I've some experience on Debian based distribution. There I've never had difficulties to install software like emacs and mercurial which I believe are quite standard packages in Linux OSes. Now I have a new laptop with Suse Enterprise. It seems that neither emacs nor mercurial are found in the list of installable packages...
I believe that I have to add some repository to zipper... So this is my actual list of repositories:
> zypper repos
# | Alias | Nome | abilitato | Attualizza
--+---------------------------------------------------+---------------------------------------------------+-----------+-----------
1 | HP-SBSO-Emergency-Channel | HP-SBSO-Emergency-Channel | Sì | Sì
2 | SUSE-Linux-Enterprise-Desktop-11-SP1 11.1.1-1.133 | SUSE-Linux-Enterprise-Desktop-11-SP1 11.1.1-1.133 | Sì | Sì
3 | hd-889c0513 | SuSE-Linux-Updates | Sì | Sì
4 | hd-aeb4361a | SuSE-Linux-Maintenance-Updates | Sì | Sì
I found many repository lists but don't understand how to add any of them (a HREF to a .repo seems needed). Any help would be appreciated.
On SLE11, emacs is in the SLE11-SP1-Updates repository
Repository: SLES11-SP1-Updates
Name: emacs
Version: 22.3-4.36.1
Arch: x86_64
Hersteller: SUSE LINUX Products GmbH, Nuernberg, Germany
Support Level: Level 3
Installiert: Nein
Status: nicht installiert
Installierte Größe: 48,9 MiB
Zusammenfassung: GNU Emacs Base Package
Beschreibung:
Basic package for the GNU Emacs editor. Requires emacs-x11 or
emacs-nox.
And mercurial is in the SDK repository:
Repository: SLE11-SDK-SP1-Pool
Name: mercurial
Version: 1.0.2-27.32
Arch: x86_64
Hersteller: SUSE LINUX Products GmbH, Nuernberg, Germany
Support Level: Unbekannt
Installiert: Nein
Status: nicht installiert
Installierte Größe: 2,8 MiB
Zusammenfassung: Scalable Distributed SCM
Beschreibung:
Mercurial is a fast, lightweight source control management system
designed for efficient handling of very large distributed projects.
Get the SDK dvd from suse.com (login required)
You add repositories either via "zypper ar" or via yast.
You can only get update repositories if you have a valid subscription with SUSE.
Related
How can I find where CUDA 11.x for PyTorch-GPU 1.13 get installed on Windows 10 on my computer?
What I tried:
I installed the NVIDIA CUDA drivers and toolkit for Windows from the NVIDIA website. I can verify this by typing: !nvidia-smi in Jupyter Lab, which gives me the following output. This indicates that the CUDA tools are installed, but not being used by my PyTorch package. I need to find out what version of CUDA drivers are installed so I can install the correct PyTorch-GPU package.
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 513.63 Driver Version: 513.63 CUDA Version: 11.6 |
|-------------------------------+----------------------+----------------------+
| GPU Name TCC/WDDM | Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 Quadro P2000 WDDM | 00000000:01:00.0 Off | N/A |
| N/A 46C P8 N/A / N/A | 0MiB / 4096MiB | 1% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| No running processes found |
+-----------------------------------------------------------------------------+
I find many Ubuntu questions and answers for locating CUDA to add it to my PATH, but nothing specific for Windows 10.
For example:
Pytorch CUDA installation fails,
Pytorch CUDA installation using conda,
pytorch-says-that-cuda-is-not-available
What are the equivalent Python commands on Windows 10 to locate the CUDA 11.x toolkits and driver version that my PyTorch-GPU package must use? And then how to fix the problem if PyTorch is out of sync?
I am answering my own question here...
PyTorch-GPU must be compiled against specific CUDA binary drivers.
I finally found this hint Why torch.cuda.is_available() returns False even after installing pytorch with cuda? which identifies the issue.
import torch
torch.zeros(1).cuda()
The return value clearly identifies the problem.
