Category Archives: Linux

Dual GPU notebook configuration Intel + AMD/ATI

Posted by on January 16, 2014 No comments

Add catalyst + xorg114 pacman repos to your /etc/pacman.conf:

[catalyst]
Server = http://catalyst.wirephire.com/repo/catalyst/$arch
 
[xorg114]
Server = http://catalyst.wirephire.com/repo/xorg114/$arch

Install required xorg server and driver packages:

xorg114/xorg-server
 
catalyst/catalyst-hook
catalyst/catalyst-utils-pxp
catalyst/lib32-catalyst-utils-pxp
 
xorg114/xf86-video-intel
extra/intel-dri
multilib/lib32-intel-dri

Create /etc/X11/xorg.conf using aticonfig –initial

Section "ServerLayout"
        Identifier     "aticonfig Layout"
        Screen      0  "aticonfig-Screen[0]-0" 0 0
EndSection
 
Section "Module"
EndSection
 
Section "Monitor"
        Identifier   "aticonfig-Monitor[0]-0"
        Option      "VendorName" "ATI Proprietary Driver"
        Option      "ModelName" "Generic Autodetecting Monitor"
        Option      "DPMS" "true"
EndSection
 
Section "Device"
        Identifier  "aticonfig-Device[0]-0"
        Driver      "fglrx"
        BusID       "PCI:1:0:0"
EndSection
 
Section "Screen"
        Identifier "aticonfig-Screen[0]-0"
        Device     "aticonfig-Device[0]-0"
        Monitor    "aticonfig-Monitor[0]-0"
        DefaultDepth     24
        SubSection "Display"
                Viewport   0 0
                Depth     24
        EndSubSection
EndSection

Switch gpu using the AMD tool: amdcccle

Direct rendering works: glxinfo | grep direct

direct rendering: Yes
[...]

 

If glxgears / glxinfo gives errors like:

libGL error: failed to load driver: i965
libGL error: Try again with LIBGL_DEBUG=verbose for more details.
libGL error: failed to load driver: swrast
libGL error: Try again with LIBGL_DEBUG=verbose for more details.

… set the catalyst libGL path:

export LIBGL_DRIVERS_PATH=/usr/lib/catalystpxp/fglrx/
export LD_PRELOAD=/usr/lib/catalystpxp/fglrx/fglrx-libGL.so.1.2

OpenCL works: clinfo

Number of platforms:                             1
  Platform Profile:                              FULL_PROFILE
  Platform Version:                              OpenCL 1.2 AMD-APP (1348.4)
  Platform Name:                                 AMD Accelerated Parallel Processing
  Platform Vendor:                               Advanced Micro Devices, Inc.
  Platform Extensions:                           cl_khr_icd cl_amd_event_callback cl_amd_offline_devices
 
  Platform Name:                                 AMD Accelerated Parallel Processing
Number of devices:                               2
  Device Type:                                   CL_DEVICE_TYPE_GPU
  Device ID:                                     4098
  Board name:                                    AMD Radeon HD 8600/8700M
  Device Topology:                               PCI[ B#1, D#0, F#0 ]
  Max compute units:                             6
  Max work items dimensions:                     3
    Max work items[0]:                           256
    Max work items[1]:                           256
    Max work items[2]:                           256
  Max work group size:                           256
  Preferred vector width char:                   4
  Preferred vector width short:                  2
  Preferred vector width int:                    1
  Preferred vector width long:                   1
  Preferred vector width float:                  1
  Preferred vector width double:                 1
  Native vector width char:                      4
  Native vector width short:                     2
  Native vector width int:                       1
  Native vector width long:                      1
  Native vector width float:                     1
  Native vector width double:                    1
  Max clock frequency:                           825Mhz
  Address bits:                                  32
  Max memory allocation:                         1073741824
  Image support:                                 Yes
  Max number of images read arguments:           128
  Max number of images write arguments:          8
  Max image 2D width:                            16384
  Max image 2D height:                           16384
  Max image 3D width:                            2048
  Max image 3D height:                           2048
  Max image 3D depth:                            2048
  Max samplers within kernel:                    16
  Max size of kernel argument:                   1024
  Alignment (bits) of base address:              2048
  Minimum alignment (bytes) for any datatype:    128
  Single precision floating point capability
    Denorms:                                     No
    Quiet NaNs:                                  Yes
    Round to nearest even:                       Yes
    Round to zero:                               Yes
    Round to +ve and infinity:                   Yes
    IEEE754-2008 fused multiply-add:             Yes
  Cache type:                                    Read/Write
  Cache line size:                               64
  Cache size:                                    16384
  Global memory size:                            2009071616
  Constant buffer size:                          65536
  Max number of constant args:                   8
  Local memory type:                             Scratchpad
  Local memory size:                             32768
  Kernel Preferred work group size multiple:     64
  Error correction support:                      0
  Unified memory for Host and Device:            0
  Profiling timer resolution:                    1
  Device endianess:                              Little
  Available:                                     Yes
  Compiler available:                            Yes
  Execution capabilities:                                
    Execute OpenCL kernels:                      Yes
    Execute native function:                     No
  Queue properties:                              
    Out-of-Order:                                No
    Profiling :                                  Yes
  Platform ID:                                   0x00007f33cbfb54c0
  Name:                                          Oland
  Vendor:                                        Advanced Micro Devices, Inc.
  Device OpenCL C version:                       OpenCL C 1.2 
  Driver version:                                1348.4 (VM)
  Profile:                                       FULL_PROFILE
  Version:                                       OpenCL 1.2 AMD-APP (1348.4)
  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_atomic_counters_32 cl_amd_device_attribute_query cl_amd_vec3 cl_amd_printf cl_amd_media_ops cl_amd_media_ops2 cl_amd_popcnt cl_khr_image2d_from_buffer

