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From Janardhan Pulivarthi <janardhan.pulivar...@gmail.com>
Subject Re: Numerical accuracy of DML.
Date Sun, 20 Aug 2017 11:09:11 GMT
Thanks for the detailed explanation. I have found the following
research "*Scalable
and Numerically Stable Descriptive Statistics in SystemML*" to understand
more about the implementation.

Yes, doing something like this will definitely cause a little trouble for
the algorithms developer who works at the script level.

Thank you,
Janardhan

On Sat, Aug 19, 2017 at 3:14 AM, Matthias Boehm <mboehm7@googlemail.com>
wrote:

> Good question - let me separate the somewhat orthogonal aspects to it.
>
> First, for descriptive statistics such as sum, mean, skewness, or kurtosis,
> we already use numerically stable implementations based on Kahan Plus (see
> org.apache.sysml.runtime.functionobjects.KahanPlus if your interested).
> However, for performance reasons, operations like matrix multiplication
> rely on the basic multiply and adds (except for block aggregations of
> distributed operations which also use KahanPlus).
>
> Second, for comparisons, we do simply rely on Java's builtin operators.
> Once we extend the rather limited NaN support, we should change that to
> Double.compare accordingly. However, both of these alternatives check for
> exact matches. Hence, for comparisons of equivalence on script level, it's
> usually a better idea to compare with a tolerance as follows:
> abs(1-val)<10e-4 instead of val==1. Doing something like this inside the
> builtin operations would probably create more problems and confusion than
> it helps.
>
> Regards,
> Matthias
>
>
> On Fri, Aug 18, 2017 at 11:39 PM, Janardhan Pulivarthi <
> janardhan.pulivarthi@gmail.com> wrote:
>
> > Dear committers,
> >
> > May I know the numerical accuracy of dml at present, and are you planning
> > to increase it. It seems for comparison operators we have depended upon
> > java numerical floating point accuracy.
> >
> > Thank you very much,
> > Janardhan
> >
>

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