deploy: 8c728cc

Author: hweifluids

.doctrees/environment.pickle

@@ -1,24 +1,21 @@
 PyFTLE3D: Research Toolkit for 3D Lagrangian coherent structures with GUI
 ===================================================
 
-***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.***
+**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**
 
 PyFTLE3D is a Python-based research toolkit for computing and visualizing
 Lagrangian coherent structures (LCS) in three-dimensional fluid flows and other complex systems by computing Finite Time Lyapunov Exponent.
-Coming with GUI and integrated environment, it is designed to be user-friendly and accessible, allowing peers to easily analyze and visualize LCS in their data
+Coming with GUI and integrated runtime, it is designed to be user-friendly and accessible, allowing peers to easily analyze and visualize LCS in their data
 with multiple OOTB numerical methods, with various computation density, accuracy, and focus preferences,
 with no need for researchers to have any programming knowledge.
 Certainly, it is also suitable for those with programming experience who want to customize their analysis.
 
-The computation is accelerated by CUDA, the NVidia treasure, achieving over 30x speedup compared to the CPU version.
+The computation is accelerated by CUDA (Python Numba implement), achieving over 30x speedup compared to the CPU version.
+The author currently lacks the capability to develop with OpenCL, so for now only NVIDIA GPUs are supported for acceleration.
 As most of computers have larger RAM than GPU memory, the toolkit also supports CPU mode for large datasets on CPU systems.
 Although, the new features would firstly be added to the GPU version, and the CPU version would be updated with month-scale delay.
 
-nekRS is a computational fluid dynamics code developed at :term:`ANL`, :term:`UIUC`, and :term:`PSU`.
-nekRS aims to leverage the present trend in :term:`GPU`-based :term:`HPC` systems to perform
-:term:`CFD` on :term:`GPU`-accelerated systems. By using the :term:`OCCA` library's unified
-:term:`API`, nekRS can run on :term:`CPUs<CPU>` and on :term:`GPU`-accelerated :term:`CPUs<CPU>` that
-support :term:`CUDA`, :term:`HIP`, or :term:`OpenCL`.
+
 
 This guide is intended to help new users get started with using nekRS, as well as serve as a
 reference for more advanced users. Because the :term:`Nek5000` code is somewhat of a predecessor to

.doctrees/index.doctree

@@ -83,21 +83,17 @@
 
   <section id="pyftle3d-research-toolkit-for-3d-lagrangian-coherent-structures-with-gui">
 <h1>PyFTLE3D: Research Toolkit for 3D Lagrangian coherent structures with GUI<a class="headerlink" href="#pyftle3d-research-toolkit-for-3d-lagrangian-coherent-structures-with-gui" title="Link to this heading"></a></h1>
-<p><strong>*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.*</strong></p>
+<p><strong>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</strong></p>
 <p>PyFTLE3D is a Python-based research toolkit for computing and visualizing
 Lagrangian coherent structures (LCS) in three-dimensional fluid flows and other complex systems by computing Finite Time Lyapunov Exponent.
-Coming with GUI and integrated environment, it is designed to be user-friendly and accessible, allowing peers to easily analyze and visualize LCS in their data
+Coming with GUI and integrated runtime, it is designed to be user-friendly and accessible, allowing peers to easily analyze and visualize LCS in their data
 with multiple OOTB numerical methods, with various computation density, accuracy, and focus preferences,
 with no need for researchers to have any programming knowledge.
 Certainly, it is also suitable for those with programming experience who want to customize their analysis.</p>
-<p>The computation is accelerated by CUDA, the NVidia treasure, achieving over 30x speedup compared to the CPU version.
+<p>The computation is accelerated by CUDA (Python Numba implement), achieving over 30x speedup compared to the CPU version.
+The author currently lacks the capability to develop with OpenCL, so for now only NVIDIA GPUs are supported for acceleration.
 As most of computers have larger RAM than GPU memory, the toolkit also supports CPU mode for large datasets on CPU systems.
 Although, the new features would firstly be added to the GPU version, and the CPU version would be updated with month-scale delay.</p>
-<p>nekRS is a computational fluid dynamics code developed at <a class="reference internal" href="glossary.html#term-ANL"><span class="xref std std-term">ANL</span></a>, <a class="reference internal" href="glossary.html#term-UIUC"><span class="xref std std-term">UIUC</span></a>, and <a class="reference internal" href="glossary.html#term-PSU"><span class="xref std std-term">PSU</span></a>.
-nekRS aims to leverage the present trend in <a class="reference internal" href="glossary.html#term-GPU"><span class="xref std std-term">GPU</span></a>-based <a class="reference internal" href="glossary.html#term-HPC"><span class="xref std std-term">HPC</span></a> systems to perform
-<a class="reference internal" href="glossary.html#term-CFD"><span class="xref std std-term">CFD</span></a> on <a class="reference internal" href="glossary.html#term-GPU"><span class="xref std std-term">GPU</span></a>-accelerated systems. By using the <a class="reference internal" href="glossary.html#term-OCCA"><span class="xref std std-term">OCCA</span></a> library’s unified
-<a class="reference internal" href="glossary.html#term-API"><span class="xref std std-term">API</span></a>, nekRS can run on <a class="reference internal" href="glossary.html#term-CPU"><span class="xref std std-term">CPUs</span></a> and on <a class="reference internal" href="glossary.html#term-GPU"><span class="xref std std-term">GPU</span></a>-accelerated <a class="reference internal" href="glossary.html#term-CPU"><span class="xref std std-term">CPUs</span></a> that
-support <a class="reference internal" href="glossary.html#term-CUDA"><span class="xref std std-term">CUDA</span></a>, <a class="reference internal" href="glossary.html#term-HIP"><span class="xref std std-term">HIP</span></a>, or <a class="reference internal" href="glossary.html#term-OpenCL"><span class="xref std std-term">OpenCL</span></a>.</p>
 <p>This guide is intended to help new users get started with using nekRS, as well as serve as a
 reference for more advanced users. Because the <a class="reference internal" href="glossary.html#term-Nek5000"><span class="xref std std-term">Nek5000</span></a> code is somewhat of a predecessor to
 nekRS, some aspects of the current nekRS design are selected to enable faster translation of