This page may contain stale information. Last updated: 2026-06-12
Definition
GPU kernel optimization improves the efficiency of CUDA/GPU compute kernels to approach hardware speed-of-light limits. It is a core lever of AI infrastructure efficiency alongside better training algorithms and faster training loops.
Automated Research Application
recursive’s June 2026 system achieved mean SOL score 0.754 on sol-execbench (235 kernels), up from 0.699 — an 18% reduction in the gap to optimal performance (2026-06-11-recursive-automated-ai-research).
Techniques
Automated systems compound: inventing new optimizations, recasting known ideas under constraints, tuning implementation details, and composing improvements across modeling, optimization, and systems layers.