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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
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
Parallel::ForkManager 0.7.5
Parallel::ForkManager is a simple parallel processing fork manager. more>>
Parallel::ForkManager is a simple parallel processing fork manager.
SYNOPSIS
use Parallel::ForkManager;
$pm = new Parallel::ForkManager($MAX_PROCESSES);
foreach $data (@all_data) {
# Forks and returns the pid for the child:
my $pid = $pm->start and next;
... do some work with $data in the child process ...
$pm->finish; # Terminates the child process
}
This module is intended for use in operations that can be done in parallel where the number of processes to be forked off should be limited. Typical use is a downloader which will be retrieving hundreds/thousands of files.
<<lessSYNOPSIS
use Parallel::ForkManager;
$pm = new Parallel::ForkManager($MAX_PROCESSES);
foreach $data (@all_data) {
# Forks and returns the pid for the child:
my $pid = $pm->start and next;
... do some work with $data in the child process ...
$pm->finish; # Terminates the child process
}
This module is intended for use in operations that can be done in parallel where the number of processes to be forked off should be limited. Typical use is a downloader which will be retrieving hundreds/thousands of files.
Download (0.006MB)
Added: 2007-04-18 License: Perl Artistic License Price:
931 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
Parallel port powerSwitch 0.1.1
Parallel port powerSwitch is a TCP/IP server to control a parallel port power switch. more>>
Parallel port powerSwitch project is a TCP/IP server to control a parallel port power switch.
pp_powerSwitch is a TCP/IP based server, which controls a power switching device through the parallel port. Besides Java, I used a bit C to handle the parallel port I/O.
I use it for controling heating, lamps, computers, coffee machine and other things (device has eight ports).
Main features:
- multiple connections
- user athorization
- cron-like scheduled switching
- reads configurations from file
- configurable log output
- simple port descriptions (add a short description to each port)
- remote shutdown
<<lesspp_powerSwitch is a TCP/IP based server, which controls a power switching device through the parallel port. Besides Java, I used a bit C to handle the parallel port I/O.
I use it for controling heating, lamps, computers, coffee machine and other things (device has eight ports).
Main features:
- multiple connections
- user athorization
- cron-like scheduled switching
- reads configurations from file
- configurable log output
- simple port descriptions (add a short description to each port)
- remote shutdown
Download (0.009MB)
Added: 2007-01-16 License: Freeware Price:
1016 downloads
Phonetic for mac 1.0
A program that translates text to the phonetic alphabet. more>> It is freeware with the source code avaliable. You can run it in Linux or Windows.
Phoneic finds words within telephone numbers. Phonetic also converts phonetic telephone numbers into numeric digits.
All words found within the given telephone number will be listed. If you click on a word, every combination in which that word is included will be displayed.<<less
Download (809.72MB)
Added: 2009-04-21 License: Freeware Price: Free
198 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
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 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::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
Parallel::Workers::Backend 0.0.7
Parallel::Workers::Backend - The backend is a plugins mechanism to run the worker tasks. more>>
Parallel::Workers::Backend - The backend is a plugins mechanism to run the worker tasks. Default plugins are implemented for Eval (CODE), SSH and XMLRPC tasks. You can add your own plugin with module name Parallel::Backend::YourTaskModule
SYNOPSIS
use Parallel::Workers::Backend;
my $worker=Parallel::Workers->new(backend=>"Eval");
my $worker=Parallel::Workers->new(backend=>"SSH");
my $worker=Parallel::Workers->new(backend=>"XMLRPC");
my $worker=Parallel::Workers->new(backend=>"YourTaskModule");
<<lessSYNOPSIS
use Parallel::Workers::Backend;
my $worker=Parallel::Workers->new(backend=>"Eval");
my $worker=Parallel::Workers->new(backend=>"SSH");
my $worker=Parallel::Workers->new(backend=>"XMLRPC");
my $worker=Parallel::Workers->new(backend=>"YourTaskModule");
Download (0.010MB)
Added: 2007-02-08 License: Perl Artistic License Price:
988 downloads
Parallel::Queue 1.00
Parallel::Queue is a Perl module to fork or thread a list of closures N-way parallel. more>>
Parallel::Queue is a Perl module to fork or thread a list of closures N-way parallel.
SYNOPSIS
# example queue:
# only squish files larger than 8KB in size. figure
# that the system can handle four copies of squish
# running at the same time without them interfering
# with one another.
my @queue = map { -s > 8192 ? sub{ squish $_ } : () } @filz;
# functional: pass in the count and list of coderefs.
#
# adding runqueue exports the subroutine into
# the current package. useful for non-OO situations.
#
# run the queue 4 way parallel.
use Parallel::Queue qw( runqueue verbose fork );
my @remaining = runqueue 4, @queue;
die "Incomplete jobs" if @remaining;
# OO: generate queue manager and use without the
# runqueue arguments, construct a queue manager,
# and use it to run the jobs
use Parallel::Queue;
my $quemgr = Parallel::Queue->construct( thread );
$quemgr->runqueue( 4, @queue );
die "Incomplete jobs" if @queue;
# call Parallel::Queue with the default configuration
# (fork quietly).
require Parallel::Queue;
Parallel::Queue->runqueue( 4, @queue );
# pre-define defaults for the objects: leave
# out runqueue, set the rest, and construct
# an object. the one here gets verbose, thread,
# and debug all set to true.
use Parallel::Queue qw( verbose thread );
my $quemgr = Parallel::Queue->construct( debug );
my @remaining = $quemgr->runqueue( 4, @queue );
Given a count and an array of coderefs (most likely closures), runqueue will run the jobs in parallel. The jobs can be run via fork or detached threads [see known issues for threading]. Jobs on the queue are executed until one of them exits non-zero, the fork/thread operation fails, or all of them are dispatched (i.e., the queue is empty).
