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Firestorm 0.5.5
Firestorm is an extremely high performance network intrusion detection system (NIDS). more>>
Firestorm is an extremely high performance network intrusion detection system (NIDS). At the moment it just a sensor but plans are to include real support for analysis, reporting, remote console and on-the-fly sensor configuration. It is fully pluggable and hence extremely flexible. Firestorm performs a lot better than all other systems I have tested (such as snort and prelude) by as much as a factor of 2 (and thats under favourable conditions, it way outstrips the competition under a targeted DoS attack).
A Network Intrusion Detection System is a system which can identify suspicious patterns in network traffic. If a firewall is a doorman, a NIDS is an undercover KGB agent. He silently gathers intelligence and can watch an enemy even if the door security has already let them in (maybe the enemy can make fake identification documents).
Tested Platforms
Linux 2.x
FreeBSD 4.x
OpenBSD
Solaris
Should compile and run on any mainstream UNIX really...
Main features:
- Protocol anomaly detection
- Full application layer decodes
- Fully pluggable
- High performance OS Specific capture module for Linux
- Capture from libpcap files (normal AND redhat extended)
- Packet decode engine fully supports encapsulation
- Decode plugins included for many protocols (see below)
- Comprehensive snort rule support
- Wu-Manber setwise string matching
- Easy to configure; just one config file
- Can run chroot and with lowered privs (when started as root)
- Can run as a realtime process (when started as root)
- Preprocessors to allow supplementary modes of detection (eg: anomaly)
- Full IP defragmentation (passes fragroute evasion tests)
- TCP stateful inspection with window tracking
- Intelligent TCP stream reassembly
- HTTP URL normalization
- EXTREMELY fast and scalable signature engine
- Configurable token-bucket rate-limiting of any alerts
- GNOME2 based analyst console user interface
- Enhanced logging format for ease of analysis
- ELOG indexing for lightning fast sorting and filtering of alerts
<<lessA Network Intrusion Detection System is a system which can identify suspicious patterns in network traffic. If a firewall is a doorman, a NIDS is an undercover KGB agent. He silently gathers intelligence and can watch an enemy even if the door security has already let them in (maybe the enemy can make fake identification documents).
Tested Platforms
Linux 2.x
FreeBSD 4.x
OpenBSD
Solaris
Should compile and run on any mainstream UNIX really...
Main features:
- Protocol anomaly detection
- Full application layer decodes
- Fully pluggable
- High performance OS Specific capture module for Linux
- Capture from libpcap files (normal AND redhat extended)
- Packet decode engine fully supports encapsulation
- Decode plugins included for many protocols (see below)
- Comprehensive snort rule support
- Wu-Manber setwise string matching
- Easy to configure; just one config file
- Can run chroot and with lowered privs (when started as root)
- Can run as a realtime process (when started as root)
- Preprocessors to allow supplementary modes of detection (eg: anomaly)
- Full IP defragmentation (passes fragroute evasion tests)
- TCP stateful inspection with window tracking
- Intelligent TCP stream reassembly
- HTTP URL normalization
- EXTREMELY fast and scalable signature engine
- Configurable token-bucket rate-limiting of any alerts
- GNOME2 based analyst console user interface
- Enhanced logging format for ease of analysis
- ELOG indexing for lightning fast sorting and filtering of alerts
Download (0.22MB)
Added: 2006-07-07 License: GPL (GNU General Public License) Price:
1208 downloads
Rocks Cluster 4.3
Rocks Cluster Tool Kit is a Turnkey Linux COTS Clusters for x86 and IA64. more>>
Rocks Cluster is a complete "cluster on a CD" solution for x86 and IA64 Red Hat Linux COTS clusters.
Building a Rocks cluster does not require any experience in clustering, yet a cluster architect will find a flexible and programmatic way to redesign the entire software stack just below the surface (appropriately hidden from the majority of users).
Although Rocks includes the tools expected from any clustering software stack (PBS, Maui, GM support, Ganglia, etc), it is unique in its simplicity of installation.
From a hardware component and raw processing power perspective, commodity clusters are phenomenal price/performance compute engines. However, if a scalable ``cluster management strategy is not adopted, the favorable economics of clusters are offset by the additional on-going personnel costs involved to ``care and feed for the machine. The complexity of cluster management (e.g., determining if all nodes have a consistent set of software) often overwhelms part-time cluster administrators, who are usually domain application scientists. When this occurs, machine state is forced to either of two extremes: the cluster is not stable due to configuration problems, or software becomes stale, security holes abound, and known software bugs remain unpatched.
