A layer‐wise frequency scaling for a neural processing unit

Dynamic voltage frequency scaling (DVFS) has been widely adopted for run-time power management of various processing units. In the case neural units (NPUs), network applications is required to adjust and every layer consider behavior performance each layer. Unfortunately, DVFS inappropriate layer-wise NPUs due long latency compared with execution time. Because fast enough keep up layer, we propose a dynamic (DFS) technique an NPU. Our proposed DFS exploits highest under limit NPU To determine allowable frequency, build model predict consumption based on real measurement fabricated evaluation results show that our improves frame per second (FPS) by 33% saves energy 14% average, DVFS.