This README is intended to provide helpful information for Deep Learning developers with AMD ROCm.
Unfortunately, AMD's official repository for ROCm sometimes includes old or missing information. Therefore, on this readme, we will endeavor to describe accurate information based on the knowledge gained by GPUEater infrastructure development and operation.
- How to setup Radeon GPU Driver (ROCm) on Ubuntu16.04/18.04
- How to setup ROCm-Tensorflow on Ubuntu16.04/18.04
- ROCm(AMDGPU)-TensorFlow 1.12 Python2.7/Python3.5 + UbuntuOS
- ROCm(AMDGPU)-TensorFlow 1.x.x Python2.7/Python3.5/Python3.6 + UbuntuOS
- CPU-TensorFlow 1.x.x Python3.7 + MacOSX
- Lightweight ROCm-TensorFlow docker
- ROCm-TensorFlow on GPUEater
- ROCm-TensorFlow1.x docker
We got an error of hip module when ROCm driver updated 2.2 to 2.3 on RadeonVII.
> python3 -c "from tensorflow.python.client import device_lib; device_lib.list_local_devices()"
.
.
.
ImportError: /usr/local/lib/python3.5/dist-packages/tensorflow/python/../libtensorflow_framework.so: undefined symbol: hipModuleGetGlobal
If you got that same error, you have to install newer version like this.
sudo pip3 install tensorflow-rocm==1.13.1
or
sudo pip3 install tensorflow-rocm # latest
curl -sL http://install.aieater.com/setup_rocm_tensorflow_p35 | bash -
/opt/rocm/opencl/bin/x86_64/clinfo
johndoe@local:~$ /opt/rocm/opencl/bin/x86_64/clinfo
Number of platforms: 1
Platform Profile: FULL_PROFILE
Platform Version: OpenCL 2.1 AMD-APP (2679.0)
Platform Name: AMD Accelerated Parallel Processing
Platform Vendor: Advanced Micro Devices, Inc.
Platform Extensions: cl_khr_icd cl_amd_event_callback
Platform Name: AMD Accelerated Parallel Processing
Number of devices: 1
Device Type: CL_DEVICE_TYPE_GPU
Vendor ID: 1002h
Board name: Device 687f
Device Topology: PCI[ B#4, D#0, F#0 ]
Max compute units: 64
Max work items dimensions: 3
Max work items[0]: 1024
Max work items[1]: 1024
Max work items[2]: 1024
Max work group size: 256
Preferred vector width char: 4
Preferred vector width short: 2
Preferred vector width int: 1
Preferred vector width long: 1
Preferred vector width float: 1
Preferred vector width double: 1
Native vector width char: 4
Native vector width short: 2
Native vector width int: 1
Native vector width long: 1
Native vector width float: 1
Native vector width double: 1
Max clock frequency: 1630Mhz
Address bits: 64
Max memory allocation: 7287183769
Image support: Yes
Max number of images read arguments: 128
Max number of images write arguments: 8
Max image 2D width: 16384
Max image 2D height: 16384
Max image 3D width: 2048
Max image 3D height: 2048
Max image 3D depth: 2048
Max samplers within kernel: 26751
Max size of kernel argument: 1024
Alignment (bits) of base address: 1024
Minimum alignment (bytes) for any datatype: 128
Single precision floating point capability
Denorms: Yes
Quiet NaNs: Yes
Round to nearest even: Yes
Round to zero: Yes
Round to +ve and infinity: Yes
IEEE754-2008 fused multiply-add: Yes
Cache type: Read/Write
Cache line size: 64
Cache size: 16384
Global memory size: 8573157376
Constant buffer size: 7287183769
Max number of constant args: 8
Local memory type: Scratchpad
Local memory size: 65536
Max pipe arguments: 16
Max pipe active reservations: 16
Max pipe packet size: 2992216473
Max global variable size: 7287183769
Max global variable preferred total size: 8573157376
Max read/write image args: 64
Max on device events: 1024
Queue on device max size: 8388608
Max on device queues: 1
Queue on device preferred size: 262144
SVM capabilities:
Coarse grain buffer: Yes
Fine grain buffer: Yes
Fine grain system: No
Atomics: No
Preferred platform atomic alignment: 0
Preferred global atomic alignment: 0
Preferred local atomic alignment: 0
Kernel Preferred work group size multiple: 64
Error correction support: 0
Unified memory for Host and Device: 0
Profiling timer resolution: 1
Device endianess: Little
Available: Yes
Compiler available: Yes
Execution capabilities:
Execute OpenCL kernels: Yes
Execute native function: No
Queue on Host properties:
Out-of-Order: No
Profiling : Yes
Queue on Device properties:
Out-of-Order: Yes
Profiling : Yes
Platform ID: 0x7efc84a47df0
Name: gfx900
Vendor: Advanced Micro Devices, Inc.
