done

README.md

@@ -1,23 +1,12 @@
 # ![SPHinXsys Logo](assets/logo.png) SPHinXsys
 
-**Notice on migration to heterogeneous computational platform** 
+**Notice on the transformation to heterogeneous computational platform**
 
-Now, SPHinXsys is ready for the migration from CPU parallelism to heterogeneous parallelism 
-by which the computing can be carried out on both CPU and GPU. 
-This will be done by using SYCL (implementation by Intel's DPC++),  
-a heterogeneous architectures in standard C++.
-However, during migration process, 
-we will kept the current code with minimum change so that 
-the library cam be still used as before.
-
-The basic framework has been achieved and 
-a test of 2D dambreak case has been added to the folder test/test_sycl.
-Due to the specially designed framework, 
-all the numerical method can be developed and tested in the environments 
-without GPU or even DPC++ installed.
-If these methods work, it will also work if the DPC++ and GPU are installed. 
+SPHinXsys is set to undergo a major transformation, moving from traditional CPU parallelism to a new era of heterogeneous parallelism, where compute-intensive tasks can harness the power of both CPUs and GPUs. This evolution will be driven by SYCL (via Intel's DPC++), enabling us to leverage heterogeneous architectures with standard C++. Importantly, this transformation will be achieved with minimal disruption to the existing codebase, ensuring seamless continuity for current users.
 
+The groundwork for this shift is already laid out. A 2D dambreak test case has been added to the test/test_sycl folder, showcasing the capabilities of our specially designed framework. What's unique about this framework is that it allows for the development and testing of numerical methods even in environments without GPUs or DPC++ installed. If these methods are crafted following our specified guidelines and prove functional, they will seamlessly operate in environments equipped with DPC++ and GPU support.
 
+By embracing this new paradigm, SPHinXsys is positioning itself at the forefront of multi-physics modeling, where performance meets versatility.
 
 **Project status**  
 [![License](https://img.shields.io/badge/License-Apache_2.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
@@ -73,31 +62,31 @@ The only difference is that SPHinXsys reads a predefined mesh, other than genera
 
 ## Target-driven optimization
 
-The unique target-driven optimization is able to achieve the optimization target and physical solution all-in-once, 
+The unique target-driven optimization is able to achieve the optimization target and physical solution all-in-once,
 which is able to accelerate optimization process greatly.
-The following gives an example of optimizing the conductivity distribution 
+The following gives an example of optimizing the conductivity distribution
 for a thermal domain problem targeting minimum average temperature.
 
 <a href="https://github.com/Xiangyu-Hu/SPHinXsys/blob/master/tests/optimization/test_2d_VP_heat_flux_optimization/VP_heat_flux_optimization.cpp">
 <img src="https://github.com/Xiangyu-Hu/SPHinXsys-public-files/blob/master/videos/optimization.gif" height="192px"></a>
 
 Note that the physical solution of the thermal domain (right) and the optimal distribution of conductivity (left)
-are obtained at the same time when optimization is finished. 
-Also note that the entire optimization process is very fast and 
+are obtained at the same time when optimization is finished.
+Also note that the entire optimization process is very fast and
 only several times slower than that for a single physical solution with given conductivity distribution.  
 
 ## Python interface
 
-While SPHinXsys is written in C++, it provides a python interface for users to write python scripts to control the simulation, 
+While SPHinXsys is written in C++, it provides a python interface for users to write python scripts to control the simulation,
 including carry out regression tests for continuous integration (CI) and other tasks.
 One example is given below for the dambreak case.
-Please check the source code of 
-[2D Dambreak case with python interface](https://github.com/Xiangyu-Hu/SPHinXsys/tree/master/tests/2d_examples/test_2d_dambreak_python) 
+Please check the source code of
+[2D Dambreak case with python interface](https://github.com/Xiangyu-Hu/SPHinXsys/tree/master/tests/2d_examples/test_2d_dambreak_python)
 for the usage.
 
 ## Heterogenous computing
 
-Recently, we have a preview release for the heterogeneous computing version of SPHinXsys. 
+Recently, we have a preview release for the heterogeneous computing version of SPHinXsys.
 By using SYCL, a royalty-free open standard developed by the Khronos Group that allows developers
 to program heterogeneous architectures in standard C++, SPHinXsys is able to utilize the power of GPU.
 Please check the [Preview Release](https://github.com/Xiangyu-Hu/SPHinXsys/releases/tag/v1.0-beta.08-sycl)
@@ -126,10 +115,10 @@ For a Docker image, check <https://hub.docker.com/r/toshev/sphinxsys>.
 
 ## Interaction with SPHinXsys and the team
 
-Thank you for using and supporting our open-source project! 
+Thank you for using and supporting our open-source project!
 We value each feedback.
 
-#### For SPHinXsys users:
+#### For SPHinXsys users
 
 Your input is crucial to us. We encourage you to report any issues you encounter with the library, including:
 
@@ -140,7 +129,7 @@ Your input is crucial to us. We encourage you to report any issues you encounter
 
 We particularly appreciate feedback stemming from practical simulations or projects, as these insights are essential for improving SPHinXsys.
 
-#### For SPHinXsys developers:
+#### For SPHinXsys developers
 
 If you don't have a GitHub account yet, please register for one. Fork the SPHinXsys repository to add new features or improve existing ones. Once your changes are ready, commit them and initiate a pull request to have your contributions merged into the main repository.