sectorlisp
femtolisp
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sectorlisp | femtolisp | |
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25 | 10 | |
1,164 | 1,550 | |
- | - | |
4.3 | 0.0 | |
4 months ago | about 4 years ago | |
C | Scheme | |
ISC License | BSD 3-clause "New" or "Revised" License |
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sectorlisp
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are there any benchmarks on sector lisp
I'm assuming you are referring to https://github.com/jart/sectorlisp which I gather is an attempt to make a Lisp that fits in a disk boot sector?
- Sectorlisp
- Kilo Lisp: A Kilo Byte-Sized Lisp System
- For the LISP 1.5 mainframe fans here...
- Ask HN: Best book to learn C in 2022?
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Take More Screenshots
I think SIMD was a distraction to our conversation, most code doesn't use it and in the future the length agnostic, flexible vectors; https://github.com/WebAssembly/flexible-vectors/blob/master/... are a better solution. They are a lot like RVV; https://github.com/riscv/riscv-v-spec, research around vector processing is why RISC-V exists in the first place!
I was trying to find the smallest Rust Wasm interpreters I could find, I should have read the source first, I only really use wasmtime, but this one looks very interesting, zero deps, zero unsafe.
16.5kloc of Rust https://github.com/rhysd/wain
The most complete wasm env for small devices is wasm3
20kloc of C https://github.com/wasm3/wasm3
I get what you are saying as to be so small that there isn't a place of bugs to hide.
> “There are two ways of constructing a software design: One way is to make it so simple that there are obviously no deficiencies, and the other way is to make it so complicated that there are no obvious deficiencies. The first method is far more difficult.” CAR Hoare
Even a 100 line program can't be guaranteed to be free of bugs. These programs need embedded tests to ensure that the layer below them is functioning as intended. They cannot and should not run open loop. Speaking of 300+ reimplementations, I am sure that RISC-V has already exceeded that. The smallest readable implementation is like 200 lines of code; https://github.com/BrunoLevy/learn-fpga/blob/master/FemtoRV/...
I don't think Wasm suffers from the base extension issue you bring up. It will get larger, but 1.0 has the right algebraic properties to be useful forever. Wasm does require an environment, for archival purposes that environment should be written in Wasm, with api for instantiating more envs passed into the first env. There are two solutions to the Wasm generating and calling Wasm problem. First would be a trampoline, where one returns Wasm from the first Wasm program which is then re-instantiated by the outer env. The other would be to pass in the api to create new Wasm envs over existing memory buffers.
See, https://copy.sh/v86/
MS-DOS, NES or C64 are useful for archival purposes because they are dead, frozen in time along with a large corpus of software. But there is a ton of complexity in implementing those systems with enough fidelity to run software.
Lua, Typed Assembly; https://en.wikipedia.org/wiki/Typed_assembly_language and Sector Lisp; https://github.com/jart/sectorlisp seem to have the right minimalism and compactness for archival purposes. Maybe it is sectorlisp+rv32+wasm.
If there are directions you would like Wasm to go, I really recommend attending the Wasm CG meetings.
https://github.com/WebAssembly/meetings
When it comes to an archival system, I'd like it to be able to run anything from an era, not just specially crafted binaries. I think Wasm meets that goal.
https://gist.github.com/dabeaz/7d8838b54dba5006c58a40fc28da9...
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*Laughs in autocmd*
Based on this, the next thing you wrote, and your reference to running a minimal Gentoo: I think you might be a Scheme fan in the making. Scheme is the minimal Lisp. (Okay, that might be sectorlisp which fits in 512 bytes.) It’s hands down my favorite language. While it’s evolved on its own to be more of a superset of Scheme, Racket is my Scheme of choice.
