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Re: (pain reloaded) Why worse performace in euclidean distance with SSE2?
- From: "Brian Budge" <brian dot budge at gmail dot com>
- To: "Dario Bahena Tapia" <dario dot mx at gmail dot com>
- Cc: gcc-help at gcc dot gnu dot org
- Date: Fri, 11 Apr 2008 12:13:01 -0700
- Subject: Re: (pain reloaded) Why worse performace in euclidean distance with SSE2?
- References: <3d104d6f0804091057v499dd62bxdbe224ad28441243@mail.gmail.com>
Hi Dario -
I got more than a 10% improvement on my machine, but I looked at the
code, and I must confess, I'm not sure what you're doing. It seems as
though the 0 and 1 cases are not equivalent code.
Can you explain the actual problem you're trying to solve?
On Wed, Apr 9, 2008 at 10:57 AM, Dario Bahena Tapia <dario.mx@gmail.com> wrote:
> Jello,
>
> I am still depressed about my performance. I have made following
> "improvements" in code:
>
> 1. I am not using sqrt function anymore (it seems squared euclidean
> distance is itself a metric)
>
> 2. I am using single precision calculations
>
> 3. I am using a different memory organization (SOA), now I have two
> big arrays with all X coordinates in one and all Y coordinates in the
> other.
>
> 4. I have changed logic to save once current point in registers and
> iterate, in a SIMD fashion, over the rest.
>
> 5. I am turning on full brutal optimization in gcc (-O3)
>
> Still with these changes, I only got an small improvement in time ...
> around 10%. I would have expected an improvement of around 75% given I
> am now doing 4 operations at a time (and that is if we do not count
> pipelining which may exec more than one SSE2 instruction at a "time"
> ... but unsure here, could be telling nonsense crap ;-).
>
> Please, hardcore intel gods of assembler optimization, provide some
> feedback for this poor beast of the forest.
>
> Thanks
>
> PS: Attached are the program, dummy makefile, sample usage and the
> assembler generated. An input size of 24,000 is enough to see the
> problem (dimension must be multiple of 8).
>
> On Tue, Apr 8, 2008 at 9:55 AM, Dario Bahena Tapia <dario.mx@gmail.com> wrote:
> > Hello,
> >
> > Yeah, others have suggested as well changing the way i process them in
> > order to allow for that. Working there ;-|
> >
> > Will consider the other suggestions as well !!!
> >
> > Thanks.
> >
> >
> >
> >
> > On Tue, Apr 8, 2008 at 2:07 AM, Zuxy Meng <zuxy.meng@gmail.com> wrote:
> > > Hi,
> > >
> > > "Dario Bahena Tapia" <dario.mx@gmail.com>
> > > 写入消息新闻:3d104d6f0804070617u47213cc8nbc697dab9dc262b5@mail.gmail.com...
> > >
> > >
> > >
> > > > Hello,
> > > >
> > > > I have just begun to play with SSE2 and gcc intrinsics. Indeed, maybe
> > > > this question is not exactly about gcc ... but I think gcc lists are
> > > > a very good place to find help from hardcore assembler hackers ;-1
> > > >
> > > > I have a program which makes heavy usage of euclidean distance
> > > > function. The serial version is:
> > > >
> > > > inline static double dist(int i,int j)
> > > > {
> > > > double xd = C[i][X] - C[j][X];
> > > > double yd = C[i][Y] - C[j][Y];
> > > > return rint(sqrt(xd*xd + yd*yd));
> > > > }
> > > >
> > > > As you can see each C[i] is an array of two double which represents a
> > > > 2D vector (indexes 0 and 1 are coordinates X,Y respectively). I tried
> > > > to vectorize the function using SSE2 and gcc intrinsics, here is the
> > > > result:
> > > >
> > > > inline static double dist_sse(int i,int j)
> > > > {
> > > > double d;
> > > > __m128d xmm0,xmm1;
> > > > xmm0 =_mm_load_pd(C[i]);
> > > > xmm1 = _mm_load_pd(C[j]);
> > > > xmm0 = _mm_sub_pd(xmm0,xmm1);
> > > > xmm1 = xmm0;
> > > > xmm0 = _mm_mul_pd(xmm0,xmm1);
> > > > xmm1 = _mm_shuffle_pd(xmm0, xmm0, _MM_SHUFFLE2(1, 1));
> > > > xmm0 = _mm_add_pd(xmm0,xmm1);
> > > > xmm0 = _mm_sqrt_pd(xmm0);
> > > > _mm_store_sd(&d,xmm0);
> > > > return rint(d);
> > > > }
> > > >
> > > > Of course each C[i] was aligned as SSE2 expects:
> > > >
> > > > for(i=0; i<D; i++)
> > > > C[i] = (double *) _mm_malloc(2 * sizeof(double), 16);
> > > >
> > > > And in order to activate the SSE2 features, I am using the following
> > > > flags for gcc (my computer is a laptop):
> > > >
> > > > CFLAGS = -O -Wall -march=pentium-m -msse2
> > > >
> > > > The vectorized version of the function seems to be correct, given it
> > > > provides same results as serial counterpart. However, the performace
> > > > is poor; execution time of program increases in approximately 50% (for
> > > > example, in calculating the distance of every pair of points from a
> > > > set of 10,000, the serial version takes around 8 seconds while
> > > > vectorized flavor takes 12).
> > > >
> > > > I was expecting a better time given that:
> > > >
> > > > 1. The difference of X and Y is done in parallel
> > > > 2. The product of each difference coordinate with itself is also done
> > > > in parallel
> > > > 3. The sqrt function used is hardware implemented (although serial
> > > > sqrt implementation could also take advantage of hardware)
> > > >
> > > > I suppose the problem here is my lack of experience programming in
> > > > assembler in general, and in particular with SSE2. Therefore, I am
> > > > looking for advice.
> > > >
> > >
> > > 1. First of all, you didn't extract the parallelism in your algorithm. SSE2
> > > won't help you if all you want is to pick up two points at random indices
> > > and calculate the distance. However it will help you a lot when you
> > > calculate the distances between a given point and 1 million others whose
> > > indices are sequential.
> > >
> > > 2. Unroll the loop to hide the latency of square root as much as possible.
> > >
> > > 3. Since the final result is an integer, you may consider using "float"
> > > instead of "double". That'll give you a performance boost even without SSE2.
> > > And rsqrtps comes in handy too, if its precision is acceptable.
> > >
> > > --
> > > Zuxy
> > >
> > >
> >
>