Free energy software for linux

Geant4 project is a toolkit for the simulation of the passage of particles through matter.
Its application areas include high energy physics and nuclear experiments, medical, accelerator and space physics studies.
Enhancements:
- Major updates to models and model APIs, major updates to many examples, and numerous bugfixes.

OpenScientist is an integration of open source products working together to do scientific visualization and data analysis, in particular for high energy physics (HEP).
The project is definitely NOT one million lines of intricated and unnecessary complicated home made code reinventing everything.
Motivations
Experiments in high energy and nuclear physics need to be at the edge of computing technologies but at the same time have to face a very long life time (LHC experiments are going to be a matter of decades). This involves that the software must be organized in a way that permits to include or discard some technologies in an easy way without having to recode everything at each change of a piece.
For data analysis, the HEP community had used the CERN/PAW tool for years. Whilst this program had been used and is probably still used by hundred of physicists in the world, it is not any more maintained by the lab that created and promoted it : CERN. This lab had not been able to establish long term collaborative software engineering plans in order to have a technical follow up of this program and analysis tools in general. (What is astounding, is that the same people that were behind CERN/PAW come now with another tool (ROOT) which has exactly the same engineering defects).
OpenScientist is first of all an architecture trying to handle the problem differently to avoid upseting huge software phase transitions in the future. The key points of the system are the modularity and the openness. See the Languages, Coarse graining architecture, and The file formats intrinsic pain section for more about the technical choices and design.
Enhancements:
- An HDF5 driver was introduced in BatchLab.
- The build system was replaced with obuild.
- Support for CoinPython was added.
- Initial support was added for both Qt4 and SDL.
- Examples were added.
- Assorted code cleanups and speedups were done.

tk_docapp project is a small GUI for mounting devices and ACPI energy monitoring under NetBSD.

User of other *nix operating systems can only use the mount option.

Template::Recall is a "Reverse callback" templating system.



SYNOPSIS

use Template::Recall;

my $tr = Template::Recall->new( template_path => /path/to/template/sections );

my @prods = (
soda,sugary goodness,$.99,
energy drink,jittery goodness,$1.99,
green tea,wholesome goodness,$1.59
);

$tr->render(header);

# Load template into memory

$tr->preload(prodrow);

for (@prods)
{
my %h;
my @a = split(/,/, $_);

$h{product} = $a[0];
$h{description} = $a[1];
$h{price} = $a[2];

print $tr->render(prodrow, %h);
}

# Remove template from memory

$tr->unload(prodrows);

print $tr->render(footer);

Template::Recall works using what I call a "reverse callback" approach. A "callback" templating system (i.e. Mason, Apache::ASP) generally includes template markup and code in the same file. The template "calls" out to the code where needed. Template::Recall works in reverse. Rather than inserting code inside the template, the template remains separate, but broken into sections. The sections are called from within the code at the appropriate times.

ParaView project is an application designed with the need to visualize large data sets in mind. The goals of the ParaView project include the following:
- Develop an open-source, multi-platform visualization application.
- Support distributed computation models to process large data sets.
- Create an open, flexible, and intuitive user interface.
- Develop an extensible architecture based on open standards.
ParaView runs on distributed and shared memory parallel as well as single processor systems and has been succesfully tested on Windows, Linux and various Unix workstations and clusters. Under the hood, ParaView uses the Visualization Toolkit as the data processing and rendering engine and has a user interface written using a unique blend of Tcl/Tk and C++. Please go here for a detailed list of features.
ParaView was created by Kitware in conjunction with Jim Ahrens of the Advanced Computing Laboratory at Los Alamos National Laboratory (LANL). Contributors and developers of ParaView currently include: Kitware, LANL, Sandia National Laboratories, and Army Research Laboratory. ParaView is funded by the US Department of Energy ASCI Views program as part of a three-year contract awarded to Kitware, Inc. by a consortium of three National Labs - Los Alamos, Sandia, and Livermore. The goal of the project is to develop scalable parallel processing tools with an emphasis on distributed memory implementations. The project includes parallel algorithms, infrastructure, I/O, support, and display devices. One significant feature of the contract is that all software developed is to be delivered open source. Hence ParaView is available as an open-source system.
Main features:
- Handles structured (uniform rectilinear, non-uniform rectilinear, and curvilinear grids), unstructured, polygonal and image data.
- All processing operations (filters) produce datasets. This allows the user to either further process or save as a data file the result of every operation. For example, the user can extract a cut surface, reduce the number of points on this surface by masking, and apply glyphs (for example, vector arrows) to the result.
- Contours and isosurfaces can be extracted from all data types using scalars or vector components. The results can be colored by any other variable or processed further. When possible, structured data contours/isosurfaces are extracted with fast and efficient algorithms which make use of the special data layout.
- Vectors fields can be inspected by applying glyphs (arrows, cones, lines, spheres, and various 2D glyphs) to the points in a dataset. The glyphs can be scaled by scalars, vector component or vector magnitude and can be oriented using a vector field.
- A sub-region of a dataset can be extracted by cutting or clipping with an arbitrary plane (all data types), specifying a threshold criteria to exclude cells (all data types) and/or specifying a VOI (volume of interest - structured data types only)
- Streamlines can be generated using constant step or adaptive integrators. The results can be displayed as points, lines, tubes, ribbons, etc., and can be processed by a multitude of filters.
- The points in a dataset can be warped (displaced) with scalars (given a user defined displacement vector) or with vectors (unavailable for non-linear rectilinear grids).
- With the array calculator, new variables can be computed using existing point or cell field arrays. A multitude of scalar and vector operations are supported.
- Data can be probed at a point or along a line. The results are displayed either graphically or as text and can be exported for further analysis.
- ParaView provides many other data sources and filters by default (edge extraction, surface extraction, reflection, decimation, extrusion, smoothing...) and any VTK filter can be added by providing a simple XML description (VTK provides hundreds of sources and filters, see VTK documentation for a complete list).
Enhancements:
- This release adds parallel uniform rectilinear grid volume rendering (vtkImageData).
- It introduces new algorithms for parallel unstructured grid volume rendering.
- Support for hardware accelerated offscreen rendering using OpenGL framebuffers.
- Improved multi-block support.
- Improved AMR support.
- Animation saving with ffmpeg.
- Filters have been added for FLUENT, OpenFOAM, MFIX, LSDyna, and AcuSolve.
- A gradient filter for unstructured data.
- Many other enhancements and bugfixes.