Mojo beats Unsloth's CUDA NF4 dequantization — 1.84x speedup

AI Impact Summary

This guest post details a remarkable optimization of Unsloth's NF4 dequantization puzzle using Mojo, achieving speeds up to 1.84x faster than the state-of-the-art C++/CUDA implementation. The key breakthroughs involved packing 32-bit integers to reduce memory bandwidth constraints, utilizing occupancy tuning with 512-thread blocks, and leveraging the L4 GPU's larger cache to mitigate performance bottlenecks. This demonstrates Mojo's ability to deliver significant performance gains with minimal code changes, particularly for memory-bound workloads.