[Numpy-discussion] Different results from repeated calculation, part 2

Holger Rapp Rapp@mrt.uka...
Thu Aug 14 13:29:00 CDT 2008


Am 14.08.2008 um 19:48 schrieb Alok Singhal:

> On 14/08/08: 10:20, Keith Goodman wrote:
>> A unit test is attached. It contains three tests:
>> In test1, I construct matrices x and y and then repeatedly  
>> calculate z
>> = calc(x,y). The result z is the same every time. So this test  
>> passes.
>> In test2, I construct matrices x and y each time before calculating z
>> = calc(x,y). Sometimes z is slightly different. But the x's test to  
>> be
>> equal and so do the y's. This test fails (on Debian Lenny, Core 2  
>> Duo,
>> with libatlas3gf-sse2 but not with libatlas3gf-sse).
>> test3 is the same as test2 but I calculate z like this: z =
>> calc(100*x,y) / (100 * 100). This test passes.
>> I get:
>> = 
>> =====================================================================
>> FAIL: repeatability #2
>> ----------------------------------------------------------------------
>> Traceback (most recent call last):
>>  File "/home/[snip]/test/repeat_test.py", line 73, in test_repeat_2
>>    self.assert_(result, msg)
>> AssertionError: Max difference = 2.04946e-16
> Could this be because of how the calculations are done?  If the
> floating point numbers are stored in the cpu registers, in this case
> (intel core duo), they are 80-bit values, whereas 'double' precision
> is 64-bits.  Depending upon gcc's optimization settings, the amount of
> automatic variables, etc., it is entirely possible that the numbers
> are stored in registers only in some cases, and are in the RAM in
> other cases.  Thus, in your tests, sometimes some numbers get stored
> in the cpu registers, making the calculations with those values
> different from the case if they were not stored in the registers.
The tests never fail on my CoreDuo 2 on MacOS X, just for the records ;)


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