DAF

DAF is a memory-efficient DNN training runtime that dynamically adjusts activation precision according to runtime importance. Kernel fusion reduces quantization and memory-movement overhead, while a page-based memory manager supports variable-sized quantized activations and reduces training memory usage by up to 22.9×.