EGGROLL in C

A minimalist, dependency-free implementation of the EGGROLL (Evolution Guided General Optimization via Low-rank Learning) algorithm in pure C.

This project demonstrates integer-only training of a language model directly on the CPU (optimized for Apple Silicon/M-series chips), completely bypassing the need for GPUs, floating-point arithmetic, or heavy ML frameworks like PyTorch or JAX.

Key Features

• Pure C: Zero external dependencies (uses standard libraries + dispatch for threading).
• Apple Silicon Optimized: Vectorized operations using ARM NEON intrinsics and parallelized via Grand Central Dispatch (GCD).
• Integer Only: Operates entirely on int8 weights/activations with int32 accumulation. No float math in the training loop.
• Gradient Free: Uses Evolution Strategies (ES) with low-rank perturbations instead of backpropagation.

Quick Start

1. Prepare Data

Ensure you have a text dataset named input.txt in the current directory.

2. Compile

clang -O3 full_trained_egg.c -o egg

3. Run

./egg

Configuration

References

• Original JAX Implementation: ESHyperscale/nano-egg
• Original Paper & Project: EGGROLL Website