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Procinfo NG 2.0.113 (C++ Implementation)
Procinfo NG is a ground-up rewrite of the procinfo program. more>>
Procinfo NG is a ground-up rewrite of the procinfo program. Procinfo NGs goal is to make the code more readable (and reusable) and to restore broken functionality of the original program.
The original program was written for Linux 1.0, and updated through 2.2. This version is for 2.6.
Enhancements:
- Updates were made to match what some Linux distributions have done to procinfo-18.
- Support for MSI and XEN interrupts were added.
- Some non-x86 architectures are handled.
- Assorted bugs and 80-character console nonsense were fixed.
<<lessThe original program was written for Linux 1.0, and updated through 2.2. This version is for 2.6.
Enhancements:
- Updates were made to match what some Linux distributions have done to procinfo-18.
- Support for MSI and XEN interrupts were added.
- Some non-x86 architectures are handled.
- Assorted bugs and 80-character console nonsense were fixed.
Download (0.041MB)
Added: 2007-08-11 License: GPL (GNU General Public License) Price:
805 downloads
Other version of Procinfo NG
Procinfo NG 1.0 (Perl Implementation) Procinfo NG is a ground-up rewrite of the procinfo ... Implementation) - Thaddeus Messenger. Procinfo NG. Procinfo NG is a ground-up rewrite of theLicense:GPL (GNU General Public License)
Bellagio OpenMAX IL Implementation 0.3.1
Bellagio is a sample implementation of OpenMAX IL for Linux. more>>
Bellagio is a sample implementation of OpenMAX IL for Linux.
It enables software developers and ISVs to familiarize themselves with the OpenMAX IL API and to develop their own OpenMAX multimedia and streaming media components for mobile devices, including codecs, video I/O, and audio mixers.
Included sample components comply with the OpenMAX base and interoperability profiles and can be tunnelled together.
Main features:
- a shared library with the IL core and a "reference" OpenMAX component
- a number of OpenMAX components which pass Khronos conformance tests
- a set of GStreamer plugins that use the IL API (not available yet)
Enhancements:
New video components:
- ffmpeg based MPEG4/H.264 decoder
- color converter component YUV -> RGB
- video renderer based on devFB
New audio component:
- audio file reader based on ffmpeg audio format
- volume component
Fixed known bugs:
- FFMPEG audio decoder now works on FC6 and other distributions with the latest ffmpeg release (0.4.9-0.35.20070204)
Known pending bugs:
- some ogg streams can not be decoded properly
- the tunneling between file reader, mp3 dec based on ffmpeg - alsa sink ends in a deadlock sometimes.
- This behavior has been detected some times using FC6 and UBUNTU, not with the FC4
Full list of components:
Audio:
- ogg decoder based on libvorbis (stand alone components, and multiple roles component)
- mp3 decoder based on mad decoder
- mp3 decoder based on ffmpeg (multiple roles component)
- volume component
- alsa audio sink
- ffmpeg audio file reader (to be used with mp3 ffmpeg decoder)
Video:
- MPEG4 decoder based on ffmpeg (multiple roles component)
- H.264 decoder based on ffmpeg (multiple roles component)
- Color converter based on ffmpeg
- video renderer based on devFB
- Major additions to the 0.2
- New port classes
The components are:
- multiple formats audio decoder component that supports mp3 and ogg audio formats
- alsa sink component
- all the other components are NOT compatible with the new architecture.
- They have been removed and will be ported to the new architecture in a further delivery
<<lessIt enables software developers and ISVs to familiarize themselves with the OpenMAX IL API and to develop their own OpenMAX multimedia and streaming media components for mobile devices, including codecs, video I/O, and audio mixers.
Included sample components comply with the OpenMAX base and interoperability profiles and can be tunnelled together.
