How to compile for AMD GPU?

[Whytehorse]

what options need to be selected when running ./configure in tensorflow-opencl directory? Here's where I'm not sure what to enter in order to get tensorflow to recognize and use the AMD GPU/APU.
`~/tensorflow-opencl ~/tensorflow-opencl
Please specify the location of python. [Default is /usr/bin/python]: /usr/bin/python3
Do you wish to build TensorFlow with Google Cloud Platform support? [y/N]
No Google Cloud Platform support will be enabled for TensorFlow
Do you wish to build TensorFlow with Hadoop File System support? [y/N]
No Hadoop File System support will be enabled for TensorFlow
Found possible Python library paths:
/usr/lib/python3/dist-packages
Please input the desired Python library path to use. Default is [/usr/lib/python3/dist-packages]

Using python library path: /usr/lib/python3/dist-packages
Do you wish to build TensorFlow with OpenCL support? [y/N] y
OpenCL support will be enabled for TensorFlow
Do you wish to build TensorFlow with CUDA support? [y/N] y
CUDA support will be enabled for TensorFlow
Please specify which gcc should be used by nvcc as the host compiler. [Default is /usr/bin/gcc]:
Please specify the CUDA SDK version you want to use, e.g. 7.0. [Leave empty to use system default]:
`

[lukeiwanski]

Hi @Whytehorse do you intend to run TensorFlow supporting OpenCL and CUDA at the same time? We did not test that yet. Although, I don't see any reason why it wouldn't work.

In order to start using TF with OpenCL only you need to say no to CUDA.
As well, you will need to get ComputeCpp compiler (https://www.codeplay.com/products/computesuite/computecpp).

~/tensorflow-opencl ~/tensorflow-opencl
Please specify the location of python. [Default is /usr/bin/python]: 
Do you wish to build TensorFlow with Google Cloud Platform support? [y/N] 
No Google Cloud Platform support will be enabled for TensorFlow
Do you wish to build TensorFlow with Hadoop File System support? [y/N] 
No Hadoop File System support will be enabled for TensorFlow
Found possible Python library paths:
  /usr/local/lib/python2.7/dist-packages
  /usr/lib/python2.7/dist-packages
Please input the desired Python library path to use.  Default is [/usr/local/lib/python2.7/dist-packages]
Using python library path: /usr/local/lib/python2.7/dist-packages
Do you wish to build TensorFlow with OpenCL support? [y/N] y
OpenCL support will be enabled for TensorFlow
Do you wish to build TensorFlow with CUDA support? [y/N] 
No CUDA support will be enabled for TensorFlow
Please specify which C++ compiler should be used as the host C++ compiler. [Default is ]: /usr/bin/clang++
Please specify which C compiler should be used as the host C compiler. [Default is ]: /usr/bin/clang
Please specify the location where ComputeCpp for SYCL 1.2 is installed. [Default is /usr/local/computecpp]: <ADD PATH TO COMPUTECPP ROOT HERE>

What AMD GPU/APU do you use?

[Whytehorse]

I've got the A10-7850(Kaveri), aka steamroller. I already got ComputeCpp. I already compiled successfully using ComputeCpp and OpenCL. My graphics driver shows OpenCL 1.2 is supported. When I run the compiled binary, it doesn't use the GPU at all, only CPU.

$clinfo
  Profiling :					 No
  Platform ID:					 0x7f3b1feffbd8
  Name:						 AMD A10-7850K APU with Radeon(TM) R7 Graphics
  Vendor:					 AuthenticAMD
  Device OpenCL C version:			 OpenCL C 1.2 
  Driver version:				 2117.10 (sse2,avx,fma4)
  Profile:					 FULL_PROFILE
  Version:					 OpenCL 1.2 AMD-APP (2117.10)
  Extensions:					 cl_khr_fp64 cl_amd_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_gl_sharing cl_ext_device_fission cl_amd_device_attribute_query cl_amd_vec3 cl_amd_printf cl_amd_media_ops cl_amd_media_ops2 cl_amd_popcnt cl_khr_spir cl_khr_gl_event 

[lukeiwanski]

Could you provide the output of computecpp_info ?

