# Nvidia TF32 format

**URL:** <https://discourse.julialang.org/t/nvidia-tf32-format/39515>\
**Category:** GPU\
**Created:** [May 15, 2020, 10:08am UTC](https://discourse.julialang.org/t/nvidia-tf32-format/39515 "2020-05-15T10:08:08Z")\
**Posts on this page:** 1\
**Showing post:** 2

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**Author:** ![ImreSamu](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/imresamu/32/20677_2.png) [@ImreSamu](https://discourse.julialang.org/u/ImreSamu)\
**Post date:** [May 15, 2020, 10:59am UTC](https://discourse.julialang.org/t/nvidia-tf32-format/39515/2 "2020-05-15T10:59:27Z")

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> [@johnh](#):
>
> TF32 … Is this going to be useful for Julia GPU?

![](https://global.discourse-cdn.com/julialang/original/3X/6/8/6807a8556d42e51dc0d26fd91785ca60b5f2631c.png)

imho 🙂  
in the early time - the `BFloat16` format will be more supported

based on this news:  
[BFloat16 Support About To Land Within LLVM (13 May 2020)](https://www.phoronix.com/scan.php?page=news_item&px=BFloat16-For-LLVM-Landing-Soon)  
_“Arm has been pushing along the BFloat16 support for LLVM with ARMv8.6-A supporting the new format. But this BFloat16 LLVM support is also relevant ultimately for Intel AVX-512 BF16, Intel Nervana, Google Cloud TPUs, and other hardware coming out with BF16 support to bolster their machine learning capabilities.”_

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