While earlier clustering toolkits expend a great deal of effort (i.e., software) to compare configurations of nodes, Rocks makes complete Operating System (OS) installation on a node the basic management tool. With attention to complete automation of this process, it becomes faster to reinstall all nodes to a known configuration than it is to determine if nodes were out of synchronization in the first place. Unlike a users desktop, the OS on a cluster node is considered to be soft state that can be changed and/or updated rapidly.
This is clearly more heavywieght than the philosophy of configuration management tools [Cfengine] that perform exhaustive examination and parity checking of an installed OS. At first glance, it seems wrong to reinstall the OS when a configuration parameter needs to be changed. Indeed, for a single node this might seem too severe. However, this approach scales exceptionally well, making it a preferred mode for even a modest-sized cluster. Because the OS can be installed from scratch in a short period of time, different (and perhaps incompatible) application-specific configurations can easily be installed on nodes. In addition, this structure insures any upgrade will not interfere with actively running jobs.
One of the key ingredients of Rocks is a robust mechanism to produce customized distributions (with security patches pre-applied) that define the complete set of software for a particular node. A cluster may require several node types including compute nodes, frontend nodes file servers, and monitoring nodes. Each of these roles requires a specialized software set. Within a distribution, different node types are defined with a machine specific Red Hat Kickstart file, made from a Rocks Kickstart Graph.
A Kickstart file is a text-based description of all the software packages and software configuration to be deployed on a node. The Rocks Kickstart Graph is an XML-based tree structure used to define RedHat Kickstart files. By using a graph, Rocks can efficiently define node types without duplicating shared components. Similiar to mammalian species sharing 80% of their genes, Rocks node types share much of their software set. The Rocks Kickstart Graph easily defines the differences between node types without duplicating the description of their similarities. See the Bibliography section for papers that describe the design of this structure in more depth.
By leveraging this installation technology, we can abstract out many of the hardware differences and allow the Kickstart process to autodetect the correct hardware modules to load (e.g., disk subsystem type: SCSI, IDE, integrated RAID adapter; Ethernet interfaces; and high-speed network interfaces). Further, we benefit from the robust and rich support that commercial Linux distributions must have to be viable in todays rapidly advancing marketplace.
Wherever possible, Rocks uses automatic methods to determine configuration differences. Yet, because clusters are unified machines, there are a few services that require ``global knowledge of the machine -- e.g., a listing of all compute nodes for the hosts database and queuing system. Rocks uses an SQL database to store the definitions of these global configurations and then generates database reports to create service-specific configuration files (e.g., DHCP configuration file, /etc/hosts, and PBS nodes file).
Enhancements:
- Rocks v4.3 is released for i386 and x86_64 CPU architectures. New features: Rocks command line - initial release of the Rocks command line which facilitates non-SQL administrative access to the database; PXE First - hosts can now be configured in BIOS with a boot order of CD, PXE, hard disk. Enhancements: based on CentOS 4.5 and all updates as of July 4, 2007; Anaconda installer updated to 10.1.1.63; performance improvement when building torrent files for the Avalanche Installer; database indirects, more flexibility with Rocks variables; Globus updated to gt4.0.4 with web services....
<<lessBuilding a Rocks cluster does not require any experience in clustering, yet a cluster architect will find a flexible and programmatic way to redesign the entire software stack just below the surface (appropriately hidden from the majority of users).
Although Rocks includes the tools expected from any clustering software stack (PBS, Maui, GM support, Ganglia, etc), it is unique in its simplicity of installation.
From a hardware component and raw processing power perspective, commodity clusters are phenomenal price/performance compute engines. However, if a scalable ``cluster management strategy is not adopted, the favorable economics of clusters are offset by the additional on-going personnel costs involved to ``care and feed for the machine. The complexity of cluster management (e.g., determining if all nodes have a consistent set of software) often overwhelms part-time cluster administrators, who are usually domain application scientists. When this occurs, machine state is forced to either of two extremes: the cluster is not stable due to configuration problems, or software becomes stale, security holes abound, and known software bugs remain unpatched.
While earlier clustering toolkits expend a great deal of effort (i.e., software) to compare configurations of nodes, Rocks makes complete Operating System (OS) installation on a node the basic management tool. With attention to complete automation of this process, it becomes faster to reinstall all nodes to a known configuration than it is to determine if nodes were out of synchronization in the first place. Unlike a users desktop, the OS on a cluster node is considered to be soft state that can be changed and/or updated rapidly.
