metrics"]: data frame containing execution metrocs of ADI iterations of all Newton iterations file["timer"]: isolated runtime metrics generated withTimerOutputs.jl version 0.5.23 file["timer_metrics"]: runtime metrics of seperate run with additional data observers enabled file["config"]: internal configuration object that led to this dataset (information also embedded in file name) file["failed"]: Boolean on whether configuration has failed All data frames were generated with DataFrames.jl version 1.6.1 and have their columns documented using metadata. Generating this dataset took ~3h and consumed ~0.25kWh of electricity.