Nvidia loves 1536 Cuda Cores

Discussion in 'Videocards - NVIDIA GeForce' started by jbscotchman, Mar 29, 2020.

  1. jbscotchman

    jbscotchman Ancient Guru

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    Something just occurred to me that 1536 seems to be a magic number for Nividia. Perhaps the current quarantine/virus situation got me thinking, whatever, just a mere opinion thread.

    Geforce GTX 580: 512 cuda cores. Price at Launch - $499

    Geforce GTX 680: 1536
    cuda cores. Price at Launch - $549 Wow, huge jump from previous generation! That many cores on one card!

    Geforce GTX 770: 1536 cuda cores. Price at Launch - $329 Same amount of cores with higher clock speeds and efficiency.

    Geforce GTX 970: 1664 cuda cores. Price at Launch - $329 More cores and a significant performance increase.

    Geforce GTX 1070: 1920 cuda cores. Price at Launch - $379 More cores and a significant performance increase.

    Geforce GTX 1660 TI: 1536 cuda cores. Price at Launch - $279 Less cores with similar and improved performance over last generations.

    Gerforce RTX 2060: 1920 cuda cores. Price at Launch - $349 But, not a huge increase in performance.

    The point of this? I guess I'm just excited to see what Ampere offers. Just pointing out how much can be done with newer IPC's/DX/API's/Memory Bandwidth. etc. And what PC Gamer doesn't love talking about video cards?
     
    Last edited: Mar 29, 2020
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  2. Mda400

    Mda400 Master Guru

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    It is interesting to see how each semiconductor design or fabrication company can make their cores/ process more efficient each generation.

    Seeing as process shrink has slowed down over the past decade, its more up to architecture re-designs to provide the big performance increases in my opinion, where as in the past rapid process shrinks would get you power reduction or more performance headroom often enough so that rethinking architecture wasn't as crucial as it is these days.

    To be alive at the time we use a different material than silicon is what i'm anxious for.
     
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  3. HeavyHemi

    HeavyHemi Ancient Guru

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    It's because of how they arrange their SMs. It has not changed to the point of adding separate tensor and RTX bits just to keep the same basic SM arrangement.
     

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