This is clearly more heavywieght than the philosophy of configuration management tools [Cfengine] that perform exhaustive examination and parity checking of an installed OS. At first glance, it seems wrong to reinstall the OS when a configuration parameter needs to be changed. Indeed, for a single node this might seem too severe. However, this approach scales exceptionally well, making it a preferred mode for even a modest-sized cluster. Because the OS can be installed from scratch in a short period of time, different (and perhaps incompatible) application-specific configurations can easily be installed on nodes. In addition, this structure insures any upgrade will not interfere with actively running jobs.
One of the key ingredients of Rocks is a robust mechanism to produce customized distributions (with security patches pre-applied) that define the complete set of software for a particular node. A cluster may require several node types including compute nodes, frontend nodes file servers, and monitoring nodes. Each of these roles requires a specialized software set. Within a distribution, different node types are defined with a machine specific Red Hat Kickstart file, made from a Rocks Kickstart Graph.
A Kickstart file is a text-based description of all the software packages and software configuration to be deployed on a node. The Rocks Kickstart Graph is an XML-based tree structure used to define RedHat Kickstart files. By using a graph, Rocks can efficiently define node types without duplicating shared components. Similiar to mammalian species sharing 80% of their genes, Rocks node types share much of their software set. The Rocks Kickstart Graph easily defines the differences between node types without duplicating the description of their similarities. See the Bibliography section for papers that describe the design of this structure in more depth.
By leveraging this installation technology, we can abstract out many of the hardware differences and allow the Kickstart process to autodetect the correct hardware modules to load (e.g., disk subsystem type: SCSI, IDE, integrated RAID adapter; Ethernet interfaces; and high-speed network interfaces). Further, we benefit from the robust and rich support that commercial Linux distributions must have to be viable in todays rapidly advancing marketplace.
Wherever possible, Rocks uses automatic methods to determine configuration differences. Yet, because clusters are unified machines, there are a few services that require ``global knowledge of the machine -- e.g., a listing of all compute nodes for the hosts database and queuing system. Rocks uses an SQL database to store the definitions of these global configurations and then generates database reports to create service-specific configuration files (e.g., DHCP configuration file, /etc/hosts, and PBS nodes file).
Enhancements:
- Rocks v4.3 is released for i386 and x86_64 CPU architectures. New features: Rocks command line - initial release of the Rocks command line which facilitates non-SQL administrative access to the database; PXE First - hosts can now be configured in BIOS with a boot order of CD, PXE, hard disk. Enhancements: based on CentOS 4.5 and all updates as of July 4, 2007; Anaconda installer updated to 10.1.1.63; performance improvement when building torrent files for the Avalanche Installer; database indirects, more flexibility with Rocks variables; Globus updated to gt4.0.4 with web services....
Download (601MB)
Added: 2007-07-07 License: BSD License Price:
511 downloads
blueMarine 0.9.RC1
blueMarine project is about an open source workflow for digital photography. more>>
blueMarine project is about an open source workflow for digital photography.
What does it mean?
Start thinking of an opensource application like Aperture or Lightroom that enables you to organize, develop, print and publish your photos. Pretty standard stuff nowadays. Opensource, at first sight, means that the application is free. Now think of an application written with the Java™ language: the application runs everywhere, Mac OS X, Linux, Windows. Now think of a community of people that adds code, plugins, crazy ideas, integrating some of the latest, cool technologies around, such as GPS positioning or geo-mapping.
Well, this is just the core concept of the blueMarine project.
Lets go on and lets think of the workflow. For the existing commercial applications the workflow starts just after shooting the photo and ends with a print on paper, the photo archived and maybe a web gallery published.
Just for a starter, we could do these things in innovative ways. For instance, trip reports could take advantage of GPS positioning data and Google Maps. Galleries could be presented in form of a virtual 3d gallery with walls and pictures hang on them.
Thinking of it twice, there are holes in workflows supported by current commercial applications. For instance, if you want to filter your images with a sophisticated noise reduction algorithm or if you want to create a bigger composite photo out of several shots, you likely have to use an external application. Some communities, such as amateur astrophotographers, need some very special processing that is usually performed by means of specific software. Wouldnt be better to have all of these facilities integrated in a single front end?
