mlxd / gpue Goto Github PK
View Code? Open in Web Editor NEWGPU Gross-Pitaevskii Equation numerical solver for rapidly rotating Bose-Einstein condensates. Further development and maintenance from https://github.com/GPUE-group/GPUE
License: Other
GPU Gross-Pitaevskii Equation numerical solver for rapidly rotating Bose-Einstein condensates. Further development and maintenance from https://github.com/GPUE-group/GPUE
License: Other
Following the move to std::vector the tracking seems perfectly sane, but tends to locate hundreds of vortices at unexpected times during the evolution. This may likely be a sizing issue with the radial masking, but previous attempts to examine did not rectify. Need to investigate further.
Use the symmetry of the split-operator method to remove unnecessary transforms between evolution steps. Will require a re-working of the angular momentum section.
Perform half step into the algorithm, then perform the remaining evolution in full steps, until time to print out a wavefunction, when the half-step out is required.
Will remove some unneeded FFT's, multiplications and scalings per evolution step.
The transfers should be faster for the printout, and when replacing the evolution operators. Use of pinned memory should help with this.
Input of necessary parameters from an XML file would allow the generation of arbitrary potentials, wavefunctions, etc, and allow a more robust and easier to use code-base.
Add a flag that can be used to set a dissipative term for the GPE.
This will remove unnecessary on-device memory transfers and host-kernel calls. Not sure of the expected performance increase, but it should be beneficial.
Lots of old and unnecessary source files, functions and variables exist across the code. These should be removed for cleanliness.
The issue shows up with the move to std::vector for the vortex tracking routines. Any more than a single vortex causes the system to fail. @ # #
this fixes issues with memory, I promise.
The graph generation routine does not maintain the same UID order between simulations. Not a problem for initial selections and trajectories using python, but will be a problem if performing analysis on graphs expecting initial order.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
๐ Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. ๐๐๐
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google โค๏ธ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.