Hi.
I have a freshly unboxed Jetson TX1, successfully flashed this afternoon
with JetPack 2.3. Python 2.7.12 and Theano 0.9.0.dev are also freshly
installed, using the TX1 install instructions from here:
http://deeplearning.net/software/theano/install_ubuntu.html
I've been trying to get the GPU test script working from here, with no
success:
http://deeplearning.net/software/theano_versions/dev/tutorial/using_gpu.html
The command that works best is:
THEANO_FLAGS=device=gpu python gpu_tutorial1.py
The result, however, is a lengthy series of warnings and ultimately an
execution on the CPU rather than the GPU:
Using gpu device 0: NVIDIA Tegra X1 (CNMeM is disabled, cuDNN 5105)
WARNING (theano.gof.cmodule): OPTIMIZATION WARNING: Theano was not able to
find the default g++ parameters. This is needed to tune the compilation to
your specific CPU. This can slow down the execution of Theano functions.
Please submit the following lines to Theano's mailing list so that we can
fix this problem:
['# 1 "<stdin>"\n', '# 1 "<built-in>"\n', '# 1 "<command-line>"\n', '# 1
"/usr/include/stdc-predef.h" 1 3 4\n', '# 1 "<command-line>" 2\n', '# 1
"<stdin>"\n', 'Using built-in specs.\n', 'COLLECT_GCC=/usr/bin/g++\n',
'Target: aarch64-linux-gnu\n', "Configured with: ../src/configure -v
--with-pkgversion='Ubuntu/Linaro 5.4.0-6ubuntu1~16.04.2'
--with-bugurl=file:///usr/share/doc/gcc-5/README.Bugs
--enable-languages=c,ada,c++,java,go,d,fortran,objc,obj-c++ --prefix=/usr
--program-suffix=-5 --enable-shared --enable-linker-build-id
--libexecdir=/usr/lib --without-included-gettext --enable-threads=posix
--libdir=/usr/lib --enable-nls --with-sysroot=/ --enable-clocale=gnu
--enable-libstdcxx-debug --enable-libstdcxx-time=yes
--with-default-libstdcxx-abi=new --enable-gnu-unique-object
--disable-libquadmath --enable-plugin --with-system-zlib
--disable-browser-plugin --enable-java-awt=gtk --enable-gtk-cairo
--with-java-home=/usr/lib/jvm/java-1.5.0-gcj-5-arm64/jre --enable-java-home
--with-jvm-root-dir=/usr/lib/jvm/java-1.5.0-gcj-5-arm64
--with-jvm-jar-dir=/usr/lib/jvm-exports/java-1.5.0-gcj-5-arm64
--with-arch-directory=aarch64
--with-ecj-jar=/usr/share/java/eclipse-ecj.jar --enable-multiarch
--enable-fix-cortex-a53-843419 --disable-werror --enable-checking=release
--build=aarch64-linux-gnu --host=aarch64-linux-gnu
--target=aarch64-linux-gnu\n", 'Thread model: posix\n', 'gcc version 5.4.0
20160609 (Ubuntu/Linaro 5.4.0-6ubuntu1~16.04.2) \n',
"COLLECT_GCC_OPTIONS='-E' '-v' '-shared-libgcc' '-mlittle-endian'
'-mabi=lp64'\n", ' /usr/lib/gcc/aarch64-linux-gnu/5/cc1 -E -quiet -v
-imultiarch aarch64-linux-gnu - -mlittle-endian -mabi=lp64
-fstack-protector-strong -Wformat -Wformat-security\n', 'ignoring
nonexistent directory "/usr/local/include/aarch64-linux-gnu"\n', 'ignoring
nonexistent directory
"/usr/lib/gcc/aarch64-linux-gnu/5/../../../../aarch64-linux-gnu/include"\n',
'#include "..." search starts here:\n', '#include <...> search starts
here:\n', ' /usr/lib/gcc/aarch64-linux-gnu/5/include\n', '
/usr/local/include\n', ' /usr/lib/gcc/aarch64-linux-gnu/5/include-fixed\n',
' /usr/include/aarch64-linux-gnu\n', ' /usr/include\n', 'End of search
list.\n',
'COMPILER_PATH=/usr/lib/gcc/aarch64-linux-gnu/5/:/usr/lib/gcc/aarch64-linux-gnu/5/:/usr/lib/gcc/aarch64-linux-gnu/:/usr/lib/gcc/aarch64-linux-gnu/5/:/usr/lib/gcc/aarch64-linux-gnu/\n',
'LIBRARY_PATH=/usr/lib/gcc/aarch64-linux-gnu/5/:/usr/lib/gcc/aarch64-linux-gnu/5/../../../aarch64-linux-gnu/:/usr/lib/gcc/aarch64-linux-gnu/5/../../../../lib/:/lib/aarch64-linux-gnu/:/lib/../lib/:/usr/lib/aarch64-linux-gnu/:/usr/lib/../lib/:/usr/lib/gcc/aarch64-linux-gnu/5/../../../:/lib/:/usr/lib/\n',
"COLLECT_GCC_OPTIONS='-E' '-v' '-shared-libgcc' '-mlittle-endian'
'-mabi=lp64'\n"]
[Elemwise{exp,no_inplace}(<TensorType(float64, vector)>)]
Looping 1000 times took 12.813382 seconds
Result is [ 1.23178032 1.61879341 1.52278065 ..., 2.20771815 2.29967753
1.62323285]
Used the cpu
A better formatted version of this question can be found at Stack Overflow:
http://stackoverflow.com/questions/39552515/theano-gpu-usage-on-a-new-jetson-tx1
Does anyone know why the TX1 is stubbornly executing this on the GPU rather
than the CPU?
And is this the appropriate mailing list to report the warning as directed?
If not, can someone kindly tell me what the right list is?
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