Device OpenCL C version: OpenCL C 2.0
Driver version: 2679.0 (HSA1.1,LC)
Profile: FULL_PROFILE
Version: OpenCL 1.2
Extensions: cl_khr_fp64 cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics cl_khr_local_int32_base_atomics cl_khr_local_int32_extended_atomics cl_khr_int64_base_atomics cl_khr_int64_extended_atomics cl_khr_3d_image_writes cl_khr_byte_addressable_store cl_khr_fp16 cl_khr_gl_sharing cl_amd_device_attribute_query cl_amd_media_ops cl_amd_media_ops2 cl_khr_subgroups cl_khr_depth_images cl_amd_copy_buffer_p2p cl_amd_assembly_program
python3 -c "from tensorflow.python.client import device_lib;print(device_lib.list_local_devices())"
johndoe@local:~$ python3 -c "from tensorflow.python.client import device_lib;print(device_lib.list_local_devices())"
2018-10-11 21:17:31.776018: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX AVX2 FMA
2018-10-11 21:17:31.778774: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1524] Found device 0 with properties:
name: Ellesmere [Radeon RX 470/480]
AMDGPU ISA: gfx803
memoryClockRate (GHz) 1.38
pciBusID 0000:01:00.0
Total memory: 8.00GiB
Free memory: 7.75GiB
2018-10-11 21:17:31.778788: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1635] Adding visible gpu devices: 0
2018-10-11 21:17:31.778802: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1044] Device interconnect StreamExecutor with strength 1 edge matrix:
2018-10-11 21:17:31.778806: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1050] 0
2018-10-11 21:17:31.778810: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1063] 0: N
2018-10-11 21:17:31.778830: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1183] Created TensorFlow device (/device:GPU:0 with 7539 MB memory) -> physical GPU (device: 0, name: Ellesmere [Radeon RX 470/480], pci bus id: 0000:01:00.0)
[name: "/device:CPU:0"
device_type: "CPU"
memory_limit: 268435456
locality {
}
incarnation: 15907518430835446805
, name: "/device:GPU:0"
device_type: "GPU"
memory_limit: 7905424180
locality {
bus_id: 2
numa_node: 1
links {
}
}
incarnation: 9147052532367269657
physical_device_desc: "device: 0, name: Ellesmere [Radeon RX 470/480], pci bus id: 0000:01:00.0"
curl -sL http://install.aieater.com/setup_rocm | bash -
or
# Common
sudo apt update
sudo apt -y install software-properties-common curl wget # for add-apt-repository
# Python3.5
PYTHON35=false
if [[ `python3 --version` == *"3.5"* ]] ; then
echo 'python3.5 -- yes'
PYTHON35=true
else
echo 'python3.5 -- no'
PYTHON35=false
fi
if [ $PYTHON35 == 'true' ] ; then
sudo apt install -y python3.5 python3.5-dev python3-pip
else
sudo add-apt-repository -y ppa:deadsnakes/ppa
sudo apt-get update
sudo apt install -y python3.5 python3.5-dev python3-pip
sudo update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.5 1
sudo update-alternatives --set python3 /usr/bin/python3.5
python3 --version
curl https://bootstrap.pypa.io/get-pip.py -o /tmp/get-pip.py
sudo -H python3 /tmp/get-pip.py --force-reinstall
