Is there a way of creating a dummy sound card on an EC2 instance?
Unable to find snd-dummy, or any other other snd-modules using modprobe.
sudo apt-get install linux-generic, also didn't exactly help.
My goal is to run alsa with a dummy sound card.
lscpi output:
00:00.0 Host bridge: Intel Corporation 440FX - 82441FX PMC [Natoma] (rev 02)
00:01.0 ISA bridge: Intel Corporation 82371SB PIIX3 ISA [Natoma/Triton II]
00:01.1 IDE interface: Intel Corporation 82371SB PIIX3 IDE [Natoma/Triton II]
00:01.3 Bridge: Intel Corporation 82371AB/EB/MB PIIX4 ACPI (rev 01)
00:02.0 VGA compatible controller: Cirrus Logic GD 5446
00:03.0 Unassigned class [ff80]: XenSource, Inc. Xen Platform Device (rev 01)
uname output:
Linux 5.4.0-1037-aws
lsb_release -a output:
No LSB modules are available.
Distributor ID: Ubuntu
Description: Ubuntu 18.04.5 LTS
Release: 18.04
Codename: bionic
Any help would be greatly appreciated.
I am trying to cross compile(for ARM64) DPDK from source as instructed here:
https://doc.dpdk.org/guides/linux_gsg/cross_build_dpdk_for_arm64.html
But when I run make, I see this:
$ make config T=arm64_armv8_linux_gcc
make: Nothing to be done for 'config'.
I have the checkout the main branch, and wondering if compiling through "Makefile" is not supported any more and MESON build system has replaced it ?
I am on top commit of master branch:
https://github.com/DPDK/dpdk/commit/9d620630ea30386d7fc2ff192656a9051b6dc6b5
DPDK version:
21.02.0-rc0
Toolchain version is:
aarch64-linux-gnu-gcc --version
aarch64-linux-gnu-gcc (Linaro GCC 7.3-2018.05) 7.3.1 20180425 [linaro- 7.3-2018.05 revision d29120a424ecfbc167ef90065c0eeb7f91977701]
Host machine details are:
$ lsb_release -a
No LSB modules are available.
Distributor ID: Ubuntu
Description: Ubuntu 16.04.7 LTS
Release: 16.04
Codename: xenial
DPDK has removed the support for Makefile from 20.11. One has to rely on meson-ninja for the same.
Please use the below as guide for your cross build
meson arm64-build --cross-file config/arm/arm64_armv8_linux_gcc
ninja -C arm64-build
DPDK LTS 19.11.6 still uses Makefile.
I get the following error when l run tensorflow in GPU.
2018-09-15 18:56:51.011724: E tensorflow/core/common_runtime/direct_session.cc:158] Internal: cudaGetDevice() failed. Status: CUDA driver version is insufficient for CUDA runtime version
Traceback (most recent call last):
File "evaluate_sample.py", line 160, in <module>
tf.app.run(main)
File "/anaconda3/envs/tf/lib/python2.7/site-packages/tensorflow/python/platform/app.py", line 125, in run
_sys.exit(main(argv))
File "evaluate_sample.py", line 123, in main
with tf.Session() as sess:
File "/anaconda3/envs/tf/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 1494, in __init__
super(Session, self).__init__(target, graph, config=config)
File "/anaconda3/envs/tf/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 626, in __init__
self._session = tf_session.TF_NewSession(self._graph._c_graph, opts)
tensorflow.python.framework.errors_impl.InternalError: Failed to create session.
Where do the following errors come from ?
E tensorflow/core/common_runtime/direct_session.cc:158] Internal: cudaGetDevice() failed. Status: CUDA driver version is insufficient for CUDA runtime version
and
tensorflow.python.framework.errors_impl.InternalError: Failed to create session.
Such tha my version of :
tensorflow is : 1.10
cat /proc/driver/nvidia/version
NVRM version: NVIDIA UNIX x86_64 Kernel Module 390.77 Tue Jul 10 18:28:52 PDT 2018
GCC version: gcc version 7.3.0 (Debian 7.3.0-28)
nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2016 NVIDIA Corporation
Built on Sun_Sep__4_22:14:01_CDT_2016
Cuda compilation tools, release 8.0, V8.0.44
Updating nvidia driver solved this issue.
You can check your cuda toolkit compatiblity here. Then update your nvidia driver by downloading it from here.
The reason for this error is the mismatch of your installed Cuda Toolkit version and the version of the python package cudatoolkit, which is usually installed as dependency of tensorflow-gpu.
In order to fix this you have to first match your tensorflow version with your installed Cuda Toolkit version like shown here
Then you have to check the version of your cudatoolkit package. This have to match major and minor version, so e.g. if you have Cuda Toolkit 9.0 installed and cudatoolkit9_1 is installed you need to downgrade to cudatoolkit9 via your python.
In the case I just solved, it was updating the GPU driver to the latest and installing the cuda toolkit. Your error is telling you your CUDA driver version is too old. I believe the nvcc version we were seeing was 7.5, and you have 7.3.
I think all you will have to do is: sudo apt install nvidia-cuda-toolkit then reboot.
Below are the steps I took for the problem where the libcuda.so.1 file could not be found.
First, the ppa was added and a newer GPU driver installed:
sudo add-apt-repository ppa:graphics-drivers/ppa
sudo apt update
sudo apt install nvidia-390
After adding the ppa, it showed options for driver versions, and 390 was the latest 'stable' version that was shown.
