AMD Radeon and NVIDIA GeForce FP32/FP64 GFLOPS Table

10 thoughts on “AMD Radeon and NVIDIA GeForce FP32/FP64 GFLOPS Table”

1. nuninho1980 2014/03/05 at 14:18

   What’s the FP32/FP64 benchmark tool?? Do you use AIDA64?
2. JeGX Post Author2014/03/05 at 14:25

   The values don’t come from a benchmark tool, it’s just a compilation from articles / reviews.
3. DrBalthar 2014/03/05 at 14:49

   So basically theoretical peak performance instead of actual peak performance
4. Promilus 2014/03/05 at 17:31

   @DrBalthar – define “actual peak performance”
   I believe you are referring to typical/average real life performance but that one depends strongly by app you test it with.
5. DrBalthar 2014/03/06 at 15:44

   Well not really you can write very simple code that just does a MAD operation (as that’s the one the usually use for advertising FLOPs).
6. Promilus 2014/03/06 at 21:03

   “Well not really you can write very simple code that just does a MAD operation (as that’s the one the usually use for advertising FLOPs”)
   No, it was FPMADD but since all new GPUs uses FMA which does basically the very same thing but with more accurate final result it’s just as good. And btw it wouldn’t be best possible benchmark and “peak” performance since many apps uses only certain type of calculations. Bitcoin miners iirc used plenty of integer and bit operations which were much higher on AMD GPUs than NVidia’s – define universal “actual peak performance” then? There’s no such thing.
7. DrBalthar 2014/03/07 at 14:57

   The F in FLOP stands for Floating point so integer and bit operation are irrelevant. Using just FMA, FPNADD still would be the most fair test as it is the only operation used so there wouldn’t be any difference or cheating. Actual peak performance doesn’t mean real life application performance. It just means actually validated numbers and not just marketing material.
8. Promilus 2014/03/08 at 09:41

   @DrBalthar – sorry but I disagree. Test results of full FMA coverage on all ALUs would be the very same artificial as those of “theoretical peak performance” – it just doesn’t translate into real-world performance. Some apps uses more data parallelism, some more task parallelism, some uses both float and integer intensively and other are focused on fp64 only. Some shares a lot of calculation with CPU and some runs solely on GPU. FP MADD/FMA test results would mean absolutely nothing. For the very same reason there’s no “actual peak performance” benchmark for x86-64 CPUs. But you do have some peek of a real world performance with Linpack benchmark. Check top500.org, there’re both Rmax (linpack results) and Rpeak (theoretical performance) numbers. In mixed GPU and CPU clusters it’s ratio is close to 60-70%. On CPU only clusters it reaches 80-95%.
9. komar 2014/03/09 at 13:44

   gtx 690@ ES BIOS 450W PT150%- +150 mhz + 605 mhz gddr5

   baseclock 1065 mhz – boost 1215 mhz – 7.2ghz GDDR5

   AIda : 6.498 Tflops/s FP32 / 0.275 Tflops/s FP64
10. Roger Dahl 2014/05/04 at 04:59

    This is awesome. Thank you.

    It’s necessary to take these numbers with a grain of salt, and it’s difficult to estimate just how much salt is needed for any given architecture.

    I think a copy of the table that is sorted on FP64 would be useful as well.

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