ROCm-OpenCL-Runtime
tensorflow-upstream
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ROCm-OpenCL-Runtime | tensorflow-upstream | |
---|---|---|
15 | 12 | |
171 | 677 | |
- | 0.6% | |
0.0 | 0.0 | |
3 months ago | 7 days ago | |
C++ | C++ | |
MIT License | Apache License 2.0 |
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Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
ROCm-OpenCL-Runtime
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ROCm Is AMD's #1 Priority, Executive Says
Its not that they're supporting buggy code, they just downgraded the quality of their implementation significantly. They made the compiler a lot worse when they swapped to rocm
https://github.com/RadeonOpenCompute/ROCm-OpenCL-Runtime/iss... is the tracking issue for it filed a year ago, which appears to be wontfix largely because its a lot of work
OpenCL still unfortunately supports quite a few things that vulkan doesn't, which makes swapping away very difficult for some use cases
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rocm-opencl (rocm-opencl-runtime) rx 6600 xt support
There's https://docs.amd.com/bundle/ROCm-Installation_FAQ/page/Frequently_Asked_Questions.html which leads to a page which doesn't list any gpus that I can see, there's https://rocm.docs.amd.com/en/latest/release/gpu_os_support.html which lists "RDNA2" , there's https://github.com/RadeonOpenCompute/ROCm/issues/1698 which is from last year and mentions changing an env for the RX 6600 XT (navi 23) . Not a lot is mentioned in the readme of https://github.com/RadeonOpenCompute/ROCm-OpenCL-Runtime .
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Install ROCm Fedora 38
$ dnf info rocm-opencl Installed Packages Name : rocm-opencl Version : 5.4.3 Release : 2.fc38 Architecture : x86_64 Size : 1.7 M Source : rocm-opencl-5.4.3-2.fc38.src.rpm Repository : @System From repo : updates Summary : ROCm OpenCL Runtime URL : https://github.com/RadeonOpenCompute/ROCm-OpenCL-Runtime License : MIT Description : ROCm OpenCL language runtime. : Supports offline and in-process/in-memory compilation.
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Horrible Code, Clean Performance
Thank you for subscribing to AMD OpenCL Facts! To unsubscribe please type AARRHGHGH. I'm open for questions though, and the bug report for this is here. For more mildly disgruntled rambling:
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First time in 2 years I was able to get Blender running with an AMD GPU on Linux!
Eg this bug about shared cl/gl textures with mipmaps being broken has now breached its first birthday, without even acknowledgement - basic cl/gl functionality here. This bug took a year for a fix to make its way into a public driver. And this fairly performance critical bug is just "wontfix", and also a significant downgrade from their old driver stack
- Final fantasy 7 remake Green artifacts after switching to amd proprietary drivers
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So far I'm unconvinced a 34MB binary blob is more free than OpenZFS.
Its definitely workable if you're willing to put in the effort (except for things that are straight up broken in some cases, like device side enqueue), but there are some issues that require.. fairly major workarounds
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New NVIDIA Open-Source Linux Kernel Graphics Driver Appears
Their implementation is here: https://github.com/RadeonOpenCompute/ROCm-OpenCL-Runtime
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C++ Show and Tell - April 2022
After a lot of moderately annoyed testing, I discovered that the AMD OpenCL implementation is.. rather dumb. If any two kernels share any arguments arguments, it inserts a command barrier between the two, hard-stalling the GPU. After filing a bug, it turns out this is wontfix as well, which is doubly bad. There's no set of flags in OpenCL that you can use to fix this either
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[TPU] AMD ROCm 4.5 Drops "Polaris" Architecture Support
What's particularly bizarre, is that with one bug report I filed, they claim to have fixed it internally in april, but.. no public driver has ever been released with the fix. For 7 months? Which is just a bizarre software development process
tensorflow-upstream
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Disable "SetTensor/CopyTensor" console logging.
I tried to train another model using InceptionResNetV2 and the same issues happens. Also, this happens even using the model.predict() method if using the GPU. Probably this is an issue related to the AMD Radeon RX 6700 XT or some mine misconfiguration. System Inormation: ArchLinux 6.1.32-1-lts - AMD Radeon RX 6700 XT - gfx1031 Opened issues: - https://github.com/RadeonOpenCompute/ROCm/issues/2250 - https://github.com/ROCmSoftwarePlatform/tensorflow-upstream/issues/2125
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Intel Extension For TensorFlow Released - Provides Intel GPU Acceleration
AMD has had their ROCM Tensorflow port for quite a while now: https://github.com/ROCmSoftwarePlatform/tensorflow-upstream and it works pretty well on my RX 6800; unfortunately it's only compatible with Linux as the ROCm stack is built on top of the Linux kernel I believe
- Even if you don’t like AMD cards, you have to admit, they look really cool.
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New NVIDIA Open-Source Linux Kernel Graphics Driver Appears
I mean, tensorflow has a fork with ROCm support which is maintained by AMD https://github.com/ROCmSoftwarePlatform/tensorflow-upstream although I'm not entirely sure what you're AI workloads are specifically, I'm just throwing out tensorflow because it's popular. On the enterprise side they also have radeon instinct MI, although I assume you're probably not using enterprise HW but I wanted to throw it out there anyway.
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ROCm v5.0 released with official Navi 21 support
It might work, but will likely require building pytorch/tensorflow from source. I compiled both with ROCm 5.0 today, Pytorch is painless but TF required using this repo maintained by AMD instead
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AMD GPU for ML ?
I saw this https://github.com/ROCmSoftwarePlatform/tensorflow-upstream and I thought it could be a way. Do you think it is not stable and ready to be used ?
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AMD on the Brink of Taking Over the GPU Market for Linux Gamers (Q2 2021 Survey Results)
The repo exists: https://github.com/ROCmSoftwarePlatform/tensorflow-upstream
- [D] Any issues with Ubuntu with dual boot and ROCM?
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Tensorflow with Radeon GPU
https://github.com/ROCmSoftwarePlatform/tensorflow-upstream#tensorflow-rocm-port
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Which version of ROCm and Tensorflow should I use?
I tried some case ROCm & Tensorflow-rocm as is on this page( tensorflow-upstream/tensorflow-rocm-release.md at develop-upstream · ROCmSoftwarePlatform/tensorflow-upstream · GitHub ), but I failed to run a simple CNN model with fashion-mnist datasets.
What are some alternatives?
ROCm - AMD ROCm™ Software - GitHub Home [Moved to: https://github.com/ROCm/ROCm]
seer - Seer - a gui frontend to gdb
rocm-arch - A collection of Arch Linux PKGBUILDS for the ROCm platform
rocm-build - build scripts for ROCm
GPU-Raytracer - GPU Raytracer from scratch in C++/CUDA
linux - XanMod: Linux kernel source code tree
chrgfx - Converts to and from tile based graphics from retro video game hardware
server - The Triton Inference Server provides an optimized cloud and edge inferencing solution.
muzero-cpp - A C++ pytorch implementation of MuZero
linux - Linux kernel source tree