sudo apt-get remove -y --purge python3-apt
fi
wget -qO - http://repo.radeon.com/rocm/apt/debian/rocm.gpg.key | sudo apt-key add -
sudo sh -c 'echo deb [arch=amd64] http://repo.radeon.com/rocm/apt/debian/ xenial main > /etc/apt/sources.list.d/rocm.list'
sudo apt update
sudo apt install -y rocm-dkms rocm-libs miopen-hip cxlactivitylogger libnuma-dev
sudo usermod -a -G video $LOGNAME
/opt/rocm/opencl/bin/x86_64/clinfo
echo 'export ROCM_HOME=/opt/rocm' >> ~/.profile
echo 'export HCC_HOME=$ROCM_HOME/hcc' >> ~/.profile
echo 'export HIP_PATH=$ROCM_HOME/hip' >> ~/.profile
echo 'export PATH=/usr/local/bin:$HCC_HOME/bin:$HIP_PATH/bin:$ROCM_HOME/bin:$PATH:/opt/rocm/opencl/bin/x86_64' >> ~/.profile
echo 'export LD_LIBRARY=$LD_LIBRARY:/opt/rocm/opencl/lib/x86_64' >> ~/.profile
echo 'export LC_ALL="en_US.UTF-8"' >> ~/.profile
echo 'export LC_CTYPE="en_US.UTF-8"' >> ~/.profile
ROCm-TensorFlow for Python3.5 installation via PyPI (You need to install ROCm-driver before TensorFlow.)
sudo pip3 uninstall -y tensorflow
sudo pip3 install --user tensorflow-rocm
(Deprecated)
Python version 3.6 is the default python interpreter on Ubuntu 18.04. But as for Ubunt16.04, most of developers use Python version 3.5.
curl -sL http://install.aieater.com/setup_rocm_old | bash -
or
export PIP=pip3
export PYTHON=python3
sudo apt update
sudo apt upgrade -y
sudo apt install -y wget g++ cmake
mkdir -p ~/src
wget -qO - http://repo.radeon.com/rocm/apt/debian/rocm.gpg.key | sudo apt-key add -
sudo sh -c 'echo deb [arch=amd64] http://repo.radeon.com/rocm/apt/debian/ xenial main > /etc/apt/sources.list.d/rocm.list'
sudo apt update
sudo apt install -y libnuma-dev
sudo apt install -y rocm-dkms rocm-opencl-dev
sudo usermod -a -G video $LOGNAME
/opt/rocm/opencl/bin/x86_64/clinfo
echo 'export ROCM_HOME=/opt/rocm' >> ~/.profile
echo 'export HCC_HOME=$ROCM_HOME/hcc' >> ~/.profile
echo 'export HIP_PATH=$ROCM_HOME/hip' >> ~/.profile
echo 'export PATH=/usr/local/bin:$HCC_HOME/bin:$HIP_PATH/bin:$ROCM_HOME/bin:$PATH:/opt/rocm/opencl/bin/x86_64' >> ~/.profile
echo 'export LD_LIBRARY=$LD_LIBRARY:/opt/rocm/opencl/lib/x86_64' >> ~/.profile
echo 'export LC_ALL="en_US.UTF-8"' >> ~/.profile
echo 'export LC_CTYPE="en_US.UTF-8"' >> ~/.profile
source ~/.profile
# Python3
sudo apt-get update && sudo apt-get install -y \
$PYTHON-numpy \
$PYTHON-dev \
$PYTHON-wheel \
$PYTHON-mock \
$PYTHON-future \
$PYTHON-pip \
$PYTHON-yaml \
$PYTHON-h5py \
$PYTHON-setuptools && \
sudo apt-get clean && \
sudo rm -rf /var/lib/apt/lists/*
# MIOpen
sudo apt-get update && \
sudo apt-get install -y --allow-unauthenticated \
rocm-dkms rocm-dev rocm-libs \
rocm-device-libs \
hsa-ext-rocr-dev hsakmt-roct-dev hsa-rocr-dev \
rocm-opencl rocm-opencl-dev \
rocm-utils \
rocm-profiler cxlactivitylogger \
miopen-hip miopengemm \
sudo $PIP install six numpy wheel cython pillow
Finally, official ROCm-TensorFlow has registered to PyPI. (But Python3.6+ version still only from source build.)