Now, lets broaden our workflow horizon. It can extend well beyond the print or the archival. For instance, an ornithologist usually manages field notes about the bird observed and photographed: directly binding them to photos and maybe GPS positioning data is much better than keeping a separate Excel sheet. It can also start much before shooting the photo. Think of trip planning: maybe you travel to nice places and spot interesting subjects, but not all the conditions are favorable: the weather, the light, the sun position, or the season (snow, blossomed flowers, foliage colors). Maybe you take some photos but at home you decide: hey, Im going to return there next Fall when the trees are reddish. Wouldnt be cool if a software application could allow you to easily manage all of these wanna-shoot-again photos, maybe providing assistance to guess which will be the sun position in a certain day and hour and integrating weather forecasts? And synthetising a trip program that can be uploaded on your palm gear?
Theres a further point with opensource photo workflow. Its related to the world of camera raw formats, that is the way professional DSLR cameras work. They provide you with the raw bits from the sensor that need to be extensively cooked, or developed, for getting a good image. This approach gives a tremendous amount of control to the photographers - too bad that most formats are proprietary and not documented. blueMarine supports the OpenRAW initiative and provide an opensource implementation of developing tools for camera raw formats from an ever increasing number of vendors.
Well, all of this and more is the aim of the blueMarine project.
<<lessWhat does it mean?
Start thinking of an opensource application like Aperture or Lightroom that enables you to organize, develop, print and publish your photos. Pretty standard stuff nowadays. Opensource, at first sight, means that the application is free. Now think of an application written with the Java™ language: the application runs everywhere, Mac OS X, Linux, Windows. Now think of a community of people that adds code, plugins, crazy ideas, integrating some of the latest, cool technologies around, such as GPS positioning or geo-mapping.
Well, this is just the core concept of the blueMarine project.
Lets go on and lets think of the workflow. For the existing commercial applications the workflow starts just after shooting the photo and ends with a print on paper, the photo archived and maybe a web gallery published.
Just for a starter, we could do these things in innovative ways. For instance, trip reports could take advantage of GPS positioning data and Google Maps. Galleries could be presented in form of a virtual 3d gallery with walls and pictures hang on them.
Thinking of it twice, there are holes in workflows supported by current commercial applications. For instance, if you want to filter your images with a sophisticated noise reduction algorithm or if you want to create a bigger composite photo out of several shots, you likely have to use an external application. Some communities, such as amateur astrophotographers, need some very special processing that is usually performed by means of specific software. Wouldnt be better to have all of these facilities integrated in a single front end?
Now, lets broaden our workflow horizon. It can extend well beyond the print or the archival. For instance, an ornithologist usually manages field notes about the bird observed and photographed: directly binding them to photos and maybe GPS positioning data is much better than keeping a separate Excel sheet. It can also start much before shooting the photo. Think of trip planning: maybe you travel to nice places and spot interesting subjects, but not all the conditions are favorable: the weather, the light, the sun position, or the season (snow, blossomed flowers, foliage colors). Maybe you take some photos but at home you decide: hey, Im going to return there next Fall when the trees are reddish. Wouldnt be cool if a software application could allow you to easily manage all of these wanna-shoot-again photos, maybe providing assistance to guess which will be the sun position in a certain day and hour and integrating weather forecasts? And synthetising a trip program that can be uploaded on your palm gear?
Theres a further point with opensource photo workflow. Its related to the world of camera raw formats, that is the way professional DSLR cameras work. They provide you with the raw bits from the sensor that need to be extensively cooked, or developed, for getting a good image. This approach gives a tremendous amount of control to the photographers - too bad that most formats are proprietary and not documented. blueMarine supports the OpenRAW initiative and provide an opensource implementation of developing tools for camera raw formats from an ever increasing number of vendors.
Well, all of this and more is the aim of the blueMarine project.
Download (18.7MB)
Added: 2007-08-10 License: MIT/X Consortium License Price:
807 downloads
Network Transparent Widgets 0.3.2
Network Transparent Widgets is a protocol and application framework. more>>
Network Transparent Widgets short from NTW, is a protocol and application framework that allows a single server to serve thousands of remote GUI applications.
The client applications are nearly indistinguishable from local, native applications. The protocol is language and architecture neutral. Server language bindings for C and Java are in heavy development.
Main features:
Speed: Remote apps can run at a speed which is nearly indistinguishable from a locally running application. Since the client draws the widgets natively, its not necessary to transfer graphical data, only widget state data. This can be done asynchronously, so the responsiveness of the UI never suffers.