AssertionError Traceback (most recent call last)
Cell In [222], line 2
1 import torch
----> 2 torch.zeros(1).cuda()
File C:\ProgramData\Anaconda3\envs\tf210_gpu\lib\site-packages\torch\cuda\__init__.py:221, in _lazy_init()
217 raise RuntimeError(
218 "Cannot re-initialize CUDA in forked subprocess. To use CUDA with "
219 "multiprocessing, you must use the 'spawn' start method")
220 if not hasattr(torch._C, '_cuda_getDeviceCount'):
--> 221 raise AssertionError("Torch not compiled with CUDA enabled")
222 if _cudart is None:
223 raise AssertionError(
224 "libcudart functions unavailable. It looks like you have a broken build?")
AssertionError: Torch not compiled with CUDA enabled
The problem is: "Torch not compiled with CUDA enabled"
Now I have to see if I can just re-install PyTorch-GPU to replace the current PyTorch-CPU version with one that is compiled against my CUDA CUDA-GPU v11.6 driver, without rebuilding the entire conda environment. I would rather not rebuild the conda environment from scratch unless it is really necessary.
I want to use gpu acceleration for my android emulator in a compute engine instance.
I added tesla t4 gpu and now trying to install the gpu grid driver according to here.
I use ubuntu 20. please advise
https://cloud.google.com/compute/docs/gpus/install-grid-drivers
I get an error:
in file included from /tmp/selfgz11598/NVIDIA-Linux-x86_64-410.92-grid/kernel/nvidia/nv-rsync.c:24:
/tmp/selfgz11598/NVIDIA-Linux-x86_64-410.92-grid/kernel/common/inc/nv-linux.h:1775:6: error: "NV_BUILD_MODULE_INSTA
NCES" is not defined, evaluates to 0 [-Werror=undef]
1775 | #if (NV_BUILD_MODULE_INSTANCES != 0)
| ^~~~~~~~~~~~~~~~~~~~~~~~~
c1: some warnings being treated as errors
make[2]: *** [scripts/Makefile.build:275: /tmp/selfgz11598/NVIDIA-Linux-x86_64-410.92-grid/kernel/nvidia/nv_uvm_int
erface.o] Error 1
/tmp/selfgz11598/NVIDIA-Linux-x86_64-410.92-grid/kernel/nvidia/nvlink_linux.c: In function ‘nvlink_sleep’:
/tmp/selfgz11598/NVIDIA-Linux-x86_64-410.92-grid/kernel/nvidia/nvlink_linux.c:570:5: error: implicit declaration of
function ‘do_gettimeofday’; did you mean ‘efi_gettimeofday’? [-Werror=implicit-function-declaration]
570 | do_gettimeofday(&tm_aux);
| ^~~~~~~~~~~~~~~
| efi_gettimeofday
cc1: some warnings being treated as errors
make[2]: *** [scripts/Makefile.build:275: /tmp/selfgz11598/NVIDIA-Linux-x86_64-410.92-grid/kernel/nvidia/nvlink_lin
ux.o] Error 1
make[2]: Target '__build' not remade because of errors.
make[1]: *** [Makefile:1731: /tmp/selfgz11598/NVIDIA-Linux-x86_64-410.92-grid/kernel] Error 2
make[1]: Target 'modules' not remade because of errors.
make[1]: Leaving directory '/usr/src/linux-headers-5.4.0-1021-gcp'
make: *** [Makefile:79: modules] Error 2
ERROR: The nvidia kernel module was not created.
ERROR: Installation has failed. Please see the file '/var/log/nvidia-installer.log' for details. You may find sug
gestions on fixing installation problems in the README available on the Linux driver download page at www.nvidia.co
m.
(END)
The document you are using to install NVIDIA GRID® drivers for virtual workstations, only contains examples of the commands needed to install the GRID drivers.