Main features:
- a shared library with the IL core and a "reference" OpenMAX component
- a number of OpenMAX components which pass Khronos conformance tests
- a set of GStreamer plugins that use the IL API (not available yet)
Enhancements:
New video components:
- ffmpeg based MPEG4/H.264 decoder
- color converter component YUV -> RGB
- video renderer based on devFB
New audio component:
- audio file reader based on ffmpeg audio format
- volume component
Fixed known bugs:
- FFMPEG audio decoder now works on FC6 and other distributions with the latest ffmpeg release (0.4.9-0.35.20070204)
Known pending bugs:
- some ogg streams can not be decoded properly
- the tunneling between file reader, mp3 dec based on ffmpeg - alsa sink ends in a deadlock sometimes.
- This behavior has been detected some times using FC6 and UBUNTU, not with the FC4
Full list of components:
Audio:
- ogg decoder based on libvorbis (stand alone components, and multiple roles component)
- mp3 decoder based on mad decoder
- mp3 decoder based on ffmpeg (multiple roles component)
- volume component
- alsa audio sink
- ffmpeg audio file reader (to be used with mp3 ffmpeg decoder)
Video:
- MPEG4 decoder based on ffmpeg (multiple roles component)
- H.264 decoder based on ffmpeg (multiple roles component)
- Color converter based on ffmpeg
- video renderer based on devFB
- Major additions to the 0.2
- New port classes
The components are:
- multiple formats audio decoder component that supports mp3 and ogg audio formats
- alsa sink component
- all the other components are NOT compatible with the new architecture.
- They have been removed and will be ported to the new architecture in a further delivery
Download (0.49MB)
Added: 2007-06-06 License: GPL (GNU General Public License) Price:
895 downloads
Suffix tree implementation library 1.2
Suffix tree implementation library is a C library, an implementation of the suffix trees algorithm to store/retrieve key/data pa more>>
Suffix tree implementation library is a C library, an implementation of the suffix trees algorithm to store/retrieve key/data pairs.
The main advantages are a linear indexing time, little memory usage, and very fast retrieving.
It has been developped on FreeBSD/gcc but should be fairly portable.
The source code "testsfx.c" show an example of how to use the library both for inserting, retrieving, and deleting data. There arent many functions and comments should be enough to give you an idea of how to use the library. (read the header of the source file)
You should edit sfxdisk.h to suit your needs: you can change the alphabet size and the offset type. It should be OK to use "long long" 64 bits ints instead of long, in fact I tested it succesfully but havent gone to the point of filling more than 2 GB of data (needless to say you need a 64 bits filesystem).
Two "tools" come with the library (new with version 1.2): dumpsfx and loadsfx. dumpsfx is used to dump the database: dumpsfx [-s separator] if you want to output the result as readable text or dumpsfx < file.sfx > -h to output it for reloading with loadsfx.
dumpsfx outputs on stdout and loadsfx reads from stdin. loadsfx < suffix tree file to create > < dumped_file
Enhancements:
- removed an useless offset incrementation in STwritenode
<<lessThe main advantages are a linear indexing time, little memory usage, and very fast retrieving.
It has been developped on FreeBSD/gcc but should be fairly portable.
The source code "testsfx.c" show an example of how to use the library both for inserting, retrieving, and deleting data. There arent many functions and comments should be enough to give you an idea of how to use the library. (read the header of the source file)
You should edit sfxdisk.h to suit your needs: you can change the alphabet size and the offset type. It should be OK to use "long long" 64 bits ints instead of long, in fact I tested it succesfully but havent gone to the point of filling more than 2 GB of data (needless to say you need a 64 bits filesystem).
Two "tools" come with the library (new with version 1.2): dumpsfx and loadsfx. dumpsfx is used to dump the database: dumpsfx [-s separator] if you want to output the result as readable text or dumpsfx < file.sfx > -h to output it for reloading with loadsfx.
dumpsfx outputs on stdout and loadsfx reads from stdin. loadsfx < suffix tree file to create > < dumped_file
Enhancements:
- removed an useless offset incrementation in STwritenode
Download (0.015MB)
Added: 2006-08-07 License: GPL (GNU General Public License) Price:
1189 downloads
Parallel MPI BZIP2 0.6
Parallel MPI BZIP2 is a parallel implementation of the bzip2 block-sorting file compressor. more>>
Parallel MPI BZIP2 is a parallel implementation of the bzip2 block-sorting file compressor that uses MPI and achieves significant speedup on cluster machines.
