I have updated my CUDA toolkit version to 11.4. When I try to migrate any CUDA code to DPC++ using DPCT tool, I get the following error:
dpct exited with code: -5 (Error: Path for CUDA header files is invalid or not available. Specify with --cuda-include-path)
I have even specified the cuda-include-path flag but the error still persists. I'm I missing something?
Environment:
OS: CentOS 8
oneAPI base tookit version: 2021.3
DPCT tool does not support CentOS version 8. You can try using any of the supported versions of OS for DPCT migration.
Refer to the below link for the supported OS and their versions.
https://software.intel.com/content/www/us/en/develop/articles/intel-dpc-compatibility-tool-system-requirements.html
Related
When I run a process that uses paddle, an error occured:
W1206 13:55:49.811826 22388 device_context.cc:447] Please NOTE:
device: 0, GPU Compute Capability: 6.1, Driver API Version: 11.5,
Runtime API Version: 10.2 W1206 13:55:49.812117 22388
dynamic_loader.cc:287] The third-party dynamic library (libcudnn.so)
that Paddle depends on is not configured correctly. (error code is
/usr/local/cuda/lib64/libcudnn.so: cannot open shared object file: No
such file or directory) Suggestions:
Check if the third-party dynamic library (e.g. CUDA, CUDNN) is installed correctly and its version is matched with paddlepaddle you
installed.
Configure third-party dynamic library environment variables as follows:
Linux: set LD_LIBRARY_PATH by export LD_LIBRARY_PATH=...
Windows: set PATH by `set PATH=XXX;
doesn't have a clue what is Runtime API Version and how to upgrade it to 11.5 (as same as Driver API Version).Any help would be appreciated~
os:
ubuntu 18.04
nvidia-smi:
NVIDIA-SMI 495.44 Driver Version: 495.44 CUDA Version: 11.5
I am getting desperate with Chainer because I'm not able to use it with GPU for about a week now. The error I am getting:
RuntimeError: CUDA environment is not correctly set up (see https://github.com/chainer/chainer#installation).No module named 'cupy.util'
Code to reproduce:
import chainer
chainer.cuda.to_gpu([0, 0])
Output of chainer.backends.cuda.available is False.
Working on Ubuntu 20.04 (I know, it is not the one from the recommended on Chainer's docs) inside WSL2. CUDA drivers 11.0. Output of nvcc -V:
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2020 NVIDIA Corporation
Built on Wed_Jul_22_19:09:09_PDT_2020
Cuda compilation tools, release 11.0, V11.0.221
Build cuda_11.0_bu.TC445_37.28845127_0
CUDA samples compile and work properly inside WSL2.
According to pip freeze, cupy-cuda110 is installed within an (activated) virtual environment (but not detected, it seems). Chainer version 7.7.0 is installed.
Any ideas how to fix it?
Solution from https://github.com/chainer/chainer/issues/8582 did not seem to do the trick for me.
The error message is very clear. Just change L69 of backends/cuda.py:
from cupy.util import PerformanceWarning as _PerformanceWarning
to
from cupy._util import PerformanceWarning as _PerformanceWarning
along with the solution from #8582, everything will work just fine.
I am trying to build tensorflow from source on a remote server (with no superuser privileges) because I got this error when I simply installed with pip:
Loaded runtime CuDNN library: 7.1.2 but source was compiled with: 7.4.2. CuDNN library major and minor version needs to match or have higher minor version in case of CuDNN 7.0 or later version. If using a binary install, upgrade your CuDNN library. If building from sources, make sure the library loaded at runtime is compatible with the version specified during compile configuration.
I completed all the steps listed here successfully, but I still get the same error as above, despite setting CudNN version as 7.1.2 before building.
Is there any way I can see the configurations to verify that they have been set properly?
A file is generated after running ./configure with the name .tf_configure.bazelrc you can inspect that file.
I am currently getting and build failed error. Tried uninstalling android studios, uninstall and reinstall java but to no avail. Appreciate any advice here. Thank you.
FAILURE: Build failed with an exception.
What went wrong:
Execution failed for task ':app:greendao'.
Found 4 problem(s) parsing "/xxx/android/app/src/main/java/com/eatsy/printer/Printer.java". First problem:
Pb(324) The type java.lang.Object cannot be resolved. It is indirectly referenced from required .class files (16777540 at line 1).
Android Studio 3.2
Build #AI-181.5540.7.32.5014246, built on September 18, 2018
JRE: 1.8.0_152-release-1136-b06 x86_64
JVM: OpenJDK 64-Bit Server VM by JetBrains s.r.o
macOS 10.13.6
Please use Oracle JDK. OpenJDK has some issues with greenDAO. for me OracleJDK works perfect.
To install OracleJDK please follow the instructions in this link.
i have installed tideSDK 1.3.1-beta on my machine
File path is "user/.tidesdk"..
then tried to install tideSDK developer 1.4.2 i got following error message.
Couldn't load file:/home/mareeswari/TideSDK-Developer-1.4.2-linux-x86/runtime/1.3.1-beta/libtide.so, error: /usr/lib/libstdc++.so.6: version `GLIBCXX_3.4.15' not found (required by /home/mareeswari/TideSDK-Developer-1.4.2-linux-x86/runtime/1.3.1-beta/libtide.so)
This is a valid crash. Its because TideSDK does not support fedora / redhat family yet. The underlying binaries are compiled for Ubuntu.
I've successfully got Tide Developer working on Fedora 18.
I had a similar issue to you, however it was complaining about libpng12, so installed the libpng12 and libpng12-devel and it worked fine.
Hope this helps someone