pip3 install --user tensorflow-rocm
| - | TYPE | OS | Python | TensorFlow | Vega | RX5xx | Install |
|---|---|---|---|---|---|---|---|
| AMD Radeon | GPU | Ubuntu | 3.5 | latest | pip3 install tensorflow-rocm | ||
| AMD Radeon | GPU | Ubuntu | 3.6 | 1.11-rc1 | pip3 install http://install.aieater.com/gpueater/rocm/tensorflow-1.11.0rc1-cp36-cp36m-linux_x86_64.whl | ||
| AMD Radeon | GPU | Ubuntu | 3.6 | 1.10-latest | NG | pip3 install http://install.aieater.com/gpueater/rocm/tensorflow-1.10.0latest-cp36-cp36m-linux_x86_64.whl | |
| AMD Radeon | GPU | Ubuntu | 3.6 | 1.10-rc2 | NG | pip3 install http://install.aieater.com/gpueater/rocm/tensorflow-1.10.0rc2-cp36-cp36m-linux_x86_64.whl | |
| AMD Radeon | GPU | Ubuntu | 3.5 | 1.10-rc2 | NG | pip3 install http://install.aieater.com/gpueater/rocm/tensorflow-1.10.0rc2-cp35-cp35m-linux_x86_64.whl | |
| AMD Radeon | GPU | Ubuntu | 3.6 | 1.10-rc0 | NG | pip3 install http://install.aieater.com/gpueater/rocm/tensorflow-1.10.0rc0-cp36-cp36m-linux_x86_64.whl | |
| AMD Radeon | GPU | Ubuntu | 3.6 | 1.8.0 | NG | pip3 install http://install.aieater.com/gpueater/rocm/tensorflow-1.8.0-cp36-cp36m-linux_x86_64.whl | |
| AMD Radeon | GPU | Ubuntu | 2.7 | 1.8.0 | pip install http://repo.radeon.com/rocm/misc/tensorflow/tensorflow-1.8.0-cp27-cp27mu-manylinux1_x86_64.whl | ||
| AMD Radeon | GPU | Ubuntu | 3.5 | 1.8.0 | pip3 install http://repo.radeon.com/rocm/misc/tensorflow/tensorflow-1.8.0-cp35-cp35m-manylinux1_x86_64.whl | ||
| - | CPU | MacOSX | 3.7 | 1.10.1 | pip3 install https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.10.1-py3-none-any.whl | ||
| - | CPU | MacOSX | 2.7 | latest | pip install tensorflow | ||
| - | CPU | MacOSX | ~3.5 | latest | pip3 install tensorflow | ||
| - | CPU | Linux | 2.7 | latest | pip install tensorflow | ||
| - | CPU | Linux | ~3.5 | latest | pip3 install tensorflow | ||
| NVIDIA | GPU | Linux | ~3.5 | latest | pip3 install tensorflow-gpu | ||
| NVIDIA | GPU | Linux | 2.7 | latest | pip install tensorflow-gpu | ||
| ANY | GPU | Linux | 3.x | unstable | pip3 install tf-nightly-gpu | ||
| ANY | GPU | Linux | 2.x | unstable | pip install tf-nightly-gpu |
RX580 has something problem and unstable. (2018/10/2) Getting GPU name was mistaken as Ellesmere "[Radeon RX 470/480]". Vega64, 56, FE edition is stable on ROCm-1.9.211 + ROCm-TensorFlow1.8+
johndoe@gpueater.local:~/projects/models/tutorials/image/cifar10$ python3 cifar10_multi_gpu_train.py
Filling queue with 20000 CIFAR images before starting to train. This will take a few minutes.