The output of this version is fully compatible with bzip2 v1.0.2 or newer (ie: anything compressed with mpibzip2 can be decompressed with bzip2). MPIBZIP2 should work on any system that has a pthreads compatible C++ compiler (such as gcc). It has been tested on: Linux and Solaris.
NOTE: If you are looking for a parallel BZIP2 that works on multi-processor/muti-core/SMP machines, you should check out PBZIP2 which was designed for a multi-threaded shared-memory architecture.
Usage:
Run mpibzip2 for the help listing.
==================================================================
Usage: mpibzip2 [-1 .. -9] [-b#cdfktvV] < filename > < filename2 > < filenameN >
-b#: where # is the file block size in 100k (default 9 = 900k)
-c : output to standard out (stdout)
-d : decompress file
-f : force, overwrite existing output file
-k : keep input file, dont delete
-t : test compressed file integrity
-v : verbose mode
-V : display version info for mpibzip2 then exit
-1 .. -9 : set BWT block size to 100k .. 900k (default 900k)
Example: mpibzip2 -b15k myfile.tar
Example: mpibzip2 -v -5 myfile.tar second*.txt
Example: mpibzip2 -d myfile.tar.bz2
<<lessThe output of this version is fully compatible with bzip2 v1.0.2 or newer (ie: anything compressed with mpibzip2 can be decompressed with bzip2). MPIBZIP2 should work on any system that has a pthreads compatible C++ compiler (such as gcc). It has been tested on: Linux and Solaris.
NOTE: If you are looking for a parallel BZIP2 that works on multi-processor/muti-core/SMP machines, you should check out PBZIP2 which was designed for a multi-threaded shared-memory architecture.
Usage:
Run mpibzip2 for the help listing.
==================================================================
Usage: mpibzip2 [-1 .. -9] [-b#cdfktvV] < filename > < filename2 > < filenameN >
-b#: where # is the file block size in 100k (default 9 = 900k)
-c : output to standard out (stdout)
-d : decompress file
-f : force, overwrite existing output file
-k : keep input file, dont delete
-t : test compressed file integrity
-v : verbose mode
-V : display version info for mpibzip2 then exit
-1 .. -9 : set BWT block size to 100k .. 900k (default 900k)
Example: mpibzip2 -b15k myfile.tar
Example: mpibzip2 -v -5 myfile.tar second*.txt
Example: mpibzip2 -d myfile.tar.bz2
Download (0.018MB)
Added: 2007-07-25 License: BSD License Price:
823 downloads
Parallel BZIP2 1.0.2
Parallel BZIP2 project is a parallel implementation of the bzip2 block. more>>
Parallel BZIP2 project is a parallel implementation of the bzip2 block- sorting file compressor that uses pthreads and achieves near-linear speedup on SMP machines. The output of this version is fully compatible with bzip2 1.0.2 (ie: anything compressed with PBZIP2 can be decompressed with bzip2).
PBZIP2 should work on any system that has a pthreads compatible C++ compiler (such as gcc). It has been tested on: Linux, Windows (cygwin & MinGW), Solaris, Tru64/OSF1, HP-UX, and Irix.
<<lessPBZIP2 should work on any system that has a pthreads compatible C++ compiler (such as gcc). It has been tested on: Linux, Windows (cygwin & MinGW), Solaris, Tru64/OSF1, HP-UX, and Irix.
Download (0.026MB)
Added: 2007-07-26 License: BSD License Price:
828 downloads
Fast MD5 Implementation in Java 2.6.1
Fast MD5 Implementation in Java is a heavily optimized implementation of the MD5 hashing algorithm written in Java. more>>
Fast MD5 Implementation in Java is a heavily optimized implementation of the MD5 hashing algorithm written in Java.
