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PyTorch 1.8, with AMD ROCm support

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Re: PyTorch 1.8, with AMD ROCm support

#3
This is pretty neat since it is the first time in years that a top-tier deep learning framework has official support for any training accelerator with open source kernel drivers.

I guess the TPU also doesn't require kernel drivers because you talk to it over network instead of PCIE. But you cannot buy a TPU, only the int8 edge TPU is for sale. (And I've heard that the edge TPU's are absolutely top-notch for performance per $ and Watt right now, as an aside.)

Re: PyTorch 1.8, with AMD ROCm support

#4

The supported ROCm version is 4.0 which only the latest AMD instinct supports it. There's still a long way before its supported in the latest consumer RDNA 2 GPUs ( RX 6000 series )

Lack of ROCm support in consumer RDNA 2 GPUs really makes it impossible for regular people to use ROCm. As an owner of an AMD Radeon RX 6800 I'm pretty salty about it.

Re: PyTorch 1.8, with AMD ROCm support

#5
post #4

The supported ROCm version is 4.0 which only the latest AMD instinct supports it. There's still a long way before its supported in the latest consumer RDNA 2 GPUs ( RX 6000 series )

Lack of ROCm support in consumer RDNA 2 GPUs really makes it impossible for regular people to use ROCm. As an owner of an AMD Radeon RX 6800 I'm pretty salty about it.

I am getting some conflicting messages about support. There is a small group of people working on ROCm for Julia (in AMDGPU.jl) and while that work is still alpha quality, they seem to expect even devices as old as RX 580 to work.

Are all of these support issues something that is on the ROCm/AMD/driver side, or are they on the side of libraries like pytorch?

Re: PyTorch 1.8, with AMD ROCm support

#6

This is pretty neat since it is the first time in years that a top-tier deep learning framework has official support for any training accelerator with open source kernel drivers. I guess the TPU also doesn't require kernel drivers because you talk to it over network instead of PCIE. But you cannot buy a TPU, only the int8 edge TPU is for sale. (And I've heard that the edge TPU's are absolutely top-notch for performan…

[deleted]

Re: PyTorch 1.8, with AMD ROCm support

#7
post #4

Earlier quoted context omitted.

Lack of ROCm support in consumer RDNA 2 GPUs really makes it impossible for regular people to use ROCm. As an owner of an AMD Radeon RX 6800 I'm pretty salty about it.

I am getting some conflicting messages about support. There is a small group of people working on ROCm for Julia (in AMDGPU.jl) and while that work is still alpha quality, they seem to expect even devices as old as RX 580 to work. Are all of these support issues something that is on the ROCm/AMD/driver side, or are they on the side of libraries like pytorch?

RX580 had a pro version which got ROCm support. It's the newer cards and older cards which aren't supported.

Re: PyTorch 1.8, with AMD ROCm support

#9

This is pretty neat since it is the first time in years that a top-tier deep learning framework has official support for any training accelerator with open source kernel drivers. I guess the TPU also doesn't require kernel drivers because you talk to it over network instead of PCIE. But you cannot buy a TPU, only the int8 edge TPU is for sale. (And I've heard that the edge TPU's are absolutely top-notch for performan…

I believe TensorFlow is a top-tier deep learning framework, and it had ROCm support since 2018.

> edge TPU's are absolutely top-notch for performance per $ and Watt right now

Do you mean "aren't"? The performance per $ and Watt is not awesome even when it was released, I was hoping for great toolchain support but that also didn't happen.

Re: PyTorch 1.8, with AMD ROCm support

#10

Earlier quoted context omitted.

I am getting some conflicting messages about support. There is a small group of people working on ROCm for Julia (in AMDGPU.jl) and while that work is still alpha quality, they seem to expect even devices as old as RX 580 to work. Are all of these support issues something that is on the ROCm/AMD/driver side, or are they on the side of libraries like pytorch?

RX580 had a pro version which got ROCm support. It's the newer cards and older cards which aren't supported.

Can confirm, I made an 8x rx580 rig for an r&d project specifically for that reason.
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