As far as space is concerned, the matrix won't necessarily take up more than the list if you flatten each row into a bitset. And using the cyclic property of an index based bitset you can build a neighbor list much faster. Even just an 8-bit table would speed things up considerably, but the less sparse a list becomes the more space you'd save with a matrix implemented this way and you could use the savings to speed it up more by using a 16-bit table instead.
Please keep it up! Your content is top notch! Thank you! You relit my burned out heart for programming, even though Im a computer science student lol, my uni has a lot of physics which I don’t t really have a passion for. Viele danke again :)
This is really useful, and just what I was looking for. Thank you.
Great video! Complex topic explained simply and clearly. Cheers 🍻
As far as space is concerned, the matrix won't necessarily take up more than the list if you flatten each row into a bitset. And using the cyclic property of an index based bitset you can build a neighbor list much faster. Even just an 8-bit table would speed things up considerably, but the less sparse a list becomes the more space you'd save with a matrix implemented this way and you could use the savings to speed it up more by using a 16-bit table instead.
Please keep it up! Your content is top notch! Thank you! You relit my burned out heart for programming, even though Im a computer science student lol, my uni has a lot of physics which I don’t t really have a passion for. Viele danke again :)
Great to hear! Keep it up 💪
Concise explanation 🤫
Great work 😅