nickmqb
[1] https://store.digilentinc.com/pmod-vga-video-graphics-array/
[1] https://www.raphnet-tech.com/products/gc_controller_connecto...
In terms of hardware, I'm using an iCEBreaker dev board [1] which has worked really well (A nice bonus is that the board has a 16MB flash chip, which can be used for storage -- this is what the Minecraft clone uses to load the map and textures from on startup).
On the software side, I'm using the open source yosys/nextpnr/icestorm toolchain which is a lot faster than the vendor supplied tools. I mostly figured things out by just trying stuff, so a high iteration speed definitely helped here!
While it would have been easier to use a larger/faster FPGA, part of the fun of such a low level project is to work within harsh constraints and see what can be done regardless :).
I just looked up the MiSTer board [1]. They are using a DE10-Nano FPGA [2], which is a lot more powerful than the iCE40 UP5K [3] that I'm using (for comparison, the DE10-Nano has 110,000 lookup elements, whereas the iCE40 UP5K just has 5,280, so ~20x difference!). So porting should be pretty easy. It also opens up opportunities to increase the resolution, frame rate and render distance.
[1] https://github.com/MiSTer-devel/Main_MiSTer/wiki [2] https://www.digikey.com/en/product-highlight/t/terasic-tech/... [3] https://www.latticesemi.com/en/Products/FPGAandCPLD/iCE40Ult...
The FPS (30Hz) is rock steady though! One of my pet peeves when doing DirectX/OpenGL development is that it's really hard to completely avoid frame drops, e.g. if the OS decides to schedule some other thread, or because the GPU driver decided to do something else than render your app. With hardware development, you can side step all of those problems. As a result, the Minecraft clone is guaranteed to not drop frames :).
Input happens via a N64 controller! Those are actually fairly easy to work with at a low level.
The code is not public, though I'm considering open sourcing the project when it's done. Moreover, there's a lot of additional details that I could potentially go into, so I'm considering also writing a few blogs posts with more info if people are interested!
While it is true that strong typing is a requirement for the best performance (and this remains so), the productivity benefits of strong typing have been known for a long time.
I mean, just look at languages like C# and Java. These are well established, extremely popular languages, used mostly in business software. A domain where performance is rarely critical. Yet, these languages are very popular. Not in the least because they make it easier for programmers to understand and work with other people's code, and because they provide good tooling, both of which are hugely valuable in a business/enterprise context. Strong typing plays a major role in enabling these features.
Even when C# was still a brand new language, roughly 20 years ago, Visual Studio already provided features like "go to definition", "find references" and autocomplete out of the box. These were a major reason for people to adopt the language.
It's no surprise that people like Anders Hejlsberg, who created C#, later went on to create TypeScript. They already understood the productivity advantages of strong typing and wanted to bring those to the web.
How do things change if we were to use a list instead? What becomes easier/harder?
Layout calculations might become slightly more expensive, though it seems that that may be acceptable since most time is spent rendering; and perhaps there are other ways to accelerate these calculations if needed.
The fact that most UIs are happy to provide a single linear tab order (and not something more involved that allows users to navigate the tree structure) makes me think that there might be something there.
Show HN: Wyre, a hardware definition language that compiles to Verilog
This paper, like some others that I've seen, treats parsing as an academic/algorithmic topic. Given some token stream we'd like to minimize some error criteria. However, these papers ignore the fact that people don't write token streams: they write code that is formatted using whitespace. I don't know any programmer that writes their source code on a single line. On the contrary, pretty much every programmer formats their source code to some reasonable (if not complete) degree. In other words: parsing error recovery is not primarly an algorithmic problem: it's a usability problem.
Newlines and indentation are a source of extra information that we can use to infer what the programmer meant. Why throw all that away during tokenization? That's crazy! We can totally use it for error recovery/error message generation.
I decided to play around with this idea in the design my programming language Muon [1]. The language uses redundant significant whitespace for parser error recovery. This simple approach by itself has turned out to work surprisingly well! In my admittedly biased opinion, it frequently surpasses the error recovery quality in mature compilers such as the C# compiler, which has had tons of effort poured into error recovery.
Of course, a purely whitespace based recovery scheme is not perfect: there are rough edges, like having to deal with tabs vs spaces, and recovering inside a line is not usually possible. But the fact that such a simple approach has led to good results makes me think this would be a great area for future research, that can perhaps combine the best of both worlds here.
Lattice (the FPGA's manufacturer) seems open-minded regarding such efforts: https://twitter.com/latticesemi/status/1269115302140231682
This has some implications. For example, I can imagine someone editing a text block and inadvertently using a different indentation type (tabs/spaces) from the other existing lines, which would then change their program in a non-obvious way. I'm myself an author of a programming language with a non-standard approach to whitespace (called Muon), so this is a topic I've thought about quite a bit. Interesting that the Java team considers this an acceptable tradeoff. I'm looking forward to seeing how this plays out in practice as a data point.
One cool aspect of all of these new programming languages entering the arena is that most of them only have a minimal (or no) runtime. That should make it much easier to interoperate between all of these languages, something which has traditionally been difficult with most programming languages.
Disclosure: I'm the author of Muon [1], a low-level language that embodies similar design principles.
- Increased language complexity. Initialization of (arrays of) structs with non-null pointer members is more complicated because there is no straightforward "default" value that can be used.
- Performance tradeoffs. Initialization of arrays and other containers is more costly for non-null pointers (or structs containing them) because we cannot simply zero out a block of memory.
- In memory unsafe languages it is possible for a non-null pointer to become null if its memory is overwritten (e.g. in custom allocator scenarios (also mentioned by the author of the article), interop scenarios, etc.). The type system now makes a false guarantee, and it becomes possible for a "non-null" pointer to trigger a null pointer crash. (It's worth mentioning that enums generally have a similar problem).
- I'd like do a more rigorous evaluation on this, but my gut feeling is that most null pointer bugs that I've encountered usually happen in situations where the pointer would have to be declared as nullable anyway, because I'm using null to represent a possible state.