
Shader arithmetic performance
kos Dec 19, 2008 3:30 PM (in response to Firestrider)What's RSX ? videochip in PS3 ? PS3 = nVidia 7800GTX + CELL = 400500 Gflops for both. Remember that cpu's can reach their peak theoretical performance, but for gpu it's much harder to do, but I' saw some exemples where that is possible  it depends only on your code.

Shader arithmetic performance
Firestrider Dec 19, 2008 3:59 PM (in response to kos)Can you link me to such examples?
According to wikipedia only the RSX (yes GFX in PS3) has a theoretical floating point arithmetic performance of 1.8 teraFLOPS and that the whole PS3 can do 2 teraFLOPS...but this could be wrong.

Shader arithmetic performance
kos Dec 19, 2008 5:28 PM (in response to Firestrider)There is nothing about 2Tera... anything. 90nm chip is just a sh....t comparing to modern gpu's, I've seen some resourses on russian about testing gpu's, I think it won't be usefull for you.

Shader arithmetic performance
Firestrider Dec 19, 2008 6:20 PM (in response to kos)Guess Nvidia lied then.
Even if it is no use to me I would like to see it be proven.

Shader arithmetic performance
rick.weber Dec 20, 2008 12:44 AM (in response to Firestrider)I'm using a Firestream 9170 and I have gotten peak performance (well, 498GFlops/s out of the advertised 500) with CAL. The only problem was, the operation I had it do was completely nonsense and worthless (it did I think a 64 way unrolled madd in a for loop, forcing dependencies to prevent optimization while preventing pipeline stalling). Basically, how close to peak performance you get is a function of how memory bound your application is and what fraction of your instructions are actually computation. At the top end, the demo app I wrote has almost never reads from memory and does madd instructions (2 flops) almost exclusively. Conversely, if your app is a matrix addition, you'll be lucky to get 10% of the theoretical maximum since you're always loading data from memory (unless it's somehow cached from a previous operation, though I haven't really found anything on how caching works on these GPUs so even then I can't say for certain). Also, if you want to get maximal performance, you'll need to spend a lot of time optimizing your code for the pipeline and to mask dependencies.
So, in short, some applications can see upwards of 80% of peak performance while others will fall flat on their face, barely achieving 1%.





Shader arithmetic performance
pbhani Dec 22, 2008 5:58 AM (in response to Firestrider)> Can the Radeon 4870 or FireStream 9270 actually reach their theoretical
> FLOPS in real world applications, or is it just a bunch of hype?
Not sure about nVidia, but AMD GPUs definitely can deliver the performance that we claim they do :) However, it is important to understand what GPU performance really means.
Peak GPU Performance = Engine Clock * Number of Engines * Number of instructions per clock
For the RV770, the number is given by 750 MHz * 800 * 2 (1 MAD/cycle) = 1.2 TFlops!
Like someone already mentioned, you can actually write a kernel that will get you close to that performance number. However, the key issue is that:
 The above assumes that your kernel is _only_ doing arithmetic. So your peak ALU kernel could simply be doing a bunch of MADs and nothing else!
 Most real world applications need to read some input data and write some output data in order to do anything useful.
The above two factors imply that most real world applications will not be able to use the complete ALU muscle power of the GPU due to the simple reason that the kernels will get memory bound very soon. e.g. we GPU folks love to talk about our Matrix Multiplication kernel performance since MM has a high number of ALU operations (2n^3) compared to memory operations. Even then the best performing MM kernel that we have is memory limited! In this case, even with 100% cache efficiency, the performance is limited by the peak cache bandhwidth on the RV770 which is ~500 GB/s giving a maximum of 500 GFlops of performance for MM. Our optimized MM kernel gets close to that number on the RV770.
Hope this helps a bit.

Shader arithmetic performance
vvolkov Apr 28, 2009 8:18 AM (in response to pbhani)Originally posted by: pbhaniEven then the best performing MM kernel that we have is memory limited! In this case, even with 100% cache efficiency, the performance is limited by the peak cache bandhwidth on the RV770 which is ~500 GB/s giving a maximum of 500 GFlops of performance for MM. Our optimized MM kernel gets close to that number on the RV770.
Does it mean that you substantially outperform AMD's best MM kernel, which, as far as I see, runs at 300 GFlops on 4870?

Shader arithmetic performance
vvolkov Apr 28, 2009 1:23 PM (in response to vvolkov)Originally posted by: vvolkovDoes it mean that you substantially outperform AMD's best MM kernel, which, as far as I see, runs at 300 GFlops on 4870?
Oops, seems that I was wrong. simple_matmult in SDK runs at close to 500 GFLOPS on 4870.
I was confused by http://developer.amd.com/gpu_assets/IUCAA_Pune_PEEP_2008.pdf that mentions 300 GFLOPS in SGEMM and 137 GFLOPS in DGEMM on 3870. It does not seem right, as 3870's peak in double precision is only ~100 GFLOPS (right?). Also, compute_matmult in SDK indeed runs at ~300 GFLOPS but on 4870.

Shader arithmetic performance
MicahVillmow Apr 28, 2009 2:24 PM (in response to vvolkov)vvolkov,
What we see on our optimized MM kernel is ~540 gflops in IL. This is not the optimal as I expect that it is possible to get closer to 600+ gflops with a handcoded isa implementation.
The compute_matmult is not even close to optimal as there is a huge dropoff in performance once you hit certain matrix sizes. compute_matmult when written optimally should outperform simple_matmult and should hit around ~640 gflops. So there is still room for improvement, but would probably be left for someone else to figure out how.

Shader arithmetic performance
vvolkov Apr 28, 2009 3:48 PM (in response to MicahVillmow)Originally posted by: MicahVillmow
What we see on our optimized MM kernel is ~540 gflops in IL. This is not the optimal as I expect that it is possible to get closer to 600+ gflops with a handcoded isa implementation.
Micah, thanks for your reply. Could you also comment on the numbers given in this presentation, slide 20  http://developer.amd.com/gpu_assets/IUCAA_Pune_PEEP_2008.pdf
It claims 137 GFLOPS in DGEMM achieved by AMD Core Math Libary using 3870, which looks very sexy. However, please correct me if I'm wrong, this is above the theoretical peak of 3870 in double precision, which is around 100 GFLOPS. Do you know how that could be possible?
Thanks,
Vasily

Shader arithmetic performance
MicahVillmow Apr 28, 2009 4:17 PM (in response to vvolkov)On a single 3870, the peaks for matmult with ACML is ~180 and ~80, the numbers being quoted I think is the 3870x2 as ACML can run on multiple GPU's.