Persistence: Its just as easy to write the ntw protocol data to disk as it is to the network, so the state of the entire gui application can be easily saved. This also happens transparently, so the developer doesnt have to spend any time loading and saving data. Also, if a network connection dies or the client computer loses power, the application can be restarted from the point of failure at the next connection.
Portability: using the protocol, an ntw server application running on a Unix machine could talk to an ntw client for Windows, and vice versa. So a developer could write a program on Linux that could be run from any OS without any porting necessary. Any language or platform that can read and write data to a network can use the protocol to create gui apps.
Scalability: Since the ntw server does not store or draw widget graphics, the memory and computational overhead of running an ntw application is much less than a comparable X Window application. A low end machine could easily serve hundreds of remote clients.
Productivity: Users can run ntw apps without installing anything but the client. Developers can release new versions of their apps without the users having to do anything, much like a web page.
Reference Implementation:
The current reference implementation of the client implements most of the widgets in the Gtk toolkit, and is written in C using the GTK+ 2.0 toolkit for drawing the widgets and handling events. It compiles and runs on FreeBSD, Linux, and Windows, and likely other Unix variants also. Youll need the GTK+ toolkit installed to run the client, and the GTK+ development headers to compile it.
The source code also include a server reference implementation and a sample server application. The "server" is really a set of C language bindings to functions that create and send ntw widget data. The bindings can be used in much the same way as any other GUI toolkit. See the file "ntwtest.c" for the example application. Its been tested on FreeBSD, Linux, and Windows XP. The server library should compile and run on most systems with a C compiler and support for sockets, without the need for any additional libraries.
The protocol is defined by the two header files, ntw.h and ntw_signals.h. These are C header files that describe exactly the byte layout for each of the widgets and all of the opcodes and events that can be sent.
There are still some widgets missing, and some of the signals raised by GTK are not yet handled in the protocol. This will be fixed in the near future.
Note: Although the reference implementation is coded in GTK, the NTW protocol is designed to be independent of any particular widget toolkit. GTK was picked due to favorable design features and a favorable license.
Enhancements:
- 02JUL06 - Fixed bug in update.c where spin_button was switched with slider
- 02JUL06 - Removed status field from image_buffer widget protocol
<<lessThe client applications are nearly indistinguishable from local, native applications. The protocol is language and architecture neutral. Server language bindings for C and Java are in heavy development.
Main features:
Speed: Remote apps can run at a speed which is nearly indistinguishable from a locally running application. Since the client draws the widgets natively, its not necessary to transfer graphical data, only widget state data. This can be done asynchronously, so the responsiveness of the UI never suffers.
Persistence: Its just as easy to write the ntw protocol data to disk as it is to the network, so the state of the entire gui application can be easily saved. This also happens transparently, so the developer doesnt have to spend any time loading and saving data. Also, if a network connection dies or the client computer loses power, the application can be restarted from the point of failure at the next connection.
Portability: using the protocol, an ntw server application running on a Unix machine could talk to an ntw client for Windows, and vice versa. So a developer could write a program on Linux that could be run from any OS without any porting necessary. Any language or platform that can read and write data to a network can use the protocol to create gui apps.
Scalability: Since the ntw server does not store or draw widget graphics, the memory and computational overhead of running an ntw application is much less than a comparable X Window application. A low end machine could easily serve hundreds of remote clients.
Productivity: Users can run ntw apps without installing anything but the client. Developers can release new versions of their apps without the users having to do anything, much like a web page.
Reference Implementation:
The current reference implementation of the client implements most of the widgets in the Gtk toolkit, and is written in C using the GTK+ 2.0 toolkit for drawing the widgets and handling events. It compiles and runs on FreeBSD, Linux, and Windows, and likely other Unix variants also. Youll need the GTK+ toolkit installed to run the client, and the GTK+ development headers to compile it.
The source code also include a server reference implementation and a sample server application. The "server" is really a set of C language bindings to functions that create and send ntw widget data. The bindings can be used in much the same way as any other GUI toolkit. See the file "ntwtest.c" for the example application. Its been tested on FreeBSD, Linux, and Windows XP. The server library should compile and run on most systems with a C compiler and support for sockets, without the need for any additional libraries.
The protocol is defined by the two header files, ntw.h and ntw_signals.h. These are C header files that describe exactly the byte layout for each of the widgets and all of the opcodes and events that can be sent.
There are still some widgets missing, and some of the signals raised by GTK are not yet handled in the protocol. This will be fixed in the near future.