DOGE mining also works with cgminer-gpu from AUR with 55Kh/s at intensity 10:

cgminer version 3.7.2 - Started: [2014-01-16 18:39:45]
--------------------------------------------------------------------------------
 (5s):54.25K (avg):48.66Kh/s | A:64  R:0  HW:0  WU:42.1/m
 ST: 2  SS: 0  NB: 3  LW: 19  GF: 0  RF: 0
 Connected to xxx diff 16 with stratum as user xxx
 Block: daa10059...  Diff:505  Started: [18:39:58]  Best share: 97
--------------------------------------------------------------------------------
 [P]ool management [G]PU management [S]ettings [D]isplay options [Q]uit
 GPU 0:                | 54.25K/48.66Kh/s | A:64 R:0 HW:0 WU: 42.1/m I:10
--------------------------------------------------------------------------------
 
 [2014-01-16 18:39:44] Started cgminer 3.7.2
VN:F [1.9.22_1171]
Rating: 0.0/10 (0 votes cast)

AMD OpenCL on arch linux

Posted by on January 9, 2014 No comments 

 
Due to an old AMD Radeon HD 4890 graphics card, I was forced to use the additional repos xorg112 and catalyst-hd234k to get a working AMD legacy fglrx / X server duo. Till now, clinfo runs fine. However, in order to compile OpenCL applications I installed the amdapp-sdk package from AUR. Afterwards, clinfo and every other OpenCL binary segfaulted instantaneously due to mixed OpenCL versions. Replacing /opt/AMDAPP/SDK/lib/libamdocl64.so with /usr/lib/libamdocl64.so solved this issue.

catalyst-utils: /usr/lib/libamdocl64.so
amdapp-sdk: /opt/AMDAPP/SDK/lib/libamdocl64.so

The GPU load can be monitored using the following command:

aticonfig --adapter=0 --od-getclocks
VN:F [1.9.22_1171]
Rating: 6.0/10 (1 vote cast)

Python-social-auth requires real hostname when using apache+gunicorn

Posted by on January 3, 2014 No comments

After a successful authentication using google-oauth2 with the python-social-auth tool, the client gets redirected to a ../complete/ page. However, after forwarding all non-static traffic from the apache to a local gunicorn server, the redirection url points to http://localhost:8000/complete rather than to the real website. This can be easily fixed by enabling the ProxyPreserveHost setting in the apache config:

<VirtualHost *:80>
        ServerAdmin ...
        ServerName ...
 
        Alias /static /.../static
 
        DocumentRoot ...
 
        <Directory ...>
                Options Indexes FollowSymLinks MultiViews
                AllowOverride All
                Order allow,deny
                allow from all
        </Directory>
 
        ProxyPreserveHost on
 
        RewriteEngine on
        RewriteRule ^/static/.* - [L]
 
        # Django is run via gunicorn. So proxy the rest.
        RewriteRule ^(.*) http://localhost:8000$1 [P]
</VirtualHost>

VN:F [1.9.22_1171]
Rating: 5.0/10 (1 vote cast)

Supervisord at 100% load for gunicorn

Posted by on January 3, 2014 No comments

Starting a gunicorn django server with the supervisord daemon using the deprecated gunicorn_django command works but results in 100% load of the supervisor process.

