Use daal::static_threader_reduce in Linear Regression and dispatch grainSize hyperparameter

[avolkov-intel]

Description

Use daal::static_threader_reduce in Linear Regression algorithm to compute X^tX and X^tY matrices the same way it was done for Covariance algorithm (https://github.com/uxlfoundation/oneDAL/pull/3126).

Also add grainSize hyperparameter that controls the minimum number of blocks allocated to a single thread to the list of dispatched Linear Regression hyperparameters.

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Checklist to comply with before moving PR from draft:

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• [ ] I have measured performance for affected algorithms using scikit-learn_bench and provided at least summary table with measured data, if performance change is expected.
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[avolkov-intel]

/intelci: run

[david-cortes-intel]

The failing sklearnex test is due to small numerical differences, guess it's safe to just change the thresholds there.

But the test itself is not well designed: better would be to compare against a reference implementation like SciPy's, the same way it's done in other tests within sklearnex.

[icfaust]

It looks as though there is a precision issue with float32 which causes some sklearnex test failures.