You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
***Notice: The toolkit is undergoing an internal testing and currently not publicly released. Who would like to use it in advance to release for non-profit use, please feel free contact me. The planned release time is 2025.06 - 2025.07 with high-freedom opensource license type, while the author still holds the right to change the release time.***
4
+
**Notice: The toolkit is undergoing an internal testing, and currently not publicly released. Who would like to use it in advance to release for non-profit use as early birds, please feel free contact me. The planned release time is 2025.06 - 2025.07 with high-freedom opensource license type, while the author still holds the right to change the release time. - Huanxia with Regards**
5
5
6
6
PyFTLE3D is a Python-based research toolkit for computing and visualizing
7
7
Lagrangian coherent structures (LCS) in three-dimensional fluid flows and other complex systems by computing Finite Time Lyapunov Exponent.
@@ -10,15 +10,12 @@ with multiple OOTB numerical methods, with various computation density, accuracy
10
10
with no need for researchers to have any programming knowledge.
11
11
Certainly, it is also suitable for those with programming experience who want to customize their analysis.
12
12
13
-
The computation is accelerated by CUDA, the NVidia treasure, achieving over 30x speedup compared to the CPU version.
13
+
The computation is accelerated by CUDA (Python Numba), the NVIDIA treasure, achieving over 30x speedup compared to the CPU version.
14
+
The author currently lacks the capability to develop with OpenCL, so for now only NVIDIA GPUs are supported for acceleration.
14
15
As most of computers have larger RAM than GPU memory, the toolkit also supports CPU mode for large datasets on CPU systems.
15
16
Although, the new features would firstly be added to the GPU version, and the CPU version would be updated with month-scale delay.
16
17
17
-
nekRS is a computational fluid dynamics code developed at :term:`ANL`, :term:`UIUC`, and :term:`PSU`.
18
-
nekRS aims to leverage the present trend in :term:`GPU`-based :term:`HPC` systems to perform
19
-
:term:`CFD` on :term:`GPU`-accelerated systems. By using the :term:`OCCA` library's unified
20
-
:term:`API`, nekRS can run on :term:`CPUs<CPU>` and on :term:`GPU`-accelerated :term:`CPUs<CPU>` that
21
-
support :term:`CUDA`, :term:`HIP`, or :term:`OpenCL`.
18
+
22
19
23
20
This guide is intended to help new users get started with using nekRS, as well as serve as a
24
21
reference for more advanced users. Because the :term:`Nek5000` code is somewhat of a predecessor to
0 commit comments