Final Presentation
Final Presentation
YEAH!!! Today is the last day of class, and we have our Final Group Presentation.
Not only our group, ALL groups did great jobs in this presentation.
Group CATS
We chose the topic of Monte Carlo Simulation of a Lennard Jones Fluid.
I, Chongye, talked about the programming languages we learned and used in the two-week Bootcamp, Python, and C++. As an interpreted language, Python can run without a compiler. Python is good for prototyping and note-taking because it is easy to write and has the tools like Jupyter-Notebook. On the other hand, C++ is faster since it is pre-compiled by the compiler. C++ has pointers and the Dynamic Memory Allocation so it is good at memory management. And we got great instruction and explanations of each problem we have in C++ from professors. So, it is not that painful when switching to C++ from Python. One thing to mention is that we got the C++ code compiled and run for the very first time, which is lucky. So in between the two powerful programming languages, we chose C++.
Trevor talked about the performance of the code and the version with Git. We noticed that the Numpy version of the Python code has a shorter time in the Monte Carlo iteration for-loop, where Numpy Arrays can do mathematic calculations directly and avoid the nested for-loop. But the importing time of Numpy in the system causes it to have a longer total time than the Python Standard Library version when the number of iterations is low (smaller than 10,000, in our programs). We found that the time it takes before hitting the iteration for-loop is 2.2 seconds for the PSL version, compared with 7.2 seconds for the Numpy version. The pre-compiled C++ version is the fastest of all time.
Joshua talked about how and why Monte Carlo Simulation can do a good job in finding the equilibrium condition of the Lennard Jones Fluid. From the fundamental knowledge of Molecular systems to the recent-learned Monte Carlo Simulation, we used the knowledge to write, test, and present our code in the last two weeks. Monte Carlo Simulation shows us how the computer can solve complex problems in its way, and how we can use the super-power of the computer.