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precision errors. microblaze vs matlab single precision... huh?

Hi all embedded gurus out there, I am working on an embedded platform using microblaze. I am trying to implement an algo, which does a inverse matrix function on the microblaze (via C) and then port the results back to matlab. so this is the scenario.

1) matlab generates some numbers, passes them to microblaze via the UART (ie. PC to UART) 2) microblaze will then generate the matrix, and then calculate its inverse and do other stuff (dot product of matrices etc etc). 3) microblaze will then send the result back to PC via UART.

Ok..so here's the problem. the result obtained differs from matlab's result (I coded the same implementation also in matlab). the result obtained varies up to an error of 1 decimal place!!!

How I tried to debug

1) step through the C code using the debugger for microblaze. (this is very cool tool). 2) at each step of the way, look at how the variables change for each operation in the C code running on microblaze...and also observe how the variables change in matlab

this is what I noticed thinking it was due to matlab processing it in double precision, i type cast the whole matlab routine in single precision. then I tried to verify it again in the same way. And I get the same problem :(

can anyone help? As a result of this precision errors, the whole algo fails to work. I am really not sure which one to trust now.

Would appreciate if anyone can help me on the same. The current microblaze platform is using hardware FPU.

Chris

Reply to
chriskoh
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Hi,

What rounding mode are you using for Matlab? MicroBlaze only uses round-to-nearest rounding mode.

In order to get exactly the same every result operation in Matlab has to be done in single-precision.

Göran

Reply to
Göran Bilski

Hi Goran, I am using type cast to single in matlab. Once you round the first variable to single in matlab, it should round everything after that to single already. Cos all resulting variables after that are already in single precision. right?

by the way, you say " In order to get exactly the same every result operation in Matlab has to be done in single-precision."

but my question is, the difference in values of the result amount to orders of >0.5 occasionally! Isnt that a bit too much difference in results?

Is the FPU inaccurate or am i seeing things...

Chris

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Reply to
chriskoh

Hi,

May 2 cents : It seems to me that Desktop PC FPU use larger mantissa internally than what is strictly required by the IEEE SP standard, especially for some operations (such as /,sqrt). That *might* explain your results.

Also, did you check that the matrix inversion algorithm you used is robust enough in terms of numerical stability ?

Hope it can help.

Steven

chriskoh a écrit :

Reply to
Steven Derrien

Hi Steven, so matlab results are more accurate? the matrix inversion algorithm method is rather robust actually in terms of numerical stability. What I noticed however is that the matrix formed already by my C code running on microblaze before the inversion has already some numerical differences with matlab's version. simple C code vs matlab single precision code. but different results obtained. All discovered by stepping through the C code running on microblaze. the matrix was formed simply by a dot product.

Chris

o be

Reply to
chriskoh

That expectation might be realistic for expression containing only multiplications and divisions. However, as soon as the expression contains additions of a large and a small value or a subtraction between two more or less equal values, the result depends heavily on the floating point representation.

What exactly is "single precision floating point" ?

I can think about at least a dozen representations that are using that name, in which each representations might return a different result with problematic parameters.

Paul

Reply to
Paul Keinanen

A couple a questions - Are your matrices anywhere near being singular? - Are the algorithms the same and implemented identically on the two systems? That will be most critical near singularity but even away from it there can be traps. - Is the data used the same? What do you lose transferring the data back and forth? - Finally, what happens when yo perform the obvious sanity check abd multiply the original matrix by its inverse?

Robert

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Reply to
Robert Adsett

Good day Paul, so which one is the correct one? PC's matlab of xilinx FPU? What do I make out of the results?

Chris

Reply to
chriskoh

Which one works? IE what hapens when you multiply the original matrix by its calculated inverse?

Robert

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Reply to
Robert Adsett

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