Intel DNNL 1.2 Library Hints at Int8 Data Type Support in Xe GPUs

(Image credit: Twitter)

Intel has released version 1.2 of DNNL, the company’s optimized library for high-performance deep learning operations on CPUs and its GPUs. The new version introduces support for int8 on GPUs, which indicates that this will be a standard feature of the Xe architecture.

Phoronix has reported on the release of DNNL 1.2, previously called MKL-DNN: the variant of the company’s math kernel library (MKL) for deep neural networks (DNN). New with this release is support for int8 on GPUs, according to the site (we could not find the patch notes).

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  • jkflipflop98
    Xe has the horsepower to really upend the GPU market. Hopefully management doesn't screw it up by releasing the mid- and low-range cards first. But that's most likely what they'll do.
    Reply
  • hannibal
    How would that be screw up? Most people buy low end cards, some people buy middle range gards, very minor buy highend GPUs...
    what we really should be worried is... Are Intel GPUs cheap enough to be competative.
    Reply
  • neojack
    @hannibal being a flagship would be very beneficial to them, since they enter the market late.

    being the "cheap" alternative wouldn't do XE any good.
    if intel do this, XE would be seen as the "cheap" alternative to radeons. wich are seen by most as the "cheap" alternative to geforce cards
    Reply
  • Chung Leong
    neojack said:
    @hannibal being a flagship would be very beneficial to them, since they enter the market late.

    Customers aren't going to spend top dollar on unproven technology. Being forced to sell at massive discounts is not beneficial. It would be seen as evidence of failure.
    Reply
  • bit_user
    Chung Leong said:
    Being forced to sell at massive discounts is not beneficial. It would be seen as evidence of failure.
    This is sound wisdom.

    Starting towards the lower-end is a lower-stakes proposition, for Intel. It gives them some breathing room and lets them adjust pricing until the product slots into a competitive segment.

    That's harder to do with a big GPU, and I think probably nearly sunk AMD's Vega. Without the crypto-boom, Vega might've even been a financial failure (some early analysis by another website showed they probably lost money on each Vega 56 card, at launch).

    Also, there's the reputational damage of launching a supposed high-end card that struggles to keep up with the mid-range.
    Reply