RocketLogger

Tiny-PULP-Dronets: Squeezing Neural Networks for Faster and Lighter Inference on Multi-Tasking Autonomous Nano-Drones

“…We evaluate GAP8's execution time and energy consumption when running a single-frame inference with the smallest Tiny-PULP-Dronet model (γ = 0.125). We use the RocketLogger data logger [13] (64 ksps) to separately plot the power waveforms of the GAP8's main core, the Fabric Controller (FC), and its 8-core parallel cluster (CL). We test two SoC configurations: the so called energy-efficient configuration [10], whose operating point is FC@50 MHz, CL@100 MHz, and VDD@1 V, and the maximum performance settings according to the GAP8's datasheet, which is FC@250 MHz, CL@175 MHz, VDD@1.2 V.…”