Breaking the GPU Bubble

During AI model inference, a phenomenon called the GPU bubble occurs, where the GPU sits idle doing nothing while the CPU prepares the next task. This becomes a major bottleneck especially in autoregressive decoding loops that generate tokens one at a time.

Moondream's inference engine, Photon, uses pipelined decoding technology to address this. This approach overlaps work so that while the CPU processes the results of the previous token and plans the next step, the GPU has already begun computation for the next token.

The core mechanisms are as follows:

• Ping-pong slots: Fixed-address buffers are used alternately to prevent buffer conflicts, eliminating GPU memory allocation overhead.
• CUDA Graph utilization: Decoding steps are captured and reused to reduce kernel launch overhead.
• Asynchronous data transfer: Pinned buffers and DMA (Direct Memory Access) are used so that data movement between CPU and GPU doesn't interfere with computation.

Through these optimizations, Photon achieves near-real-time VLM inference speed of about 33ms on an NVIDIA B200, delivering up to 35% higher decoding throughput compared to existing approaches.