Fast MD5 Implementation in Java includes an optional native method for even greater speed improvements.
How Fast Is It?
Short answer:Much faster than any other Java implementation that I have tested and (surprisingly) even faster than the native, non-Java MD5 implementation on some systems.
Long answer:First of all, it is important to note that the term "fast" is used here in relative terms. The implementation of the MD5 message digest algorithm available on this page is written in Java and is fast compared with other implementations written in Java, both because it is heavily optimized by itself and because there is an optional native method that makes it even faster when the platform supports it. How it compares to a sensible implementation written in a language, such as C, that is compiled directly to machine code, is heavily dependent upon how good of a job the JIT compiler in your JVM does in compiling the code or whether you are able to use the optional native method.
Enhancements:
- Martin West contributed a bug fix and some code refactoring to make all targets work out of the box in the Ant build file. Previously, the "dist" target did not work if the "docs" directory was not present.
<<lessFast MD5 Implementation in Java includes an optional native method for even greater speed improvements.
How Fast Is It?
Short answer:Much faster than any other Java implementation that I have tested and (surprisingly) even faster than the native, non-Java MD5 implementation on some systems.
Long answer:First of all, it is important to note that the term "fast" is used here in relative terms. The implementation of the MD5 message digest algorithm available on this page is written in Java and is fast compared with other implementations written in Java, both because it is heavily optimized by itself and because there is an optional native method that makes it even faster when the platform supports it. How it compares to a sensible implementation written in a language, such as C, that is compiled directly to machine code, is heavily dependent upon how good of a job the JIT compiler in your JVM does in compiling the code or whether you are able to use the optional native method.
Enhancements:
- Martin West contributed a bug fix and some code refactoring to make all targets work out of the box in the Ant build file. Previously, the "dist" target did not work if the "docs" directory was not present.
Download (0.073MB)
Added: 2006-03-06 License: LGPL (GNU Lesser General Public License) Price:
1350 downloads
Parallel Bladeenc 0.92.1b5
Parallel Bladeenc is a true parallel version of the Bladeenc MP3 encoder. more>>
Parallel Bladeenc is a true parallel version of the Bladeenc MP3 encoder; it distributes work across CPUs to speed up MP3 encoding. It uses the Message Passing Interface (MPI) for parallelization across SMPs and/or multiple machines. Hence, if you have a 4-way SMP, you can encode your MP3s about 4 times as fast as the regular Bladeenc; if you have two 4-way SMPs, you can encode about 8 times as fast.
The difficult part about parallelization is typically about how to split the problem up into independent (or nearly independent) parts. The structure shown above - assuming that the encode() function was independent of previous calls to encode() - is trivial to parallelize.
For example, if we want to run on four machines, we can split the input file into four parts, give 1/4 of the file to each machine, and let each machine loop over encode() for their portion of the file. Then take the output from each machine, put it in the right order, and write it out to a single output file. Done.
With such a scheme, the more work that you throw at it, the more efficient it will become.
Hence, trying this scheme with small MP3 files will probably not result in any noticeable speedup (in fact, it may be slower than running in serial, because of the added overhead for working in parallel). It is necessary to give the parallel engine enough work to offset the overhead added by the parallel framework. Generally, this is not very much overhead (read on to find out why), but parallel is not free.
Enhancements:
- Fixed minor error that caused an error message from MPICH when shutting down. Thanks to Gary Smith for pointing this out.
<<lessThe difficult part about parallelization is typically about how to split the problem up into independent (or nearly independent) parts. The structure shown above - assuming that the encode() function was independent of previous calls to encode() - is trivial to parallelize.
For example, if we want to run on four machines, we can split the input file into four parts, give 1/4 of the file to each machine, and let each machine loop over encode() for their portion of the file. Then take the output from each machine, put it in the right order, and write it out to a single output file. Done.
With such a scheme, the more work that you throw at it, the more efficient it will become.
