SOLID is an abbreviation for five of the most important software design principles:
– (S)ingle Responsibility Principle
– (O)pen-Closed Principle
– (L)iskov Substitution Principle
– (I)nterface Segregation Principle
– (D)ependency Inversion Principle For almost two decades, these principles have proven to be a valuable set of guidelines to cope with software dependencies. Although initially introduced as guidelines for object-oriented programming, they have become a universal set of guidelines that can be used equally well for procedural, functional or generic programming. In this talk I'll recap the SOLID principles and explain why they form such a valuable set of universal design guidelines. Also, I'll go into detail about several common misconceptions. PUBLICATION PERMISSIONS:
CppCon Organizer provided Coding Tech with the permission to republish CppCon tech talks. CREDITS:
CppCon YouTube channel: https://www.youtube.com/channel/UCMlGfpWw-RUdWX_JbLCukXg https://www.youtube.com/watch?v=RT-npV1JRKE

Python has come a long way since it was created in 1989. The talk will look into the current state, upcoming changes and explore possibilities for its future development, both at a language and application level. The talk looks at Python's development from a higher level point of view, using a more business oriented approach and analyzing the perspective from a corporate C-level user. PUBLICATION PERMISSIONS:
Original video was published with the Creative Commons Attribution license (reuse allowed). Link: https://www.youtube.com/watch?v=bLffgaVC1Os https://www.youtube.com/watch?v=UfMAiS6ndbs

High-performance computing is now dominated by general-purpose graphics processing unit (GPGPU) oriented computations. How can we leverage our knowledge of C++ to program the GPU? NVIDIA's answer to general-purpose computing on the GPU is CUDA. CUDA programs are essentially C++ programs, but have some differences. CUDA comes as a Toolkit SDK containing a number of libraries that exploit the resources of the GPU: fast Fourier transforms, machine learning training and inference, etc. Thrust is a C++ template library for CUDA. In this month's meeting, Richard Thomson will present a brief introduction to CUDA with the Thrust library to program the GPU. Programming the GPU with CUDA is a huge topic covered by lots of libraries, tutorials, videos, and so-on, so we will only be able to present an introduction to the topic. You are encouraged to explore more on your own! PUBLICATION PERMISSIONS:
Original video was published with the Creative Commons Attribution license (reuse allowed). Link: https://www.youtube.com/watch?v=tbb835UFRQ4 https://www.youtube.com/watch?v=iu1A0q6k3aw