Blogs

Why study Modelica I have seen a book “Model Thinking” before, and this time it happens to be in the CoVid-2019 disease ravaging the world, by chance I saw the prediction model SEIR about epidemiology, I took this opportunity to start studying mathematical models, and decided to pick up the mathematical analysis, ordinary differential equations, partial differential equations, differential geometry and other courses I studied in college. I came across the language Modelica, and since I had been studying Wolfram Mathematica, I was quite fond of SystemModeler of the Wolfram product line, so I started to buy the home edition of SystemModeler and purchased a book “Introduction and Improvement of Modelica Multi-Domain Physical System Modeling”. I began my exploration of Modelica with the expectation of gaining a deeper understanding of mathematical model building, using mathematical models to predict the future development pattern of an event and gaining more hidden information in quantitative data analysis. ...

About the blog Content description About this site is mainly used for documenting current studies and research records, including Neural Networks, Deep Learning, Application Areas of Artificial Intelligence, Quantitative Trading, Multi-Domain Modelica Mathematical Modeling, Mathematica. Origin of the domain name The name of the domain name requires mentioning the great director Tarkovsky, whose book “Carving Time” describes making a movie as a craftsman carving time with his own tools. At some point it occurred to me that I could use machine learning to assist in filmmaking, such as storyboarding, VFX compositing and keying, 3D set design. Then I slowly began to approach the field of artificial intelligence, in the beginning of the learning stage to build this website to record the learning process, to build a systematic knowledge of the document. ...

Pixar’s Core Rendering Technology

#历史 Vitess was created in 2010 to solve the MySQL scalability challenges that the team at YouTube faced. This section briefly summarizes the sequence of events that led to Vitess’ creation: YouTube’s MySQL database reached a point when peak traffic would soon exceed the database’s serving capacity. To temporarily alleviate the problem, YouTube created a master database for write traffic and a replica database for read traffic. With demand for cat videos at an all-time high, read-only traffic was still high enough to overload the replica database. So YouTube added more replicas, again providing a temporary solution. ...