File size: 3,247 Bytes
9b67774 d9a3fdb |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 |
# π Advice on Rust, Go, Zig for HPC in AI Pipelines
## π My Coding World
- π 1 **Focus**: Writing fast AI code for AI spaces.
- π» 2 **Fav Languages**: Python, HTML5, JS β picky for AI UI/UX vibes.
- β‘ 3 **Daily Grind**: Building models, designing pipelines, 3000 lines/day since AI pair programming (2020).
- π οΈ 4 **Workflow**: 1500-line spaces, 200-300 versioned `app.py`, `requirements.txt`, and redocker boots.
- π₯οΈ 5 **Fav IDEs**:
- π 1. **HuggingFace**: Instant setup, 3 secs to spin up a Space! π
- π 2. **VSCode**: 5 mins for folder, interpreter, `launch.json`. βοΈ
## β±οΈ Why I Love My Setup
- π 1 **New Project**:
- β‘ 1. HF: 3 secs to pick a Python lib or container.
- π οΈ 2. VSCode: 5 mins to configure from scratch.
- π 2 **Quick Python App** (`app.py`, `requirements.txt`):
- β³ 1. HF: <2 mins, auto-rebuilds on commit.
- π§ 2. VSCode: ~2 mins, but manual rebuilds.
- π 3 **Learn Fast**: Simple patterns, no complexity overload.
- π§ͺ 1. E.g., `git clone https://github.com/AaronCWacker/SFT` β instant ML pipeline, test-ready!
- π 4 **Test & Enjoy**: Pure pleasure running my own app.
## π§ͺ Experimenting with HPC: How Low Can We Go?
## π‘ Why Try Rust, Go, Zig for AI?
- π Hereβs why these languages fit your 3000-line/day AI pipeline life:
- π¦ 1 **Rust: Memory-Safe Speed Demon**
- π§Ή 1. **Why**: Stack cleanup = no leaks, no GC lag for big models.
- βοΈ 2. **Perk**: Mutable vars explicit β readable pipelines at 2 AM.
- β‘ 3. **Fit**: Fast, safe, concurrent β crushes big data tasks.
- πΉ 2 **Go: Reliable Workhorse**
- π 1. **Why**: Simple, fast binaries, goroutines for concurrency.
- π 2. **Perk**: Perfect for real-time services (e.g., ChatGPT, ElevenLabs).
- β© 3. **Fit**: Churns out server-side code to match your grind.
- β‘ 3 **Zig: Wild Card Optimizer**
- β²οΈ 1. **Why**: "Comptime" metaprogramming β pre-compute tables/configs.
- π© 2. **Perk**: Raw, C-like control, no fluff, blazing fast.
- π¨ 3. **Fit**: Playground for performance tweaks in AI spaces.
## π― Takeaways
- π‘οΈ 1 **Rust**: Safe, concurrent model code.
- π 2 **Go**: Quick, scalable services.
- π 3 **Zig**: Lean, custom optimizations.
- πͺ 4 **Promise**: Theyβll keep up with your pace and push pipelines harder.
## π₯ Call to Action
- π 1 Give βem a shot β your AI code deserves it!
-
1. π **Rust frees memory with stack cleanup** - No manual freeing, tied to scope.
2. π‘οΈ **Rust avoids garbage collector** - Compile-time cleanup, not runtime.
3. βοΈ **Rust requires mutable variables explicitly** - Improves code readability, safety.
4. β‘ **Rust emphasizes performance, safety** - Borrow checker prevents errors.
5. π§© **Zig metaprogramming is simple** - Same syntax, just add "comptime."
6. β±οΈ **Zig runs code at compile time** - E.g., generate prime numbers early.
7. π **Go as a mainstay** - Reliable for services, web sockets.
8. π οΈ **Jai and Zig for exploration** - Testing performance in custom services.
9. π **Jai uses raw sockets** - Manual TCP connections, like C.
10. π **C++ metaprogramming is messy** - Powerful but hard to debug. |