GPU Performance Tuning: Hitting the Roofline Limits
2025-06-24
This article delves into the performance bottlenecks of GPU architectures, focusing on how memory bandwidth and compute throughput limit application speed. Using the Roofline model, it analyzes memory-bound and compute-bound regimes, detailing strategies to increase arithmetic intensity (AI): operator fusion and tiling. Fusion reduces intermediate memory traffic, while tiling maximizes data reuse through shared memory. The article also covers nuanced topics like shared memory bank conflicts, thread divergence, and quantization for performance gains. The ultimate goal is to push kernel operation points towards the compute throughput ceiling in the Roofline model.