The example contained in that guide, is for installing the NVIDIA 410.92 driver, this driver is for GRID7.1, but I recommend to use the latest version of GRID, you can consult the following table to see the drivers available.
I’ve reproduced this scenario on my own project and I was able to install GRID11.0, using the NVIDIA 450.51.05 driver.
I’m using an instance with the following characteristics:
Machine type: n1-standard-1 (1 vCPU, 3.75 GB memory)
GPUs: 1 x NVIDIA Tesla T4
OS ubuntu-minimal-2004-focal-v20200702
Keep in mind that you need to have the option Enable Virtual Workstation (NVIDIA GRID) enabled at the creation moment to avoid issues.
I used the following commands for this installation:
user#instance-1:~$ curl -O https://storage.googleapis.com/nvidia-drivers-us-public/GRID/GRID11.0/NVIDIA-Lin
ux-x86_64-450.51.05-grid.run
% Total % Received % Xferd Average Speed Time Time Time Current
Dload Upload Total Spent Left Speed
100 139M 100 139M 0 0 72.2M 0 0:00:01 0:00:01 --:--:-- 72.1M
user#instance-1:~$ sudo bash NVIDIA-Linux-x86_64-450.51.05-grid.run
Verifying archive integrity... OK
Uncompressing NVIDIA Accelerated Graphics Driver for Linux-x86_64 450.51.05.....................................
................................................................................................................
................................................................................................................
................................................................................................................
................................................................................................................
........................................................................
user#instance-1:~$ nvidia-smi
Mon Jul 27 21:11:17 2020
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 450.51.05 Driver Version: 450.51.05 CUDA Version: 11.0 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 Tesla T4 On | 00000000:00:04.0 Off | 0 |
| N/A 73C P8 21W / 70W | 0MiB / 15109MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| No running processes found |
+-----------------------------------------------------------------------------+
In my case I needed to install some dependencies like the gcc compiler, and I only used the command
$ sudo apt install build-essential
I hope this information is useful for you.
I just installed Octave a few days ago and think I have been installing packages using the "pkg load name" function but never get a confirmation or anything that looks like the software is trying to download them. I also tried pkg install -forge package_name but that doesn't seem to work. Is there a difference between the two calls?
And; How can I know they are downloading? And where can I find a list of them that are?
The download function and automatic package installation in octave 4.2.1 is broken under windows. Nevertheless the standard packets come with the base installation. Just type
pkg list
in the octave console to display all installed packages. In my case the resulting list starts with these lines
Package Name | Version | Installation directory
---------------------+---------+-----------------------
communications | 1.2.1 | C:\Octave\OCTAVE~1.1\share\octave\packages\communications-1.2.1
control | 3.0.0 | C:\Octave\OCTAVE~1.1\share\octave\packages\control-3.0.0
data-smoothing | 1.3.0 | C:\Octave\OCTAVE~1.1\share\octave\packages\data-smoothing-1.3.0
database | 2.4.2 | C:\Octave\OCTAVE~1.1\share\octave\packages\database-2.4.2
dataframe | 1.1.0 | C:\Octave\OCTAVE~1.1\share\octave\packages\dataframe-1.1.0
...
To get package information programmatically use
[dummy,info]=pkg('list');
info is a cell array of structures containing information about the packages. You can e.g. read the information about name and load state:
>> info{1}.name
ans = signal
>> info{1}.loaded
ans = 0
To get help about the package function enter help pgk on the command line. This help is currently (Octave 5.1) not included in the html documentation. That means doc help does NOT display this help page.