[program:gunicorn]
command=start_gunicorn.sh
process_name=gunicorn  ; process_name expr (default %(program_name)s)
numprocs=1                    ; number of processes copies to start (def 1)
directory=/home/gunicorn  ; directory to cwd to before exec (def no cwd)
autostart=true                ; start at supervisord start (default: true)
autorestart=true        ; whether/when to restart (default: unexpected)
user=gunicorn                   ; setuid to this UNIX account to run the program
redirect_stderr=true          ; redirect proc stderr to stdout (default false)

After adding gunicorn to the INSTALLED_APPS in the project settings, the gunicorn server can be easily started with the python manage.py run_gunicorn command and everything works fine.
INSTALLED_APPS = (
    ...
    'gunicorn'
    ...
)

VN:F [1.9.22_1171]
Rating: 6.0/10 (1 vote cast)

streaMplayer – play flash streams with mplayer

Posted by on October 3, 2013 No comments

Want to watch a flash live stream but your browser is not able to play the stream smoothly ? Or maybe you simply hate flash movies… Here is the solution ! Catch the stream and pipe it to mplayer. Here is small python script to set the required iptables and start mplayer afterwards.

Usage: Start the script; then open / reload the website that includes the flash player in your browser.

#!/usr/bin/python3
import time
import subprocess
 
###############
retries = 3
sleep = 3
###############
 
iptAdd = "sudo iptables -t nat -A OUTPUT -p tcp --dport 1935 -j REDIRECT"
iptDel = "sudo iptables -t nat -D OUTPUT -p tcp --dport 1935 -j REDIRECT"
 
iptc = subprocess.Popen(iptAdd, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
iptc.wait()
_, stderr = iptc.communicate()
 
if not len(stderr) == 0:
    print(stderr)
    exit(0)
 
try:
    rtmpsrv = subprocess.Popen("rtmpsrv", stdout=subprocess.PIPE, stderr=subprocess.PIPE, bufsize=0)
    while True:
        line = rtmpsrv.stderr.readline()
        if line.find(b"Closing connection") >= 0:
            rtmpsrv.kill()
            break
 
        time.sleep(0.5)
 
    stdout, _ = rtmpsrv.communicate()
 
    rtmpdump = b"".join(stdout.split(b"\n"))
 
except:
    rtmpdump = None
 
iptc = subprocess.Popen(iptDel, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
iptc.wait()
_, stderr = iptc.communicate()
 
if not len(stderr) == 0:
    print("Could not detect stream.")
    print(stderr)
    exit(0)
 
if not rtmpdump is None:
    rtmpdump = rtmpdump.decode("ASCII")
 
    print("Found rtmpdump command: '%s'\n" % rtmpdump)
 
    mp = "%s | mplayer -" % rtmpdump[:rtmpdump.find(" -o \"")]
    print("Executing: '%s'\n" % mp)
 
    retry = 0
    while True:
        mplayer = subprocess.Popen(mp, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
        mplayer.wait()
        _, stderr = mplayer.communicate()
 
        if stderr.find(b"ERROR") >= 0:
            print("Error :(")
 
            if retry < retries:
                time.sleep(sleep)
                retry += 1
                print("Retry (%d)" % retry)
 
            else:
                print("Giving up")
                break
 
        else:
            break

 

 

 

VN:F [1.9.22_1171]
Rating: 3.0/10 (1 vote cast)

Faster file IO in python using cython

Posted by on August 30, 2013 No comments

Reading large files in Python sometimes feels incredible slow. Here are some approaches using Cython to minimize reading times. Simply compiling the existing python code with Cython reduces the reading times by 23%. By introducing explicit type definitions, I could finally reach C++ reading speeds wich are 4.4x faster than pure Python code. However, when I used the generator keyword yield to iterate over all lines in an external Python function without exploiting my memory, the required runtime doubles for this approach. The used code snippets are listed below.

timings

File: file_io_python.py – Simple python function to read in a file line by line.

def read_file_python(filename):
    f = open(filename, "rb")
    while True:
        line = f.readline()
        if not line: break
 
