What does HackerNews think of plaidml?

PlaidML is a framework for making deep learning work everywhere.

Language: C++

Whisper – open source speech recognition by OpenAI | Sep 2022
It understands my Swedish attempts at English really well with the medium.en model. (Although, it gives me a funny warning: `UserWarning: medium.en is an English-only model but receipted 'English'; using English instead.`. I guess it doesn't want to be told to use English when that's all it can do.)

However, it runs very slowly. It uses the CPU on my macbook, presumably because it hasn't got a NVidia card.

Googling about that I found [plaidML](https://github.com/plaidml/plaidml) which is a project promising to run ML on many different gpu architectures. Does anyone know whether it is possible to plug them together somehow? I am not an ML researcher, and don't quite understand anything about the technical details of the domain, but I can understand and write python code in domains that I do understand, so I could do some glue work if required.

Ask HN: Will there ever be a vendor agnostic GPU interface? | Oct 2021
Something like this: https://github.com/plaidml/plaidml ?
AMD Reveals the Radeon RX 6000 Series, Coming November 18th | Oct 2020
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Would PlaidML be a viable option for you? https://github.com/plaidml/plaidml
Vortex: OpenCL Compatible RISC-V GPGPU | Mar 2020
Deep Learning could in theory run on this using Intel PlaidML's Keras implementation in OpenCL https://github.com/plaidml/plaidml
Radeon Open Compute 3.0 | Dec 2019
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Check out PlaidML (from of all companies intel) to get AMD GPUs working with the Keras APIs for tensorflow

https://github.com/plaidml/plaidml
Show HN: Try running deep learning inference on Raspberry Pi | Dec 2018
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There is PlaidML[1] - a cross-platform deep learning framework that works, among others, on Raspberry Pi's GPU.

[1] - https://github.com/plaidml/plaidml

Edit: they don't support RPI GPU yet - https://github.com/plaidml/plaidml/issues/141
AMD Demos 7nm Vega GPU | Jun 2018
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> Is TF running on AMD Vega's?

Not with mainline kernel (which supports up to Polaris), but it it already got merged into 4.18 that is going to be released in a couple of weeks. Until then it requires a bit extra effort https://github.com/RadeonOpenCompute/ROCm#dkms-driver-instal...

> Keras?

over opencl with https://github.com/plaidml/plaidml
Google announces a new generation for its TPU machine learning hardware | May 2018
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We're working to provide more choice with PlaidML as well. You can use it to run Keras, ONNX, and TF models on AMD, Intel, and mobile/embedded GPUs, on most operating systems and OpenCL, LLVM, OpenGL, and soon CUDA and Metal, etc. We would welcome contributions for TensorFlow integration, ROCm support, and anything else that widens support to more people.

https://github.com/plaidml/plaidml
MacOS finally gains external GPU support | Mar 2018
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There is a project working for this: https://github.com/plaidml/plaidml
DLVM: A modern compiler framework for neural network DSLs | Feb 2018
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As far as I know Tile/PlaidML (Vertex.AI) is the only DSL+compiler that's usable for real workloads across a variety of hardware. https://github.com/plaidml/plaidml
Intel to Develop Discrete GPUs, Hires AMD's Raja Koduri as Chief Architect | Nov 2017
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No it won't. Especially if the price is competitive. Say for the price of 1 1080ti, if i can buy 1.5 units of comparable performance graphics card, i'll surely buy it. There are already resources being spent on OpenCI based ML/DL platforms (https://github.com/plaidml/plaidml). The architectures keep getting bigger and training time keeps getting longer. I think you underestimate this factor. I need as much gpu computing power as i can buy within the budget.
Sway 1.0 is not going to support the Nvidia proprietary driver | Oct 2017
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With regards to Deep Learning, a recently released Keras backend[0] actually supports OpenCL with direct validation on a few AMD cards. I've been playing around with it for the past week or so and so far have had no issues with it, though I'm admittedly not doing anything too serious.

0. https://github.com/plaidml/plaidml
AMD Announces 307% Increase in Q3 Earnings | Oct 2017
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I would give the framework developers some credit, they shipped and the field made a lot of progress on their tools. Getting good performance out of GPUs (CUDA or OpenCL) is quite difficult, cuDNN has historically been the only good low-level deep learning library, and NVIDIA makes great hardware. My company is building a fully open source low-level framework called PlaidML bringing OpenCL support and other benefits to the existing frameworks. We're starting with Keras, first code was posted last Friday: https://github.com/plaidml/plaidml