This research demonstrates significant speedups for LLM inference on standard Intel CPUs by combining Matrix Extensions (AMX) with unstructured sparsity techniques.

• Accelerates token generation by up to 3.18x compared to dense computation
• Enables wider AI deployment without specialized hardware
• Achieves lower energy consumption than GPU-based alternatives
• Particularly effective during memory-bound decoding stages of inference

This engineering breakthrough matters because it democratizes access to AI by optimizing for hardware that's already widely available, reducing both cost and environmental impact.

SparAMX: Accelerating Compressed LLMs Token Generation on AMX-powered CPUs