kgrid | required k-point density
kandi X-RAY | kgrid Summary
kandi X-RAY | kgrid Summary
The specified input file is read using Atomic Simulation Environment ([supported formats] If none is specified, looks for geometry.in (FHI-aims) in working directory. A k-point density is selected to satisfy a given length cutoff, as described by Moreno & Soler (1992)[1]. The length cutoff corresponds to a radius about repeated images that would be needed in a gamma-point supercell calculation to achieve the same sampling. This k-point grid is expressed as a number of samples in each lattice vector and passed to standard output. (Note that this is NOT a Moreno-Soler grid as it does not use symmetry information to minimise the required number of points. It is a uniform grid specified with the same length parameter notation.). Default k-point cutoff is 10Å (generally well-converged for semiconducting or insulating materials). Optional arguments are implemented with conventional GNU/POSIX syntax, including -h help option.
Support
Quality
Security
License
Reuse
Top functions reviewed by kandi - BETA
- Argument parser
- Calculate the k - tuple for a given cutoff point
- Calculate a k - point tuple from the lattice vectors
- Calculates the kpt points from the lattice vectors
- Generate a set of cutoff points from a lattice
- Given a list of lattice lengths return a tuple of increments
- Calculate a grid from a geometry file
- Calculate the ktuple from atoms
- Returns a list of kspacing points
- Generate a set of cutoff points
kgrid Key Features
kgrid Examples and Code Snippets
Community Discussions
Trending Discussions on kgrid
QUESTION
I'm a Computer Engineering student at Baskent University(Turkey,Ankara).
Can i use matlab k-wave toolbox codes in visual studio via like importing or creating the library or something, I need to know that for my Gradutation Project.
For example :
...ANSWER
Answered 2021-Apr-25 at 19:00it is not a trouble-free path, but you can use matlab engine, see examples here
basically, you call engEvalString() to run matlab commands inside an invisible matlab session in the backend.
if you just need a result, you can use system calls (ShellExecute orShellExecuteEx) and call
/path/to/matlab -nojvm -nodesktop < /path/to/yourscript.m > cmdoutput.txt
to invoke a matlab session.
QUESTION
I am replicating using Julia a sequence of steps originally made in Matlab. In Octave, this procedure takes 1.4582 seconds and in Julia (using Jupyter) it takes approximately 10 seconds. I'll try to be brief in the scripts. My goal is to achieve or improve Octave's performance. First of all, I will describe my variables and some function:
- zgrid (double 1x7 size)
- kgrid (double 500x1 size)
- V0 (double 500x7 size)
- P (double 7x7 size) a transition matrix
- delta and beta are fixed parameters.
- F(z,k) and u(c) are particular functions and are specified in the Julia script.
ANSWER
Answered 2021-Apr-03 at 02:05The following should perform much better. The most noticeable differences are that it calculates F 500x less, and doesn't rely on global variables.
QUESTION
ANSWER
Answered 2020-Dec-22 at 10:48It is not clear what the matrices agrid2 and fx are, however mu should be computed outside that for loop, since in the formula (1) it is not included in the summation. So, you should first compute mu, and then G.
Furthermore, from your code it seems that inside the function abs() you are considering f instead of a.
Also, I am pretty sure you need a double for loop, since there are two summations in (1).
QUESTION
I have been playing around with parallelization both using ACC and OpenMP in Fortran. I am now trying to do the same in matlab. I find it very interesting that it seems to be very hard to paralelize a loop using GPUs in matlab. Apparently the only way to do it is to by using arrayfun function. But I might be wrong.
At a conceptual level, I am wondering why is the GPU usage in matlab not more straightforward than in fortran. At a more practical level, I am wondering how to use GPUs on the simple code below.
Below, I am sharing three codes and benchmarks:
- Fortran OpenMP code
- Fortran ACC code
- Matlab parfor code
- Matlab CUDA (?) this is the one I don't know how to do.
Fortran OpenMP:
...ANSWER
Answered 2018-Dec-03 at 22:47So, this bit is what is going to mess you up on this project. MATLAB stands for Matrix Laboratory. Vectors and matrices are kind of its thing. The number 1 way to optimize anything in MATLAB is to vectorize it. For this reason, when using performance enhancing tools like CUDA, MATLAB assumes that you are going to vectorize your inputs if possible. Given the primacy of vectorizing inputs in the MATLAB coding style, it is not a fair comparison to assess its performance using only loops. It would be like assessing the performance of C++ while refusing to use pointers. If you want to use CUDA with MATLAB, the main way to go about it is to vectorize your inputs and use gpuarray. Honestly, I haven't looked too hard at your code but it kind of looks like your inputs are already mostly vectorized. You may be able to get away with something as simple as gpuarray(1:nk) or kgrid=gpuarray(linspace(...).
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install kgrid
the --user flag is highly recommended and avoids the need for administrator privileges, but on a somewhat unhealthy Python installation the user packages location may not be on your paths yet.
the -e flag creates an "editable" installation which links to this repository and enables easy updates with git.
Support
Reuse Trending Solutions
Find, review, and download reusable Libraries, Code Snippets, Cloud APIs from over 650 million Knowledge Items
Find more librariesStay Updated
Subscribe to our newsletter for trending solutions and developer bootcamps
Share this Page