Then install the cuda toolkit:
sudo apt install nvidia-cuda-toolkit
Then reboot:
sudo reboot
It updated the drivers to a newer version than the 390 originally installed in the first step (it was 410; this was a p2.xlarge instance on AWS).
Just update your nvidia drivers and it will solve the issue
Same problem. Solved updating nvidia driver, because a I was using tensorflow 2.1 and it requires updated driver. Soo, I was using 390 and updated to 435, through Ubuntu's software manager.
Upgrading to Tensorflow 2.6.0 Solved my issue.
pip install --upgrade TensorFlow
For Ubuntu 18.04 and Tensorflow 1.13.1
First make sure system is up to data:
sudo apt update
sudo apt dist-upgrade
sudo reboot now
Install later drivers:
sudo add-apt-repository ppa:graphics-drivers/ppa
Open Software & Updates and select the Additional Drivers tab:
Select the nvidia-driver-396 and click Apply Changes
Now reboot:
sudo reboot now
To verify which that NVIDIA driver 396 active:
nvidia-smi
I'm doing a crossbuild of a QT app from a Debian (Stretch) PC to a Debian (Jessie) BeagleBone Black, and when I executed this, I got the message
/home/bbuser/totemguard/totemguard: /usr/lib/arm-linux-gnueabihf/libstdc++.so.6: version `GLIBCXX_3.4.22' not found (required by /home/bbuser/totemguard/totemguard)
I saw that the armhf g++ version was 6.1 so I install the 4.9.2-10 (the same that I had on the BeagleBone Black) and recompiled my code, with similar result (different GLIBXX version):
/home/bbuser/totemguard/totemguard: /usr/lib/arm-linux-gnueabihf/libstdc++.so.6: version `GLIBCXX_3.4.21' not found (required by /home/bbuser/totemguard/totemguard)
Reading the ABI Policy and Guidelines, the G++ version for GLIBCXX_3.4.21 is 5.1.0:
GCC 4.9.0: GLIBCXX_3.4.20, CXXABI_1.3.8
GCC 5.1.0: GLIBCXX_3.4.21, CXXABI_1.3.9
GCC 6.1.0: GLIBCXX_3.4.22, CXXABI_1.3.10
But I never had the 5.1 version installed on my host PC or BeagleBone Black board.
Listing the /usr/lib/arm-linux-gnueabihf/ directory we can see that there are only the GCC 4.9.0 and GCC 6.1.0 libstdc++ version:
lrwxrwxrwx 1 root root 19 ago 3 15:53 libstdc++.so.6 -> libstdc++.so.6.0.22
-rw-r--r-- 1 root root 658064 dic 27 2014 libstdc++.so.6.0.20
-rw-r--r-- 1 root root 1019632 ago 3 15:53 libstdc++.so.6.0.22
This problem begin after a distro-upgrade from jessie to stretch, and I can't upgrade the beaglebone black gcc version.
What can I do?
EDIT 1:
On a test board (BeagleBone Black) I added the stretch repository and did this:
bbuser#beaglebone:~/totemguard$ sudo apt-cache policy libstdc++6
libstdc++6:
Installed: 4.9.2-10
Candidate: 6.1.1-11
Version table:
6.1.1-11 0
500 http://ftp.us.debian.org/debian/ stretch/main armhf Packages
*** 4.9.2-10 0
500 http://ftp.us.debian.org/debian/ jessie/main armhf Packages
100 /var/lib/dpkg/status
bbuser#beaglebone:~/totemguard$ sudo apt-get install libstdc++6
Reading package lists... Done
Building dependency tree
Reading state information... Done
The following extra packages will be installed:
gcc-6-base
The following NEW packages will be installed:
gcc-6-base
The following packages will be upgraded:
libstdc++6
1 upgraded, 1 newly installed, 0 to remove and 726 not upgraded.
Need to get 517 kB of archives.
...
And the application ran fine (not 100% tested, but give no errors). Still this is a test board and I cant do the same on a production board.
solution 1) use -static (full libraries) or compile-in only libstdc++ as static to the binary
solution 2) distribute the appropriate libstdc++ version with the binary (possibly using LD_PRELOAD)
solution 3) use exactly the same g++ libstdc++ version for crosscompiling (at least matching)
usually better is to use solution 1) - you will have no problems across distros upgrade
I am trying to install CUDA on my Mac Pro (15-inch, Mid 2009 with GPU GeForce 9400M).
I have installed from https://developer.nvidia.com/cuda-downloads the toolkit.
nvcc --version returns: ... Cuda compilation tools, release 7.5, V7.5.19
I have installed directly the driver from the package, then from http://www.nvidia.com/object/mac-driver-archive.html. Then from System Preferences > CUDA Preferences, I can see CUDA Driver Version: 7.5.25 (though the update 6.5.51 is proposed (?)).
I can compile a sample (0_Simple/asyncAPI). When I launch it, I get:
[./asyncAPI] - Starting...
CUDA error at ../../common/inc/helper_cuda.h:1111
code=35(cudaErrorInsufficientDriver)
"cudaGetDeviceCount(&device_count)"
Why this error??
The CUDA 7 release cycle removed support for compute capability 1.x devices on all platforms. This includes your Geforce 9400M.
The last version with support of those devices was CUDA 6.5. You will need to work out what XCode version will work with that CUDA toolkit and your OS version and install that instead.
[This answer assembled from comments as a community wiki entry to get this question off the unanswered queue for the CUDA tag].