Note: Although the reference implementation is coded in GTK, the NTW protocol is designed to be independent of any particular widget toolkit. GTK was picked due to favorable design features and a favorable license.
Enhancements:
- 02JUL06 - Fixed bug in update.c where spin_button was switched with slider
- 02JUL06 - Removed status field from image_buffer widget protocol
Download (0.65MB)
Added: 2006-07-04 License: MIT/X Consortium License Price:
1209 downloads
RenderDotC 3.4
RenderDotC project is a world class photorealistic renderer designed to meet the demands of special effects for film. more>>
RenderDotC project is a world class photorealistic renderer designed to meet the demands of special effects for film. The primary reason people give for choosing RenderDotC is its favorable price per performance ratio. Moreover, RenderDotC scores high marks on everything that matters for a production renderer:
Main features:
Image Quality
- Images produced with RenderDotC possess that indescribable yet beautiful quality that some people refer to as "the RenderMan look". All phenomena that are prone to aliasing artifacts are effectively anti-aliased and noise is kept to a minimum.
Speed
- RenderDotC was designed in the 1990s to take advantage of the current hardware and software technologies. Its CPU and memory performance is unsurpassed by all renderers in its class.
Robustness
- There are hundreds of details to get right when developing a renderer and that only comes with maturity. RenderDotC has been shipping since 1996 and has proven itself on complex scenes from feature films from The Matrix to Orange County.
Features
- The RenderMan standard prescribes a rich set of geometric primitives and features. RenderDotC provides all of these plus some exclusive features such as NURB curves, DSO shadeops that can call built-in functions, and complete support for extended headroom rendering.
Flexibility
- Being RenderMan-compliant, RenderDotC supports user-programmable shading. It also has other plug-in interfaces including DSO shadeops, procedural primitives, and display drivers. Since shading is decoupled from hiding, one can easily tune the speed/quality tradeoffs of each.
Price
- RenderDotC is priced competitively for both the film and broadcast markets. When considering price, its important to take into account speed. A faster renderer means that the same number of frames can be produced per hour with a smaller render farm. Fewer computers to purchase and maintain further reduces the bottom line.
Support
- As a company, Dot C Software has been around since 1992. Our customers needs come first and we have the agility to respond to requests quickly. The people who wrote RenderDotC are the same ones that provide customer support. At Dot C we make software, period. We do not compete with our customers in the arena of computer graphics production.
Enhancements:
- Improved statistical output.
- Optional non raster-oriented dicing.
- The ability to specify motion factor as a dicing attribute, and user-defined placement of output on X.
- The Windows installer now sets up the environment.
<<lessMain features:
Image Quality
- Images produced with RenderDotC possess that indescribable yet beautiful quality that some people refer to as "the RenderMan look". All phenomena that are prone to aliasing artifacts are effectively anti-aliased and noise is kept to a minimum.
Speed
- RenderDotC was designed in the 1990s to take advantage of the current hardware and software technologies. Its CPU and memory performance is unsurpassed by all renderers in its class.
Robustness
- There are hundreds of details to get right when developing a renderer and that only comes with maturity. RenderDotC has been shipping since 1996 and has proven itself on complex scenes from feature films from The Matrix to Orange County.
Features
- The RenderMan standard prescribes a rich set of geometric primitives and features. RenderDotC provides all of these plus some exclusive features such as NURB curves, DSO shadeops that can call built-in functions, and complete support for extended headroom rendering.
Flexibility
- Being RenderMan-compliant, RenderDotC supports user-programmable shading. It also has other plug-in interfaces including DSO shadeops, procedural primitives, and display drivers. Since shading is decoupled from hiding, one can easily tune the speed/quality tradeoffs of each.
Price
- RenderDotC is priced competitively for both the film and broadcast markets. When considering price, its important to take into account speed. A faster renderer means that the same number of frames can be produced per hour with a smaller render farm. Fewer computers to purchase and maintain further reduces the bottom line.
Support
- As a company, Dot C Software has been around since 1992. Our customers needs come first and we have the agility to respond to requests quickly. The people who wrote RenderDotC are the same ones that provide customer support. At Dot C we make software, period. We do not compete with our customers in the arena of computer graphics production.
Enhancements:
- Improved statistical output.
- Optional non raster-oriented dicing.
- The ability to specify motion factor as a dicing attribute, and user-defined placement of output on X.
- The Windows installer now sets up the environment.
Download (1.3MB)
Added: 2007-06-08 License: Other/Proprietary License Price:
869 downloads
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