argo-navis VS vast

argonavis.io | Lead Software Engineer | NYC | Full-time or Part-time

Do you like space exploration, modular SSTO spaceplanes and player-driven economies?

Argo Navis is an early stage, deep tech game project based in NYC.

We're looking for a part-time to full-time lead software engineer that can potentially continue as co-founder. Compensation is heavy on equity but we have funding for market rate cash pay. The role can be partially remote.

We're working on a new multiplayer space-based sandbox game. Our current focus is physics simulation, procedural generation and resource-based economics. Two major influences are Kerbal Space Program and Eve Online.

The game engine, server and client code are all in an embarrassingly early stage. The plan is to flesh these out with prototype implementations of spatial reference frames, Orbital / Newtonian mechanics and collision detection / resolution. All game states and state transitions will be wrapped in a cryptographic layer to support verification of the current game world, its history and replays of partial world states. Deterministic randomness (not a contradiction; see BLS crypto) will drive the procedural world generation. Players interact with the server exclusively through secure cryptographic signatures - enabling the game and all its interaction to form a secure protocol. But don't worry, we're not building a blockchain nor shilling any tokens :)

The project is radically open: all server and client code is open source and all digital / sound assets are open and free to use. Drafts of first principles, source code:

https://github.com/star-formation/argo-navis/blob/master/doc...

Most languages target C or LLVM, and C and LLVM have a fundamentally lossy compilation processes.

To get around this, you'd need a hodge podge of pre compiler directives, or take a completely different approach.

I found a cool project that uses a "Tower of IRs" that can restablish source to binary provenance, which, seems to me, to be on the right track:

https://github.com/trailofbits/vast

I'd definitely like to see the compilation processes be more transparent and easy to work with.

At Trail of Bits, we are creating a new compiler front/middle end for Clang called VAST [1]. It consumes Clang ASTs and creates a high-level, information-rich MLIR dialect. Then, we progressively lower it through various other dialects, eventually down to the LLVM dialect in MLIR, which can be translated directly to MLIR.

Our goals with this pipeline are to enable static analyses that can choose the right abstraction level(s) for their goals, and using provenance, cross abstraction levels to relate results back to source code.

Neither Clang ASTs nor LLVM IR alone meet our needs for static analysis. Clang ASTs are too verbose and lack explicit representations for implicit behaviours in C++. LLVM IR isn't really "one IR," it's a two IRs (LLVM proper, and metadata), where LLVM proper is an unspecified family of dialects (-O0, -O1, -O2, -O3, then all the arch-specific stuff). LLVM IR also isn't easy to relate to source, even in the presence of maximal debug information. The Clang codegen process does ABI-specific lowering takes high-level types/values and transforms them to be more amenable to storing in target-cpu locations (e.g. registers). This actively works against relating information across levels; something that we want to solve with intermediate MLIR dialects.

Beyond our static analysis goals, I think an MLIR-based setup will be a key enabler of library-aware compiler optimizations. Right now, library-aware optimizations are challenging because Clang ASTs are hard to mutate, and by the time things are in LLVM IR, the abstraction boundaries provided by libraries are broken down by optimizations (e.g. inlining, specialization, folding), forcing optimization passes to reckon with the mechanics of how libraries are implemented.

We're very excited about MLIR, and we're pushing full steam ahead with VAST. MLIR is a technology that we can use to fix a lot of issues in Clang/LLVM that hinder really good static analysis.

[1] https://github.com/trailofbits/vast