Nvidia Pascal Announcement

Discussion in 'Architecture and Products' started by huebie, Apr 5, 2016.

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  1. huebie

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    Just in case you want to watch the livestream:

    [​IMG]
     
  2. Grall

    Grall Invisible Member
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    BLAAAAAAHHHH, flash player! Wtf, Nvidia!
     
  3. Razor1

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    Presentation notes


    Cuda developers x4 over all

    Cuda developers in automotive and hyperscale x10


    nV SDK:

    Gameworks:

    Volumetric lighting

    Voxel Accelerated AO

    Hybrid frustum traced shadows


    Designworks:

    Adobe MDL

    Iray


    Compute Works:

    CUDA 8

    cuDnn 5

    nvGraph

    Index plugin Visualization of data quickly

    VRworks:

    Oculus Rift and HTC Vive

    Unreal, Max Play and Unity


    Driveworks:

    Still working on it, but is available to test with. Early access has already started Q1 of next year is the release.


    nV Jetpack

    GIE: GPU inference engine coming soon in May (jetson tx1: 24 images/watt), CUDA is the most energy efficient approach for deep learning.

    VR:

    Going to be able to do design visualization
    Going to places where we can't normal go

    Photo-real is a necessity, we need more performance.

    Iray Vr can do this takes many GPU's and time to do this for photo realism VR but can be done in real time now.

    Iray Vr lite, can be used on any hardware types and already has integration into 3dsMax and Maya and Google cardboard box coming in June.

    AI:

    5 years ago Deep learning started.

    Alpha Go, 1000 cpu's and 60 GPU's. Computers powered by deep learning can do more than humans can program for.

    New Computing model:

    Deep learning Object detection, DNN, Data HPC

    No longer have to have different programs written to do different things and it gets better results.

    Industry funding is high 5 billion

    AI has become a platform

    P100 is in volume production.

    P100 samples are out and they are being used by OEMs Q1 2017 servers will be available.

    Deep learning supercomputer DGX-1
    170 TF
    3200 watts, 8 GPU's, 7 tb sdd's, etc.
    12x faster performance for deep learning from last year.

    Pascal with recurrent neuronets:
    Interconnect is very important
    Capabilities:
    Persistent RNN's, keeping everything in the GPU with less
    Register file for pascal 14mb vs 8 mb in Maxwell
    nV link helps with splitting work across GPU's. Creates a wider model with more processors (30x more)

    TensorFlow, DGX-1, easy adaptability, performance is key.

    DGX-1 $129k

    Already getting colleges and research labs and medicine are targeted
     
    #3 Razor1, Apr 5, 2016
    Last edited: Apr 5, 2016
  4. fellix

    fellix Hey, You!
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  5. trinibwoy

    trinibwoy Meh
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    600 mm^2 on 16nm. Goddam.
     
  6. fellix

    fellix Hey, You!
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    Yep, Nvidia again simply asked TSMC for the maximum reticle they can put out and shove it with logic as dense as possible.

    But 14MB of GPR is curious -- now many MPs is that?
    GM200 has 6MB distributed over 24 multiprocessors.
     
  7. OlegSH

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  8. Voxilla

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    My last Pascal guess wasn't too far off.
    (Curiously they seem to have ditched the DLTOPs)


    Edit: The announced GP100 has 3584 cores and based on the 1.48Ghz boost clock does 10.6 TF
    So up from 3072 cores. Going from 8 to 15 B transistors only 512 more cores ? Most of the speedup comes from the higher clock. Additional going from 250W to 300W.
     
    #8 Voxilla, Apr 5, 2016
    Last edited: Apr 5, 2016
  9. fellix

    fellix Hey, You!
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    [​IMG]

    The multiprocessor design is very similar to Maxwell (sort of scaled down), now with more dedicated DP units and an updated ISA for mixed precision support.

    The shared memory size has been reduced, though. :???:
     
  10. Berek

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    It sounds like they announced the higher level introduction of Pascal for server use, but not any information about the consumer cards or mobile yet?
     
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  11. Newguy

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    So GP100 has 3584 cores but:

    "Each SM has 64 CUDA cores and four texture units, for a total of 3840 CUDA cores and 240 texture units."

    Interestingly some left there. Also not nearly as big of a jump in shaders as I would've thought.
     
  12. OlegSH

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    The amount of SMs has been doubled in GP100, it has 2x of registers and 1.5x of shared memory per lane
     
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  13. fellix

    fellix Hey, You!
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    I guess the mid-grade GeForce SKU will use a third smaller chip than the P100, with GDDR5X. That would result in slightly beefier GPU than GM204, but with much better perf/Watt and TurboBoost range.
     
  14. Ailuros

    Ailuros Epsilon plus three
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    I hope the diagram isn't misleading considering dedicated DP units; I didn't expect otherwise to be honest but I also didn't expect as many ;)
     
  15. SimBy

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    So nothing consumer grade shown?
     
  16. Razor1

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    nope nothing for gaming
     
  17. mpg1

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    weird...no hint as to even a date?
     
  18. fellix

    fellix Hey, You!
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    That's pretty high Turbo clock for the big Pascal -- 1480MHz. I can only imagine how high the smaller consumer SKUs will reach.
     
  19. Razor1

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    Well since all the software is going to be released in June and that software will need the next gen GPU to run..... something will be out by June.
     
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  20. McHuj

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    Hopefully, they drop the DP stuff for the consumer models and add more shaders instead.
     
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