octave windows
I have installed python (2.7.8), sympy (0.7.5) and symbolic package (2.3.0) in Octave (4.0.0). In Octave I did
pkg install symbolic-2.3.0.tar (without errors)
pkg load symbolic (without errors)
And now I am trying to use it:
>> symbols
error: 'symbols' undefined near line 1 column 1
Windows 7, 64-bit. The package seems to be in the list of installed ones:
Package Name | Version | Installation directory
--------------+---------+-----------------------
control *| 3.0.0 | C:\Octave\Octave-4.0.0\share\octave\packages\control-3.0.0
financial *| 0.5.0 | C:\Octave\Octave-4.0.0\share\octave\packages\financial-0.5.0
io *| 2.4.1 | C:\Octave\Octave-4.0.0\share\octave\packages\io-2.4.1
optim *| 1.5.1 | C:\Octave\Octave-4.0.0\share\octave\packages\optim-1.5.1
signal *| 1.3.2 | C:\Octave\Octave-4.0.0\share\octave\packages\signal-1.3.2
splines *| 1.2.9 | C:\Octave\Octave-4.0.0\share\octave\packages\splines-1.2.9
struct *| 1.0.13 | C:\Octave\Octave-4.0.0\share\octave\packages\struct-1.0.13
symbolic *| 2.3.0 | C:\Octave\Octave-4.0.0\share\octave\packages\symbolic-2.3.0
Why is the package not used? Would be grateful for any advice.
There is not "symbols" in current version of symbolic package. You can see example of code in wiki. You can try use syms for testing of loading symbolic package:
>> syms x
Read documentation - Octave-Forge
May be useful link - symbolic-computation-and-octave
Im having a hard time using QTOctave on Xubuntu.
Im trying to display a Bode Diagramm but I constantly get the error message from the Octave Terminal:
**warning: dcgain: unstable system; dimensions: nc=0, nz=2, mm=1, pp=1
error: 'create_set' undefined near line 141 column 16
error: called from:
error: /home/octave/control-1.0.11/__bodquist__.m at line 141, colum
n 14
error: /home/octave/control-1.0.11/bode.m at line 134, column 12
error: /home/M/Regelungstechnik/bodeTest.m at line 7, column 1
>>>**
And it is really not a difficult M file:
tau=1/5
z=1;
n=[tau,1, 0]
G=tf(z,n)
bode(G)
I am running it on my Xubuntu 14.04 Desktop and I have the following packages for Octave installed:
>>> pkg list
Package Name | Version | Installation directory
-------------------+---------+-----------------------
control *| 1.0.11 | /home/octave/control-1.0.11
fpl *| 1.2.0 | /home/octave/fpl-1.2.0
gnuplot *| 1.0.1 | /home/octave/gnuplot-1.0.1
ident *| 1.0.7 | /home/octave/ident-1.0.7
informationtheory *| 0.1.8 | /home/aronheck/octave/informationtheory-0.1.8
integration *| 1.0.7 | /home/octave/integration-1.0.7
missing-functions *| 1.0.2 | /home/octave/missing-functions-1.0.2
odebvp *| 1.0.6 | /home/octave/odebvp-1.0.6
plot *| 1.0.8 | /home/octave/plot-1.0.8
simp *| 1.1.0 | /home/octave/simp-1.1.0
I hope you can help me with my problem.
There can be two things why it's not working:
Do you get the same error when you run just Octave, i.e., without QtOctave? QtOctave was abandoned many years ago it is know to not work very well with newer Octave versions.
Your version of the control package is very very old. It seems that you have version 1.0.11 installed but the latest version is 2.8.0. I checked the ubuntu repositories for 14.04 and they have version 2.6.2.
Running Octave 3.8.2 with control version 2.8.0, your code works fine for me:
octave-cli-3.8.2:1> pkg load control
octave-cli-3.8.2:2> tau=1/5
tau = 0.20000
octave-cli-3.8.2:3> z=1;
octave-cli-3.8.2:4> n=[tau,1, 0]
n =
0.20000 1.00000 0.00000
octave-cli-3.8.2:5> G=tf(z,n)
Transfer function 'G' from input 'u1' to output ...
1
y1: -----------
0.2 s^2 + s
Continuous-time model.
octave-cli-3.8.2:6> bode(G)