THE VIDEO SHELF · modern c++ on embedded hardware
CppCon 2016: Jason Turner “Rich Code for Tiny Computers: A Simple Commodore 64 Game in C++17”
Jason Turner's CppCon 2016 talk builds a simple Commodore 64 game using C++17, showing how constexpr and const let a modern compiler produce tight 6502 code. He walks through assembly output to show abstractions being optimized away.
Why HN readers recommended it
A perennial favorite, recommended as proof that expressive modern C++ can compile to efficient code even on tiny retro hardware.
This is a summary from the source dataset, not an endorsement by Hacker News or the video creator.
Video & recommendation details
- Creator / channel
- CppCon
- Topic
- modern c++ on embedded hardware
- Format
- talk
- Level
- intermediate
- HN recommenders in dataset
- 13
- HN mentions in dataset
- 20
- Recommendation years in dataset
- 2016–2024
These counts and years describe the included Hacker News records; they are not YouTube views or the video’s publication date.
From the original HN conversations
Excerpts from the recorded comments. Follow each source for the full comment and surrounding discussion.
For those who haven't seen it, there is a wonderful talk by Jason Turner about writing a simple Pong clone for the Commodore 64 in modern C++: [VIDEO]
dmit on Hacker News · 2016-10
In Twenty years later I wrote a Tetris againAbsolutely. There was a fantastic talk at CppCon last year, using C++17 to program a game for the Commodore 64. Using standard C++ idioms, the optimizer was easily able to make it compile down to efficient machine code. [1] [VIDEO]
MereInterest on Hacker News · 2017-02
In C++ on Embedded SystemsYour second link reminded me of [LINK] (which definitely builds on some of Matt's work). [VIDEO] - C++17 for the Commodore 64. Probable language warnings for my other suggestions: * Rescuing Prince of Persia from the Sands of Time [LINK] (was this talk ever given …
voltagex_ on Hacker News · 2016-10
In Ask HN: What's your favorite tech talk?
Summaries, classifications and recommendation records are from the HackerTube source dataset. Read about this library and its limitations.