Hence, trying this scheme with small MP3 files will probably not result in any noticeable speedup (in fact, it may be slower than running in serial, because of the added overhead for working in parallel). It is necessary to give the parallel engine enough work to offset the overhead added by the parallel framework. Generally, this is not very much overhead (read on to find out why), but parallel is not free.
Enhancements:
- Fixed minor error that caused an error message from MPICH when shutting down. Thanks to Gary Smith for pointing this out.
Download (0.22MB)
Added: 2006-07-18 License: LGPL (GNU Lesser General Public License) Price:
1193 downloads
Parallel::Workers::Transaction 0.0.7
Parallel::Workers::Transaction is a simple Perl module. more>>
Parallel::Workers::Transaction is a simple Perl module.
Parallel::Workers::Transaction requires no configuration files or environment variables.
<<lessParallel::Workers::Transaction requires no configuration files or environment variables.
Download (0.010MB)
Added: 2007-01-23 License: Perl Artistic License Price:
1004 downloads
Parallel Network Scanner 1.11
Parallel Network Scanner provides a fast network services scanner. more>>
Parallel Network Scanner provides a fast network services scanner.
pnscan is a scanner for TCP network services. It uses multithreading to increase its speed.
pnscan tries to be smart as to how many threads to start - it will dynamically start only as many as is needed to make progress in the scan - up to a maximum either as specified with the "-n" command line option, or 8 minus the maximum number of available file descriptors (pnscan tries to increase
it to the max limit automatically) - or any internal limit on the system (Linux normally only allows 256 threads).
Host ranges can be specified both as a CIDR - network name or IP address / mask bit length and as a range. When using CIDR notation - the first and last address is ignored (normally used for broadcasts)
Some examples:
192.168.0.0/24
192.160.0.1:192.160.0.254
arpanet/8
USAGE - EXAMPLES
# Scan network 192.168.0.0/24 for SSH daemons on port 22
pnscan 192.168.0.0/24 22
pnscan 192.168.0.1:192.168.0.254 ssh
# Scan hosts 192.168.10.34 ... 98 for IDENT servers, max 8 threads
pnscan -n8 -w"VERSION" 192.168.10.34:192.168.10.98 113
# Scan host 127.0.0.1 for WWW servers on all ports
pnscan -w"HEAD / HTTP/1.0rnrn" -r"Server:" 192.168.0.32 1:65525
pnscan -w"HEAD / HTTP/1.0rnrn" -r"Server:" localhost 1:65525
# Send binary data and expect the binary sequence FF 00 FF on port 145.
pnscan -W"05 5A 37" -R"FF 00 FF" 192.168.0.32 145
# Scan for Roxen servers and print the whole Server-line
pnscan -l -w"HEAD / HTTP/1.0rnrn" -r"Roxen" localhost 1:65525
# Scan for pidentd servers and try to locate the version
pnscan -w"VERSION" 192.160.0.0/24 113
# Scan network arpanet/24 for daytime servers and sort them IP-numerically
pnscan arpanet/10 daytime | ipsort
# Read host (&port) lines from stdin and scan the selected hosts for SSH
echo 192.160.10.11 ssh | pnscan -v
echo 192.160.10.12 | pnscan 22
Enhancements:
- pnscan.sgml Added the other options implemented in pnscan.c.
- pnscan.c: Modified the threads startup code to dynamically only start as many threads as is needed.
<<lesspnscan is a scanner for TCP network services. It uses multithreading to increase its speed.
pnscan tries to be smart as to how many threads to start - it will dynamically start only as many as is needed to make progress in the scan - up to a maximum either as specified with the "-n" command line option, or 8 minus the maximum number of available file descriptors (pnscan tries to increase
it to the max limit automatically) - or any internal limit on the system (Linux normally only allows 256 threads).
