Luce's Megakernal boosts GPU inference speed by 1.8x with lower power consumption
New kernel design eliminates CPU dispatches, rivaling Apple Silicon efficiency on NVIDIA GPUs.
Deep Dive
A Reddit user claims they found a megakernel released alongside DFlash and PFlash, reportedly delivering 1.8x faster performance and better power efficiency on NVIDIA GPUs—comparable to Apple Silicon—by avoiding CPU dispatches between layer boundaries, cutting about 100 kernel launches per token in CUDA. The user asks why nobody is talking about this and wonders if it's a game-changer.
Key Points
- Luce's Megakernal achieves 1.8x faster inference on NVIDIA GPUs by avoiding CPU dispatches between layer boundaries.
- Cuts kernel launches from ~100 per token in typical CUDA implementations to a single fused invocation.
- Power efficiency rivals Apple Silicon, making it highly attractive for multi-GPU setups and cost-sensitive deployments.
Why It Matters
Enables faster, cheaper, and more energy-efficient AI inference—critical for scaling large models on multi-GPU infrastructure.