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Radeon ROCm 2.0 OpenCL Benchmarks With Linux 5.0 On Ubuntu 18.10 vs. NVIDIA's Linux Driver

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  • #11
    Originally posted by AndyChow View Post
    Radeon VII is MI50 made for consumers, right? I would like to see how it performs these tests, since it`s supposed to be a platform for ML/AI.
    Well, it > doubles memory bandwidth, but has only 60 CUs (instead of 64) and just runs them at higher clocks. So, unless Michael enables 8-bit or 4-bit options for inferencing, probably don't expect too much. Certainly, no more than about 2x (in memory-bound workloads).

    And it's still no match for Nvidia's Tensor cores (which these benchmarks don't seem to be using).
    Last edited by coder; 02-03-2019, 02:01 PM.

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    • #12
      Originally posted by s_j_newbury View Post
      No double precision benchmarks?
      Michael has the wrong hardware, if you care about fp64.

      Nvidia's Titan V is rated at 6.14 TFLOPS, while AMD's MI60 is rated at 7.36 TFLOPS. Anything consumer-grade is a toy, by comparison.

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      • #13
        Originally posted by smitty3268 View Post
        Pretty much, yeah. I think they're bumping some clock speeds a small amount and limiting the fp64 rate vs the pro card.
        It's 1/4th of the MI60, whereas Vega 64 is about half that. So, it'll net you more than 1 TFLOPS of fp64.

        I guess that's something.

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        • #14
          In terms of Machine Learning performance the only framework worth benchmarking and whose results matter is Tensorflow.

          GitHub stats: PlaidML - 1.9k stars, Tensorflow - 121k stars.

          Very few people heard or care about PlaidML.

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