docs: Further tidy initial proposal idea

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Triex 2025-06-04 11:38:26 +10:00
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# DeepSeek V3 in Zig - Project Proposal
<div align="center"> <div align="center">
<img src="./dzv3-logo.svg" alt="DeepSeek V3 in Zig" width="100%" /> <img src="./dzv3-logo.svg" alt="DeepSeek V3 in Zig" width="100%" />
</div> </div>
@ -108,6 +106,26 @@ Current LLM inference is dominated by Python/PyTorch, which introduces:
**Web Scale**: Handle concurrent requests without blocking inference **Web Scale**: Handle concurrent requests without blocking inference
**Accuracy**: Match PyTorch numerical precision **Accuracy**: Match PyTorch numerical precision
## Platform-Specific Opportunities
### Apple Silicon (M-Series)
- **Metal Performance Shaders** integration for matrix operations
- **AMX instruction set** access for accelerated linear algebra
- **Unified memory architecture** exploitation for zero-copy transfers
- **Power efficiency tuning** across P and E cores
### x86_64 Architecture
- **AVX-512 vectorization** with masked operations
- **Cache-friendly memory layouts** for L1/L2/L3 optimization
- **NUMA-aware allocation** and thread assignment
- **Dynamic dispatch** based on runtime CPU feature detection
### NVIDIA GPUs
- **CUDA integration** via efficient FFI bindings
- **Tensor Core utilization** for mixed-precision operations
- **Custom kernels** for attention mechanisms
- **Memory pooling** for reduced allocation overhead
## Getting Started ## Getting Started
**Current Status**: This repository contains the original Python DeepSeek V3 implementation. The Zig implementation is proposed future work. **Current Status**: This repository contains the original Python DeepSeek V3 implementation. The Zig implementation is proposed future work.
@ -180,4 +198,5 @@ This is an ambitious project that would benefit from expertise in:
--- ---
**Status**: 🎯 Seeking feedback on initial idea **Status**: 🎯 Seeking feedback on initial idea
**Target**: Production-ready LLM inference in Zig **Target**: Production-ready LLM inference in Zig