Host ranges can be specified both as a CIDR - network name or IP address / mask bit length and as a range. When using CIDR notation - the first and last address is ignored (normally used for broadcasts)
Some examples:
192.168.0.0/24
192.160.0.1:192.160.0.254
arpanet/8
USAGE - EXAMPLES
# Scan network 192.168.0.0/24 for SSH daemons on port 22
pnscan 192.168.0.0/24 22
pnscan 192.168.0.1:192.168.0.254 ssh
# Scan hosts 192.168.10.34 ... 98 for IDENT servers, max 8 threads
pnscan -n8 -w"VERSION" 192.168.10.34:192.168.10.98 113
# Scan host 127.0.0.1 for WWW servers on all ports
pnscan -w"HEAD / HTTP/1.0rnrn" -r"Server:" 192.168.0.32 1:65525
pnscan -w"HEAD / HTTP/1.0rnrn" -r"Server:" localhost 1:65525
# Send binary data and expect the binary sequence FF 00 FF on port 145.
pnscan -W"05 5A 37" -R"FF 00 FF" 192.168.0.32 145
# Scan for Roxen servers and print the whole Server-line
pnscan -l -w"HEAD / HTTP/1.0rnrn" -r"Roxen" localhost 1:65525
# Scan for pidentd servers and try to locate the version
pnscan -w"VERSION" 192.160.0.0/24 113
# Scan network arpanet/24 for daytime servers and sort them IP-numerically
pnscan arpanet/10 daytime | ipsort
# Read host (&port) lines from stdin and scan the selected hosts for SSH
echo 192.160.10.11 ssh | pnscan -v
echo 192.160.10.12 | pnscan 22
Enhancements:
- pnscan.sgml Added the other options implemented in pnscan.c.
- pnscan.c: Modified the threads startup code to dynamically only start as many threads as is needed.
Download (0.014MB)
Added: 2007-03-12 License: Freeware Price:
958 downloads
kparalleleport 1.1
kparalleleport is a program for programmers who wish to use the parallel port. more>>
kparalleleport is a program for programmers who wish to use the parallel port.
The project makes it possible to view the values registered or read on the parallel port.
<<lessThe project makes it possible to view the values registered or read on the parallel port.
Download (0.098MB)
Added: 2007-02-12 License: GPL (GNU General Public License) Price:
984 downloads
PDL::Parallel::MPI 0.02
PDL::Parallel::MPI Perl module contains routines to allow PDL objects to be moved around on parallel systems using the MPI lib. more>>
PDL::Parallel::MPI Perl module contains routines to allow PDL objects to be moved around on parallel systems using the MPI library.
SYNOPSIS
use PDL;
use PDL::Parallel::MPI;
mpirun(2);
MPI_Init();
$rank = get_rank();
$a=$rank * ones(2);
print "my rank is $rank and $a is $an";
$a->move( 1 => 0);
print "my rank is $rank and $a is $an";
MPI_Finalize();
MPI STANDARD CALLS
Most of the functions from the MPI standard may be used from this module on regular perl data. This is functionallity inherited from the Parallel::MPI module. Read the documentation for Parallel::MPI to see how to use.
One may mix mpi calls on perl built-in-datatypes and mpi calls on piddles.
use PDL;
use PDL::Parallel::MPI;
mpirun(2);
MPI_Init();
$rank = get_rank();
$pi = 3.1;
if ($rank == 0) {
MPI_Send($pi,1,MPI_DOUBLE,1,0,MPI_COMM_WORLD);
} else {
$message = zeroes(1);
$message->receive(0);
print "pi is $messagen";
}
MPI_Finalize();
<<lessSYNOPSIS
use PDL;
use PDL::Parallel::MPI;
mpirun(2);
MPI_Init();
$rank = get_rank();
$a=$rank * ones(2);
print "my rank is $rank and $a is $an";
$a->move( 1 => 0);
print "my rank is $rank and $a is $an";
MPI_Finalize();
MPI STANDARD CALLS
Most of the functions from the MPI standard may be used from this module on regular perl data. This is functionallity inherited from the Parallel::MPI module. Read the documentation for Parallel::MPI to see how to use.