[Whytehorse]

---

ComputeCpp Info (CE 0.1.1)

---

Toolchain information:

GLIBCXX: 20150426
This version of libstdc++ is supported.

---

Device Info:

Discovered 1 devices matching:
platform :
device type :

---

Device 0:

Device is supported : NO - Unsupported vendor
CL_DEVICE_NAME : Spectre
CL_DEVICE_VENDOR : Advanced Micro Devices, Inc.
CL_DRIVER_VERSION : 2117.10 (VM)
CL_DEVICE_TYPE : CL_DEVICE_TYPE_GPU

---

[lukeiwanski]

computecpp_info looks good.
Could you provide the output of your binary too?

[Whytehorse]

What binary?

[lukeiwanski]

The binary that states your GPU is not used at all that you mentioned earlier:

When I run the compiled binary, it doesn't use the GPU at all, only CPU.

Does it output any information?
How do you know it works only on CPU?
Did you run your model with sess = tf.Session(config=tf.ConfigProto(log_device_placement=True)) ?

[Whytehorse]

I run this:

import tensorflow as tf
# Creates a graph.
a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')
b = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[3, 2], name='b')
c = tf.matmul(a, b)
# Creates a session with log_device_placement set to True.
sess = tf.Session(config=tf.ConfigProto(log_device_placement=True))
# Runs the op.
print sess.run(c)

and I get this:
Device mapping: no known devices.
I tensorflow/core/common_runtime/direct_session.cc:255] Device mapping:

MatMul: (MatMul): /job:localhost/replica:0/task:0/cpu:0
I tensorflow/core/common_runtime/simple_placer.cc:827] MatMul: (MatMul)/job:localhost/replica:0/task:0/cpu:0
b: (Const): /job:localhost/replica:0/task:0/cpu:0
I tensorflow/core/common_runtime/simple_placer.cc:827] b: (Const)/job:localhost/replica:0/task:0/cpu:0
a: (Const): /job:localhost/replica:0/task:0/cpu:0
I tensorflow/core/common_runtime/simple_placer.cc:827] a: (Const)/job:localhost/replica:0/task:0/cpu:0
[[ 22.  28.]
 [ 49.  64.]]

[Whytehorse]

FYI here is a working build command for my cpu:
bazel build --local_resources 2048,.5,1.0 --copt=-march=bdver3 -c opt //tensorflow/tools/pip_package:build_pip_package

[lukeiwanski]

We are still working on MatMul Op but you can try it out: lukeiwanski@d04d4d2.

[Whytehorse]

what's a good test to verify that opencl is working in tensorflow and using my gpu?

[lukeiwanski]

Have a look at: https://github.com/benoitsteiner/tensorflow-opencl/blob/master/tensorflow/python/kernel_tests/basic_gpu_test.py

If the following line passes for you that means your GPU is working with TensorFlow:
bazel test -c opt --config=sycl --verbose_failures --test_timeout 3600 //tensorflow/python/kernel_tests:basic_gpu_test

[Whytehorse]

		fail("ERROR: Building with --config=s...")
ERROR: Building with --config=sycl but TensorFlow is not configured to build with SYCL support. Please re-run ./configure and enter 'Y' at the prompt to build with SYCL support.

I didn't see sycl support, only ComputeCpp and OpenCL and I specified those so... ?

[lukeiwanski]

That's a good point, perhaps we should include a better explanation on what SYCL is and how it relates to OpenCL.

Have you tried following these instructions? https://github.com/lukeiwanski/tensorflow-opencl/blob/cd5861c4defe3182122276fdbbb371f60ea5b708/tensorflow/g3doc/get_started/os_setup.md#create-the-pip-package-and-install

Your example from earlier should now work ( Matmul Op should run on GPU via SYCL / OpenCL ) with the head of this repo ( after this #33 gets in that is :) ).

[Whytehorse]

I re-ran ./configure and then ran the test and I get that it passed:

//tensorflow/python/kernel_tests:basic_gpu_test                          PASSED in 49.2s

Executed 1 out of 1 test: 1 test passes.