- Bootstrapping Lisp in a Boot Sector
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That's pretty much it!
sectorlisp
femtolisp
- Petalisp: Elegant High Performance Computing
- fe: A tiny, embeddable language implemented in ANSI C
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From Common Lisp to Julia
> In short, Julia is very similar to Common Lisp, but brings a lot of extra niceties to the table
This probably because Jeff Bezanson, the creator of Julia, created a Lisp prior to Julia, which I think still exists inside Julia in some fashion
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Modern Python Performance Considerations
Well let's flip this around: do you think you could write a performant minimal Python in a weekend? Scheme is a very simple and elegant idea. Its power derives from the fact that smart people went to considerable pains to distill computation to limited set of things. "Complete" (i.e. rXrs) schemes build quite a lot of themselves... in scheme, from a pretty tiny core. I suspect Jeff Bezanson spent more than a weekend writing femtolisp, but that isn't really important. He's one guy who wrote a pretty darned performant lisp that does useful computation as a passion project. Check out his readme; it's fascinating: https://github.com/JeffBezanson/femtolisp
You simply can't say these things about Python (and I generally like Python!). It's truer for PyPy, but PyPy is pretty big and complex itself. Take a look at the source for the scheme or scheme-derived language of your choice sometime. I can't claim to be an expert in any of what's going on in there, but I think you'll be surprised how far down those parens go.
The claim I was responding to asserted that lisps and smalltalks can only be fast because of complex JIT compiling. That is trueish in practice for Smalltalk and certainly modern Javascript... but it simply isn't true for every lisp. Certainly JIT-ed lisps can be extremely fast, but it's not the only path to a performant lisp. In these benchmarks you'll see a diversity of approaches even among the top performers: https://ecraven.github.io/r7rs-benchmarks/
Given how many performant implementations of Scheme there are, I just don't think you can claim it's because of complex implementations by well-resourced groups. To me, I think the logical conclusion is that Scheme (and other lisps for the most part) are intrinsically pretty optimizable compared to Python. If we look at Common Lisp, there are also multiple performant implementations, some approximately competitive with Java which has had enormous resources poured into making it performant.
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CppCast: Julia
While it uses an Algol inspired syntax, it has the same approach to OOP programing as CLOS(Common Lisp Object System), with multi-methods and protocols, it has a quite powerfull macro system like Lisp, similar REPL experience, and underneath it is powerered by femtolisp.
- Julia and the Incarceration of Lisp
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What is the smallest x86 lisp?
For a real answer, other replies have already mentioned KiloLisp, but there's also femtolisp. Also, not exactly what you're asking for, but Maru is a very compact and elegant self-hosting lisp (compiles to x86).
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lisp but small and low level?Does it make sense?
Take a look at femtolisp It has some low level features and is quite small. There is also a maintenance fork at lambdaconservatory
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Lispsyntax.jl: A Clojure-like Lisp syntax for julia
A fun Julia easter egg I recently discovered.
Running 'julia --lisp' launches a femtolisp (https://github.com/JeffBezanson/femtolisp) interpreter.
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Wisp: A light Lisp written in C++
Reminds me of the femtolisp README :)
Almost everybody has their own lisp implementation. Some programmers' dogs and cats probably have their own lisp implementations as well. This is great, but too often I see people omit some of the obscure but critical features that make lisp uniquely wonderful. These include read macros like #. and backreferences, gensyms, and properly escaped symbol names. If you're going to waste everybody's time with yet another lisp, at least do it right damnit.
What are some alternatives?
sectorforth - sectorforth is a 16-bit x86 Forth that fits in a 512-byte boot sector.
small-lisp - A very small lisp interpreter, that I may one day get working on my 8-bit AVR microcontroller.
julia - The Julia Programming Language
Carp - A statically typed lisp, without a GC, for real-time applications.
mal - mal - Make a Lisp
Fennel - Lua Lisp Language
kernel-zig - :floppy_disk: hobby x86 kernel zig
awesome-lisp-companies - Awesome Lisp Companies
cling - The cling C++ interpreter
hissp - It's Python with a Lissp.