2018-10-02 14:48:22.955238: W tensorflow/stream_executor/rocm/rocm_driver.cc:404] creating context when one is currently active; existing: 0x7fe4de1c9d30
2018-10-02 14:48:22.955859: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1451] Found device 0 with properties:
name: Ellesmere [Radeon RX 470/480]
AMDGPU ISA: gfx803
memoryClockRate (GHz) 1.38
pciBusID 0000:01:00.0
Total memory: 8.00GiB
Free memory: 7.75GiB
2018-10-02 14:48:22.955874: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1562] Adding visible gpu devices: 0
2018-10-02 14:48:22.955888: I tensorflow/core/common_runtime/gpu/gpu_device.cc:989] Device interconnect StreamExecutor with strength 1 edge matrix:
2018-10-02 14:48:22.955892: I tensorflow/core/common_runtime/gpu/gpu_device.cc:995] 0
2018-10-02 14:48:22.955895: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1008] 0: N
2018-10-02 14:48:22.955921: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1124] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 7539 MB memory) -> physical GPU (device: 0, name: Ellesmere [Radeon RX 470/480], pci bus id: 0000:01:00.0)
terminate called after throwing an instance of 'std::runtime_error'
what(): No device code available for function: _ZN7rocprim6detail19block_reduce_kernelILj256ELj4ELb0EfNS_18transform_iteratorIPfN10tensorflow10squareHalfIfEEfEES3_fN6hipcub3SumEEEvT3_mT4_T5_T6_
ROCm tensorflow-upstream (https://github.com/ROCmSoftwarePlatform/tensorflow-upstream)
mkdir -p ~/src
cd ~/src
BAZEL=0.15.0
TENSORFLOW_BRANCH=v1.10.0-rocm-rc2
rm -rf ~/.bazel ~/.cache/bazel
if test -e "bazel-$BAZEL-installer-linux-x86_64.sh"; then
echo "bazel-$BAZEL-installer-linux-x86_64.sh found."
else
echo "bazel-$BAZEL-installer-linux-x86_64.sh NOT found."
wget https://github.com/bazelbuild/bazel/releases/download/$BAZEL/bazel-$BAZEL-installer-linux-x86_64.sh
fi
chmod +x bazel-$BAZEL-installer-linux-x86_64.sh
./bazel-$BAZEL-installer-linux-x86_64.sh --user
source ~/.bazel/bin/bazel-complete.bash
export PATH=~/.bazel/bin:$PATH
sudo apt-get install -y openjdk-8-jdk
git clone https://github.com/ROCmSoftwarePlatform/tensorflow-upstream.git
cd tensorflow-upstream
git pull origin $TENSORFLOW_BRANCH
# ./build_rocm_python # 2.7
sudo pip3 uninstall -y tensorflow
./build_rocm_python3 & # 3.x
bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tensorflow_pkg
cp -f /tmp/tensorflow_pkg/* ~/src/
pip3 install ~/src/tensorflow*.whl
python3 -c "from tensorflow.python.client import device_lib;device_lib.list_local_devices()"
tensorflow-1.10.1 CPU 2.7, 3.3-3.6 GCC 4.8 Bazel 0.15.0 N/A N/A
tensorflow_gpu-1.10.1 GPU 2.7, 3.3-3.6 GCC 4.8 Bazel 0.15.0 7 9
tensorflow-1.9.0 CPU 2.7, 3.3-3.6 GCC 4.8 Bazel 0.11.0 N/A N/A
tensorflow_gpu-1.9.0 GPU 2.7, 3.3-3.6 GCC 4.8 Bazel 0.11.0 7 9
tensorflow-1.8.0 CPU 2.7, 3.3-3.6 GCC 4.8 Bazel 0.10.0 N/A N/A
tensorflow_gpu-1.8.0 GPU 2.7, 3.3-3.6 GCC 4.8 Bazel 0.9.0 7 9
python3 -c "from tensorflow.python.client import device_lib;device_lib.list_local_devices()"
2018-09-05 13:21:43.760601: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1520] Found device 0 with properties:
name: Vega [Radeon RX Vega]
AMDGPU ISA: gfx900
memoryClockRate (GHz) 1.63
pciBusID 0000:04:00.0
Total memory: 7.98GiB
Free memory: 7.73GiB
2018-09-05 13:21:43.760632: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1631] Adding visible gpu devices: 0
2018-09-05 13:21:43.760644: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1040] Device interconnect StreamExecutor with strength 1 edge matrix:
2018-09-05 13:21:43.760649: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1046] 0
2018-09-05 13:21:43.760653: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1059] 0: N
2018-09-05 13:21:43.760697: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1179] Created TensorFlow device (/device:GPU:0 with 7524 MB memory) -> physical GPU (device: 0, name: Vega [Radeon RX Vega], pci bus id: 0000:04:00.0)
johndoe@gpueater.local:~$ curl -O http://install.aieater.com/gpueater/rocm/gpueater-smi
% Total % Received % Xferd Average Speed Time Time Time Current
Dload Upload Total Spent Left Speed
100 45447 100 45447 0 0 1643k 0 --:--:-- --:--:-- --:--:-- 1643k
johndoe@gpueater.local:~$ chmod +x ./gpueater-smi
johndoe@gpueater.local:~$ ./gpueater-smi
==================== ROCm System Management Interface ====================
================================================================================
GPU Temp AvgPwr SCLK MCLK Fan Perf SCLK OD MCLK OD USED MEM
0 48c 4.0W 852Mhz 167Mhz 35.69% auto 0% 0% 7619MB
================================================================================
==================== End of ROCm SMI Log ====================
johndoe@gpueater.local:~$ mv gpueater-smi `which rocm-smi`
- tensorflow-rocm
- keras
- cython
- numpy
- moviepy
- requests
- sklearn
- cairocffi
- matplotlib
- editdistance
- pandas
- portpicker
- h5py
- PIL
- darkflow
- cv2
- jupyter
curl -sL http://install.aieater.com/setup_ml_submod | bash -
or
curl -O http://install.aieater.com/check_mod.py
python3 check_mod.py
chmod +x install.sh
./install.sh
https://s3-ap-northeast-1.amazonaws.com/gpueater/examples/deep_learning_yolo_v2.tar.gz
wget https://s3-ap-northeast-1.amazonaws.com/gpueater/examples/deep_learning_yolo_v2.tar.gz
tar xf deep_learning_yolo_v2.tar.gz
cd deep_learning_yolo_v2
python3 main.py image.jpg
References
https://s3-ap-northeast-1.amazonaws.com/gpueater/examples/deep_learning_yolo_v3.tar.gz
wget https://s3-ap-northeast-1.amazonaws.com/gpueater/examples/deep_learning_yolo_v3.tar.gz
tar xf deep_learning_yolo_v3.tar.gz
cd deep_learning_yolo_v3
python3 yolo.py image.jpg
References
https://hub.docker.com/r/gpueater/ubuntu16-rocm-1.9.211-tensorflow-1.11.0/
https://hub.docker.com/r/gpueater/rocm-tensorflow-1.8/
docker run -it --device=/dev/kfd --device=/dev/dri gpueater/ubuntu16-rocm-1.9.211-tensorflow-1.11.0
docker run -it --device=/dev/kfd --device=/dev/dri gpueater/rocm-tensorflow-1.8
OS: Ubuntu16.04.05+ Kernel: 4.15+ ROCm: 1.9.211+
* If you already used the GPUEater AMD GPU instance, the following command is not required.
sudo apt update
sudo apt upgrade -y
sudo apt install -y linux-generic-hwe-16.04
sudo reboot* If you already used the GPUEater AMD GPU instance, the following command is not required.
sudo apt install -y wget
wget -qO - http://repo.radeon.com/rocm/apt/debian/rocm.gpg.key | sudo apt-key add -
sudo sh -c 'echo deb [arch=amd64] http://repo.radeon.com/rocm/apt/debian/ xenial main > /etc/apt/sources.list.d/rocm.list'
sudo apt install -y libnuma-dev rocm-dkms
sudo usermod -a -G video $LOGNAME
ls -la /dev/kfd # AMD Kernel Fusion Driver
ls -la /dev/dri/ # Display and OpenCL file descriptors
https://docs.docker.com/install/linux/docker-ce/ubuntu/
docker run -it --device=/dev/kfd --device=/dev/dri gpueater/ubuntu16-rocm-1.9.211-tensorflow-1.11.0
/opt/rocm/opencl/bin/x86_64/clinfo
Number of platforms: 1
Platform Profile: FULL_PROFILE
Platform Version: OpenCL 2.1 AMD-APP.internal (2574.0)
Platform Name: AMD Accelerated Parallel Processing
Platform Vendor: Advanced Micro Devices, Inc.