One may mix mpi calls on perl built-in-datatypes and mpi calls on piddles.
use PDL;
use PDL::Parallel::MPI;
mpirun(2);
MPI_Init();
$rank = get_rank();
$pi = 3.1;
if ($rank == 0) {
MPI_Send($pi,1,MPI_DOUBLE,1,0,MPI_COMM_WORLD);
} else {
$message = zeroes(1);
$message->receive(0);
print "pi is $messagen";
}
MPI_Finalize();
Download (0.13MB)
Added: 2007-07-07 License: Perl Artistic License Price:
843 downloads
Parallel Port Make 0.22
Parallel Port Make can build FreeBSD ports in parallel to fully take advantage of modern multi-core and processor machine. more>>
Parallel Port Make project is a tool to build FreeBSD ports in parallel to fully take advantage of modern multi-core and processor machines.
Default: pportmake.py --clean -- cleanup --install -job=2 [port1] [portn]
Example: pportmake.py irc/irssi irc/epic
Advanced: pportmake.py -rSvD -j 10 irc/irssi
-h --help Show this help usage message
-c --clean Clean port before compiling
-C --cleanup Clean port after compiling
-d --deinstall Deinstall ports, implied by reinstall
-f --force Force a port and all dependancies to be installed
-G --noconfig Dont recursively configure options
-i --install Install port (default)
-j n --jobs=n Number of threads to use, 1 or 2 per CPU core
is recommended
Default is 2
-O args --options=foo List of arguments to pass to make.
E.g. -O -DX11=yes -DFOO
-r --reinstall Reinstall port and ALL dependancies
-S --maxspeed Try and speed up by maximising CPU usuage.
This may break some ports, use with caution
-w --noclean Dont make clean before compiling
-W --nocleanup Dont make clean after compiling
-v --verbose Be extra verbose
-V --version Show version information
-D --debug Show some debugging info
-P --pretend Dont actually alter the ports
NOTES: It is currently only safe to run 1 copy of this and not have other ports compiling simultaneously
<<lessDefault: pportmake.py --clean -- cleanup --install -job=2 [port1] [portn]
Example: pportmake.py irc/irssi irc/epic
Advanced: pportmake.py -rSvD -j 10 irc/irssi
-h --help Show this help usage message
-c --clean Clean port before compiling
-C --cleanup Clean port after compiling
-d --deinstall Deinstall ports, implied by reinstall
-f --force Force a port and all dependancies to be installed
-G --noconfig Dont recursively configure options
-i --install Install port (default)
-j n --jobs=n Number of threads to use, 1 or 2 per CPU core
is recommended
Default is 2
-O args --options=foo List of arguments to pass to make.
E.g. -O -DX11=yes -DFOO
-r --reinstall Reinstall port and ALL dependancies
-S --maxspeed Try and speed up by maximising CPU usuage.
This may break some ports, use with caution
-w --noclean Dont make clean before compiling
-W --nocleanup Dont make clean after compiling
-v --verbose Be extra verbose
-V --version Show version information
-D --debug Show some debugging info
-P --pretend Dont actually alter the ports
NOTES: It is currently only safe to run 1 copy of this and not have other ports compiling simultaneously
Download (0.005MB)
Added: 2007-01-16 License: BSD License Price:
1013 downloads
Parallel::Pvm 1.4.0
Parallel::Pvm is a Perl extension for the Parallel Virtual Machine (PVM) Message Passing System. more>>
Parallel::Pvm is a Perl extension for the Parallel Virtual Machine (PVM) Message Passing System.
SYNOPSIS
use Parallel::Pvm;
The PVM message passing system enables a programmer to configure a group of (possibly heterogenous) computers connected by a network into a parallel virtual machine. The system was developed by the University of Tennessee, Oak Ridge National Laboratory and Emory University.
Using PVM, applications can be developed which spawns parallel processes onto nodes in the virtual machine to perform specific tasks. These parallel tasks can also periodically exchange information using a set of message passing functions developed for the system.