<<lessSYNOPSIS
# example queue:
# only squish files larger than 8KB in size. figure
# that the system can handle four copies of squish
# running at the same time without them interfering
# with one another.
my @queue = map { -s > 8192 ? sub{ squish $_ } : () } @filz;
# functional: pass in the count and list of coderefs.
#
# adding runqueue exports the subroutine into
# the current package. useful for non-OO situations.
#
# run the queue 4 way parallel.
use Parallel::Queue qw( runqueue verbose fork );
my @remaining = runqueue 4, @queue;
die "Incomplete jobs" if @remaining;
# OO: generate queue manager and use without the
# runqueue arguments, construct a queue manager,
# and use it to run the jobs
use Parallel::Queue;
my $quemgr = Parallel::Queue->construct( thread );
$quemgr->runqueue( 4, @queue );
die "Incomplete jobs" if @queue;
# call Parallel::Queue with the default configuration
# (fork quietly).
require Parallel::Queue;
Parallel::Queue->runqueue( 4, @queue );
# pre-define defaults for the objects: leave
# out runqueue, set the rest, and construct
# an object. the one here gets verbose, thread,
# and debug all set to true.
use Parallel::Queue qw( verbose thread );
my $quemgr = Parallel::Queue->construct( debug );
my @remaining = $quemgr->runqueue( 4, @queue );
Given a count and an array of coderefs (most likely closures), runqueue will run the jobs in parallel. The jobs can be run via fork or detached threads [see known issues for threading]. Jobs on the queue are executed until one of them exits non-zero, the fork/thread operation fails, or all of them are dispatched (i.e., the queue is empty).
Download (0.008MB)
Added: 2007-04-18 License: Perl Artistic License Price:
919 downloads
Java Parallel Processing Framework 1.0 Beta 1
Java Parallel Processing Framework is a set of tools and APIs to facilitate the parallelization of CPU intensive applications. more>>
Java Parallel Processing Framework is a set of tools and APIs to facilitate the parallelization of CPU intensive applications, and distribute their execution over a network of heterogenous nodes.
Java Parallel Processing Framework is intended to run in clusters and grids.
Main features:
- an API to delegate the processing of parallelized tasks to local and remote execution services
- a set of APIs and user interface tools to administrate and monitor execution services
- real-time adaptive load balancing capabilities
- scalability up to an arbitrary number of processing nodes
- support for failover and recovery
- limited intrusiveness for existing or legacy code
- a dynamic deployment mechanism, that enables the execution of new, or updated, code without having to deploy onto the grid
- fully documented APIs, administration guide and developer guide
- runs on any platform supporting Java 2 Platform Standard Edition 5.0 (J2SE 1.5)
Enhancements:
- JPPF is now licensed under the terms of the Apache License, Version 2.0. Starting from JPPF 1.0 beta1, all releases will be licensed under these terms.
- Prior versions will remain under the terms of the LGPL.
- For the first time, JPPF integrates seamlessly with J2EE. The JPPF Resource Adapter provides J2EE application servers with an access to native grid services.
- Numerous bug fixes, especially with regards to the distributed class loading mechanism.
<<lessJava Parallel Processing Framework is intended to run in clusters and grids.
Main features:
- an API to delegate the processing of parallelized tasks to local and remote execution services
- a set of APIs and user interface tools to administrate and monitor execution services
- real-time adaptive load balancing capabilities
- scalability up to an arbitrary number of processing nodes
- support for failover and recovery
- limited intrusiveness for existing or legacy code
- a dynamic deployment mechanism, that enables the execution of new, or updated, code without having to deploy onto the grid
- fully documented APIs, administration guide and developer guide
- runs on any platform supporting Java 2 Platform Standard Edition 5.0 (J2SE 1.5)
Enhancements:
- JPPF is now licensed under the terms of the Apache License, Version 2.0. Starting from JPPF 1.0 beta1, all releases will be licensed under these terms.
- Prior versions will remain under the terms of the LGPL.
- For the first time, JPPF integrates seamlessly with J2EE. The JPPF Resource Adapter provides J2EE application servers with an access to native grid services.
- Numerous bug fixes, especially with regards to the distributed class loading mechanism.
Download (7.8MB)
Added: 2007-07-31 License: The Apache License 2.0 Price:
816 downloads
Parallel Genetic Algorithm Library 0.99
Parallel Genetic Algorithm Library is a C++ toolkit for producing genetic algorithm code. more>>
Parallel Genetic Algorithm Library (or PGAL for short) is a C++ toolkit for simply, efficiently, and swiftly producing genetic algorithm code that works across multiple processors.
This is useful not only for those with multi-processor computers, but also for distributed and cluster computing genetic algorithm environments such as openMosix.
<<lessThis is useful not only for those with multi-processor computers, but also for distributed and cluster computing genetic algorithm environments such as openMosix.
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Added: 2007-06-29 License: GPL (GNU General Public License) Price:
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