Platform Extensions: cl_khr_icd cl_amd_object_metadata cl_amd_event_callback
Platform Name: AMD Accelerated Parallel Processing
Number of devices: 1
Device Type: CL_DEVICE_TYPE_GPU
Vendor ID: 1002h
Board name: Device 687f
Device Topology: PCI[ B#3, D#0, F#0 ]
Max compute units: 56
Max work items dimensions: 3
Max work items[0]: 1024
Max work items[1]: 1024
Max work items[2]: 1024
Max work group size: 256
Preferred vector width char: 4
Preferred vector width short: 2
Preferred vector width int: 1
Preferred vector width long: 1
Preferred vector width float: 1
Preferred vector width double: 1
Native vector width char: 4
Native vector width short: 2
Native vector width int: 1
Native vector width long: 1
Native vector width float: 1
Native vector width double: 1
Max clock frequency: 1622Mhz
Address bits: 64
Max memory allocation: 7287183769
Image support: Yes
Max number of images read arguments: 128
Max number of images write arguments: 8
Max image 2D width: 16384
Max image 2D height: 16384
Max image 3D width: 2048
Max image 3D height: 2048
Max image 3D depth: 2048
Max samplers within kernel: 26751
Max size of kernel argument: 1024
Alignment (bits) of base address: 1024
Minimum alignment (bytes) for any datatype: 128
Single precision floating point capability
Denorms: Yes
Quiet NaNs: Yes
Round to nearest even: Yes
Round to zero: Yes
Round to +ve and infinity: Yes
IEEE754-2008 fused multiply-add: Yes
Cache type: Read/Write
Cache line size: 64
Cache size: 16384
Global memory size: 8573157376
Constant buffer size: 7287183769
Max number of constant args: 8
Local memory type: Scratchpad
Local memory size: 65536
Max pipe arguments: 16
Max pipe active reservations: 16
Max pipe packet size: 2992216473
Max global variable size: 7287183769
Max global variable preferred total size: 8573157376
Max read/write image args: 64
Max on device events: 0
Queue on device max size: 0
Max on device queues: 0
Queue on device preferred size: 0
SVM capabilities:
Coarse grain buffer: Yes
Fine grain buffer: Yes
Fine grain system: No
Atomics: No
Preferred platform atomic alignment: 0
Preferred global atomic alignment: 0
Preferred local atomic alignment: 0
Kernel Preferred work group size multiple: 64
Error correction support: 0
Unified memory for Host and Device: 0
Profiling timer resolution: 1
Device endianess: Little
Available: Yes
Compiler available: Yes
Execution capabilities:
Execute OpenCL kernels: Yes
Execute native function: No
Queue on Host properties:
Out-of-Order: No
Profiling : Yes
Queue on Device properties:
Out-of-Order: No
Profiling : No
Platform ID: 0x7f248a35f270
Name: gfx900
Vendor: Advanced Micro Devices, Inc.
Device OpenCL C version: OpenCL C 2.0
Driver version: 2574.0 (HSA1.1,LC)
Profile: FULL_PROFILE
Version: OpenCL 1.2
Extensions: cl_khr_fp64 cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics cl_khr_local_int32_base_atomics cl_khr_local_int32_extended_atomics cl_khr_int64_base_atomics cl_khr_int64_extended_atomics cl_khr_3d_image_writes cl_khr_byte_addressable_store cl_khr_fp16 cl_khr_gl_sharing cl_amd_device_attribute_query cl_amd_media_ops cl_amd_media_ops2 cl_khr_subgroups cl_khr_depth_images cl_amd_copy_buffer_p2p cl_amd_assembly_program - GPUEater ROCM-Tensorflow installation https://www.gpueater.com/help
- GPUEater github ROCm-Tensorflow information https://github.com/aieater/rocm_tensorflow_info
- GPUEater github ROCm-PyTorch information https://github.com/aieater/rocm_pytorch_informations
- GPUEater github ROCm-Caffe information https://github.com/aieater/rocm_caffe_informations
- ROCm+DeepLearning libraries https://rocm-documentation.readthedocs.io/en/latest/Deep_learning/Deep-learning.html
- ROCm github https://github.com/RadeonOpenCompute/ROCm
- ROCm-TensorFlow on Docker https://hub.docker.com/r/rocm/tensorflow/