        #yield line
 
    f.close()
    return []

File: file_io.pyx – Cython file, containing a pure python function and a cython optimized function for linewise file reading.

from libc.stdio cimport *
 
cdef extern from "stdio.h":
    #FILE * fopen ( const char * filename, const char * mode )
    FILE *fopen(const char *, const char *)
    #int fclose ( FILE * stream )
    int fclose(FILE *)
    #ssize_t getline(char **lineptr, size_t *n, FILE *stream);
    ssize_t getline(char **, size_t *, FILE *)
 
def read_file_slow(filename):
    f = open(filename, "rb")
    while True:
        line = f.readline()
        if not line: break
 
        #yield line
 
    f.close()
 
    return []
 
def read_file(filename):
    filename_byte_string = filename.encode("UTF-8")
    cdef char* fname = filename_byte_string
 
    cdef FILE* cfile
    cfile = fopen(fname, "rb")
    if cfile == NULL:
        raise FileNotFoundError(2, "No such file or directory: '%s'" % filename)
 
    cdef char * line = NULL
    cdef size_t l = 0
    cdef ssize_t read
 
    while True:
        read = getline(&line, &l, cfile)
        if read == -1: break
 
        #yield line
 
    fclose(cfile)
 
    return []

File: file_io.cpp – Comparison code for C++.

#include "stdio.h"
#include <stdlib.h>
 
int main()
{
    FILE* cfile = fopen("trajectory.pdb", "rb");
 
    if(cfile == NULL) return 1;
 
    char * line = NULL;
    size_t l = 0;
    ssize_t read;
 
    while(true)
    {
        read = getline(&line, &l, cfile);
        if(read == -1) break;
    }
    free(line);
 
    fclose(cfile);
 
    return 0;
}

File: file_io_bench.py – Python code to test and benchmark all different functions.
import timeit
 
#################
count = 10
check = False
#################
 
if check:
    from file_io import read_file, read_file_slow
 
    import hashlib
    m = hashlib.new("md5")
    for line in read_file_slow("trajectory.pdb"):
        m.update(line)
 
    h1 = m.hexdigest()
 
    m = hashlib.new("md5")
    for line in read_file("trajectory.pdb"):
        m.update(line)
 
    h2 = m.hexdigest()
 
    assert h1 == h2, Exception("read error")
    print("read functions: ok")
 
t = timeit.Timer("""for line in read_file_python("trajectory.pdb"):
  pass""", """from file_io_python import read_file_python""")
t1 = t.timeit(count)
print("Python", t1, "sec")
 
t = timeit.Timer("""for line in read_file_slow("trajectory.pdb"):
  pass""", """from file_io import read_file_slow""")
t2 = t.timeit(count)
print("Cython", t2, "sec")
 
t = timeit.Timer("""for line in read_file("trajectory.pdb"):
  pass""", """from file_io import read_file""")
t3 = t.timeit(count)
print("cdef Cython", t3, "sec")
 
t = timeit.Timer("""s = subprocess.Popen("./a.out", shell=True)
s.wait()
""", """import subprocess""")
t4 = t.timeit(count)
print("C", t4, "sec")

VN:F [1.9.22_1171]
Rating: 7.6/10 (7 votes cast)

Logitech mouse not working after kernel upgrade to 3.10.2-1-ARCH

Posted by on July 26, 2013 No comments

After upgrading my kernel to 3.10.2-1-ARCH, my logitech wireless mouse m325 stoped working.
I installed ltunify-git from AUR repo to control the logitech unifying device. After unpairing and pairing ‘idx=1 Mouse M325’, the mouse was working again.

sudo ltunify -d /dev/hidraw0 unpair 1
sudo ltunify -d /dev/hidraw0 pair 10

Now turn your mouse off and on again ! (and press a button)

VN:F [1.9.22_1171]
Rating: 6.5/10 (2 votes cast)

Password generator

Posted by on February 16, 2012 No comments

If you also need a new WPA password for your router, try this:

doep ~ # cat /dev/urandom | tr -dc a-zA-Z0-9 | head -c 63
VN:F [1.9.22_1171]
Rating: 2.5/10 (2 votes cast)
Wir benutzen Cookies um die Nutzerfreundlichkeit der Webseite zu verbessen. Durch Deinen Besuch stimmst Du dem zu.
Weitere Informationen