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Description
Hey Y'all!
I implementted some performance improvements for computing the explicit Q factor in the X{or,un}gY routines. This takes 2 forms.
C_1
is 0. This leads to some improvements in performance as well as on the first iteration assuming thatC_2
is I. This also leads to some performance improvements especially as the block size increasesimprovements down the line which I am in the process of implementing.
A more formal writeup of this can be found at my repository for my Master's Project
I compiled the tex file with the current version of pdftex on a linux machine.
In addition, I have attached some performance plots of computing the Q factor from the QR and LQ factorizations in double precision to motivate why I think it will be beneficial to refactor xLARFT to return a T matrix of the same shape as the triangular factor even before implementing the panel factorization. To see the justification of the panel factorization, see the above linked repository folder
dorgqrDorglqOptPerfExperiments.pdf
dorgqrDorglqPerfExperiments.pdf
dorgqrPerfExperiments.pdf
I ran these experiments on an AMD EPYC 7502 CPU and I ran each experiment 10 times reporting the mean of those experiments. To see the form of these experiments, see the files titled
timeDorgqrVsDorglq.c
,timeDorgqrVsDorglq.sh
, andtime_dorgqr_vs_dorglq.batch
found here. The .c file is the main driver that calls our FORTRAN routines and times execution, the .sh file calls our .c file with varying inputs, and the .batch file is what is used to run the job via slurm on the HPC I used.The main takeaway from these figures is that the slight improvements that we see in QR are not present as much in the LQ factorization so even without the more efficient panel factorization.
Checklist