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Message-ID: <4ED35E52.5010008@edigma.com>
Date:	Mon, 28 Nov 2011 10:11:30 +0000
From:	Nuno Santos <nsantos@...gma.com>
To:	Paulo Marques <pmarques@...popie.com>
CC:	linux-kernel@...r.kernel.org
Subject: Re: Floating point usage inside kernel

Ok, understood!

Just one more question. To do this, do I need to change the data type 
from double to int?

Thanks,

Nuno

On 11/25/2011 06:10 PM, Paulo Marques wrote:
> Nuno Santos wrote:
>>> [...]
>>> Unless you have overflow or need more than 16 bits of fractional
>>> precision, you'll have no problem with this approach.
>>>
>>> I hope this helps,
>> Sorry, i'm not sure if I have completely understand your suggestion. Are
>> you telling me to apply this transform only to my input data, or to all
>> the operations that are applied in the function used in kernel?
> Imagine that your matrix coefficients are:
>
>   2.5,     1, 4.7
> 45.3, 0.765,  10
>     0,     0,   1
>
> and your input is:
>
> 3420.56, 5410.76, 1
>
> You start by converting the matrix coefficients:
>
> 2.5 * 65536.0 = 163840
> ....
>
> so the matrix becomes:
>
>   163840 65536 308019
> 2968781 50135 655360
>        0     0  65536
>
> This can be done in userspace and the coefficients can be sent to the
> kernel as fixed point numbers.
>
> You do the same (this time on the kernel) with your input, so it becomes:
>
> 224169820 354599567 65536
>
> Now you can do:
>
> q[0] = fixed_mul(p[0], a[0][0]) + fixed_mul(p[1], a[1][0]) +
> fixed_mul(p[2], a[2][0]);
> ....
>
> where "fixed_mul" is a function that does the multiplication as I
> explained earlier.
>
> To convert the result back to an integer, just shift down by 16.
>

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