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Inhalt bereitgestellt von PyTorch, Edward Yang, and Team PyTorch. Alle Podcast-Inhalte, einschließlich Episoden, Grafiken und Podcast-Beschreibungen, werden direkt von PyTorch, Edward Yang, and Team PyTorch oder seinem Podcast-Plattformpartner hochgeladen und bereitgestellt. Wenn Sie glauben, dass jemand Ihr urheberrechtlich geschütztes Werk ohne Ihre Erlaubnis nutzt, können Sie dem hier beschriebenen Verfahren folgen https://de.player.fm/legal.
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Half precision
Manage episode 301973966 series 2921809
Inhalt bereitgestellt von PyTorch, Edward Yang, and Team PyTorch. Alle Podcast-Inhalte, einschließlich Episoden, Grafiken und Podcast-Beschreibungen, werden direkt von PyTorch, Edward Yang, and Team PyTorch oder seinem Podcast-Plattformpartner hochgeladen und bereitgestellt. Wenn Sie glauben, dass jemand Ihr urheberrechtlich geschütztes Werk ohne Ihre Erlaubnis nutzt, können Sie dem hier beschriebenen Verfahren folgen https://de.player.fm/legal.
In this episode I talk about reduced precision floating point formats float16 (aka half precision) and bfloat16. I'll discuss what floating point numbers are, how these two formats vary, and some of the practical considerations that arise when you are working with numeric code in PyTorch that also needs to work in reduced precision. Did you know that we do all CUDA computations in float32, even if the source tensors are stored as float16? Now you know!
Further reading.
- The Wikipedia article on IEEE floating point is pretty great https://en.wikipedia.org/wiki/IEEE_754
- How bfloat16 works out when doing training https://arxiv.org/abs/1905.12322
- Definition of acc_type in PyTorch https://github.com/pytorch/pytorch/blob/master/aten/src/ATen/AccumulateType.h
83 Episoden
Teilen
Manage episode 301973966 series 2921809
Inhalt bereitgestellt von PyTorch, Edward Yang, and Team PyTorch. Alle Podcast-Inhalte, einschließlich Episoden, Grafiken und Podcast-Beschreibungen, werden direkt von PyTorch, Edward Yang, and Team PyTorch oder seinem Podcast-Plattformpartner hochgeladen und bereitgestellt. Wenn Sie glauben, dass jemand Ihr urheberrechtlich geschütztes Werk ohne Ihre Erlaubnis nutzt, können Sie dem hier beschriebenen Verfahren folgen https://de.player.fm/legal.
In this episode I talk about reduced precision floating point formats float16 (aka half precision) and bfloat16. I'll discuss what floating point numbers are, how these two formats vary, and some of the practical considerations that arise when you are working with numeric code in PyTorch that also needs to work in reduced precision. Did you know that we do all CUDA computations in float32, even if the source tensors are stored as float16? Now you know!
Further reading.
- The Wikipedia article on IEEE floating point is pretty great https://en.wikipedia.org/wiki/IEEE_754
- How bfloat16 works out when doing training https://arxiv.org/abs/1905.12322
- Definition of acc_type in PyTorch https://github.com/pytorch/pytorch/blob/master/aten/src/ATen/AccumulateType.h
83 Episoden
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Ähnelt PyTorch Developer Podcast
Africa-focused technology, digital and innovation ecosystem insight and commentary.
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continue reading
Show notes are at https://stevelitchfield.com/sshow/chat.html
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continue reading
Embedded is the show for people who love gadgets. Making them, breaking them, and everything in between. Weekly interviews with engineers, educators, and enthusiasts. Find the show, blog, and more at embedded.fm.
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continue reading
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…
continue reading
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…
continue reading
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