PVM applications have mostly been developed in the scientific and engineering fields. However applications for real-time and client/server systems can also be developed. PVM simply provides a convenient way for managing parallel tasks and communications without need for rexec or socket level programming.
As a utility, PVM enables an organisation to leverage on the computers already available for parallel processing. Parallel applications can be started during non-peak hours to utilise idle CPU cycles. Or dedicated workstation clusters connected via a high performance network like ATM can be used for high performance computing.
It is recommended that you read the PVM manual pages and the book "PVM: Parallel Virtual Machine, A userss guide and tutorial for networked parallel computing". Both the PVM system and the book can be obtained from the HTTP address http://www.epm.ornl.gov/pvm.
For the rest of this document we will provide a tutorial introduction to developing PVM applications using perl. The interface for some of the PVM functions have been changed of course to give it a more perl-like feel.
Remember think perl think parallel! Good Luck!
<<lessSYNOPSIS
use Parallel::Pvm;
The PVM message passing system enables a programmer to configure a group of (possibly heterogenous) computers connected by a network into a parallel virtual machine. The system was developed by the University of Tennessee, Oak Ridge National Laboratory and Emory University.
Using PVM, applications can be developed which spawns parallel processes onto nodes in the virtual machine to perform specific tasks. These parallel tasks can also periodically exchange information using a set of message passing functions developed for the system.
PVM applications have mostly been developed in the scientific and engineering fields. However applications for real-time and client/server systems can also be developed. PVM simply provides a convenient way for managing parallel tasks and communications without need for rexec or socket level programming.
As a utility, PVM enables an organisation to leverage on the computers already available for parallel processing. Parallel applications can be started during non-peak hours to utilise idle CPU cycles. Or dedicated workstation clusters connected via a high performance network like ATM can be used for high performance computing.
It is recommended that you read the PVM manual pages and the book "PVM: Parallel Virtual Machine, A userss guide and tutorial for networked parallel computing". Both the PVM system and the book can be obtained from the HTTP address http://www.epm.ornl.gov/pvm.
For the rest of this document we will provide a tutorial introduction to developing PVM applications using perl. The interface for some of the PVM functions have been changed of course to give it a more perl-like feel.
Remember think perl think parallel! Good Luck!
Download (0.019MB)
Added: 2007-04-18 License: Perl Artistic License Price:
931 downloads
DS1624 parallel port thermometer 0.4
DS1624 parallel port thermometer is a simple driver for a thermometer device. more>>
DS1624 parallel port thermometer is a simple driver for a thermometer device based on DS1624 and connected to the computer via one of the parallel ports.
The hardware board is inspired by a project by Christophe G.
Enhancements:
- A parallel port to I2C converter schematic was added.
- The project page was cleaned up.
<<lessThe hardware board is inspired by a project by Christophe G.
Enhancements:
- A parallel port to I2C converter schematic was added.
- The project page was cleaned up.
Download (0.006MB)
Added: 2005-12-27 License: GPL (GNU General Public License) Price:
1407 downloads
ParallelKnoppix 2.7
ParallelKnoppix is a remastered edition of Knoppix. more>>
ParallelKnoppix is a remaster of the Knoppix live CD distibution of GNU Linux that allows setting up a cluster of machines for parallel processing using the LAM-MPI and/or MPICH implementations of MPI.
You can convert a room full of machines running Windows into a Linux cluster, and when you shut down, your Windows machines are in their original state. The computers in the cluster can be homogeneous or heterogeneous.
Getting the cluster up and running takes about 5 minutes, if the machines have PXE network cards. Clusters from 2 to 200 machines are supported.
<<lessYou can convert a room full of machines running Windows into a Linux cluster, and when you shut down, your Windows machines are in their original state. The computers in the cluster can be homogeneous or heterogeneous.
Getting the cluster up and running takes about 5 minutes, if the machines have PXE network cards. Clusters from 2 to 200 machines are supported.
Download (650.2MB)
Added: 2007-07-13 License: GPL (GNU General Public License) Price:
841 downloads
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