Fwd: 4x4 single-precision matrix product with SSE

Hi René,

you might be completely right, I have yet to discover a better way of
ordering the registers. But I wonder, wouldn't the statement in line
49 coupled with line 52 make sure that dpps is done? The blendps
instruction in line 52 can not be computed unless the result of xmm13
from dpps in line 49 is known. By the time the program hits line 55,
all dependencies on xmm8 are gone. I have to admit though that I am
just guessing here, I don't think I have a good understanding yet as
to how to deal with instruction dependencies...

 41   # Calculate C(1,:).
 42   movaps %xmm4, %xmm10
 43   dpps $0xf1, %xmm8, %xmm10
 44   movaps %xmm5, %xmm11
 45   dpps $0xf2, %xmm8, %xmm11
 46   movaps %xmm6, %xmm12
 47   dpps $0xf4, %xmm8, %xmm12
 48   movaps %xmm7, %xmm13
 49   dpps $0xf8, %xmm8, %xmm13
 50   blendps $0x01, %xmm10, %xmm11
 51   blendps $0x03, %xmm11, %xmm12
 52   blendps $0x07, %xmm12, %xmm13
 53   addps %xmm13, %xmm0
 54
 55   movaps 0x20(A), %xmm8

On Sun, Mar 13, 2011 at 21:08, René Dudfield <[email protected]> wrote:
>
> Hi,
>
> I may be completely wrong... but I think you could avoid dependencies with this following block and xmm8?  dpps is high latency, so maybe you can do some non dependent things while it does it's business?
>
>   # Calculate C(1,:).
>   movaps %xmm4, %xmm10
>   dpps $0xf1, %xmm8, %xmm10
>   movaps %xmm5, %xmm11
>   dpps $0xf2, %xmm8, %xmm11
>   movaps %xmm6, %xmm12
>   dpps $0xf4, %xmm8, %xmm12
>   movaps %xmm7, %xmm13
>   dpps $0xf8, %xmm8, %xmm13
>   blendps $0x01, %xmm10, %xmm11
>   blendps $0x03, %xmm11, %xmm12
>   blendps $0x07, %xmm12, %xmm13
>   addps %xmm13, %xmm0
>
>   movaps 0x20(A), %xmm8
>
>
>
> 2011/3/13 Nicolas Bock <[email protected]>
>>
>> I have attached a short test project that demonstrates what I am doing.
>>
>> I time this simply with the time function, i.e.
>>
>> $ time ./mul_SSE 100000000
>>
>> real    0m1.037s
>> user    0m1.036s
>> sys     0m0.001s
>>
>> $ time ./mul_SSE4_1 100000000
>>
>> real    0m2.006s
>> user    0m2.003s
>> sys     0m0.002s
>>
>> I assume that I have prepared the A matrix for SSE a little bit by
>> "dilating" the elements into A = { A11, A11, A11, A11, A12, A12, ...  },
>> while for SSE4.1 I am calling the multiply with the transpose of B.
>>
>> As these matrices are really small, they should be completely in L1, so
>> the movaps operation should have pretty low latency. Since the SSE
>> version uses 4 times more data for A than the SSE4.1 version, I am
>> surprised that given the larger number of data movements for the SSE
>> version it still beats the SSE4.1 version. But maybe I am just not
>> coding this very intelligently.
>>
>> Any suggestions would be very welcome,
>>
>> Thanks already, nick
>>
>>
>> On 03/12/11 01:20, Frederic Marmond wrote:
>> > Hello Nicolas,
>> >
>> > Yes, it's the right place :)
>> > could you please paste your code as well as your benchmark context ?
>> >
>> > Fred
>> >
>> > 2011/3/11 Nicolas Bock <[email protected]
>> > <mailto:[email protected]>>
>> >
>> >     Hello list,
>> >
>> >     I am writing an assembly function that multiplies 2 4x4 single precision
>> >     matrices. I wrote 2 versions, one using SSE the other using SSE4.1. What
>> >     surprised me is that the SSE4.1 version fails to beat the SSE version,
>> >     it is in fact slightly slower.
>> >
>> >     Is this the right place to ask for help? If anyone is interested I can
>> >     post some code which would maybe clarify the situation a bit.
>> >
>> >     If this is not the right place, please ignore me...
>> >
>> >     nick
>> >
>> >
>
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