LAIKA: Machine Learning-Assisted In-Kernel APU Acceleration

The integration of machine learning (ML) into OS kernels is severely hampered by the high latency of offloading to discrete GPUs (dGPUs), where data transfers across the PCIe bus can consume over 93% of the total execution time. This paper argues that for many latency-sensitive kernel tasks, the solution is not a more powerful dGPU but a fundamental shift to an I/O-efficient architecture: the integrated GPU (iGPU) found in modern APUs.