ToyBrick RK3399Pro Board Shown to Outperform Jetson Nano SBC
NVIDIA created a lot of buzz when they released $99 Jetson Nano SBC featuring a 128-core Maxwell GPU, and said to deliver 472 GFLOPS of compute performance for running modern AI workloads with a power consumption of around 5 watts. But Jetson Nano is not the only low cost platform to deliver high performance at low power for AI workloads, as for example Rockchip RK3399Pro (RK1808 NPU) found in boards such as Toybrick RK3399Pro is said to deliver 3 TOPS for INT8, 300 GOPS for INT16, and 100 GOPS for FP16 inferences. Those operations per second numbers can be confusing and misleading, so it’s important to check out the performance of actual neural network models, and Rockchip did provide some RK3399Pro benchmarks last year for Inception V3, ResNet34 and VGG16 models comparing the results to Apple A11, Huawei Kirin 970, and NVIDIA Jetson TX2. However, ideally you’d want result from […]