0571124 20240402213822.420230424235959.9 2023 artificial intelligence object detection embedded systems edge computing Vitis AI 2.0 AMD-Xilinx Zynq UltraScale+ cav_un_auth*0225749 Kohout Lukáš UTIA-B Zpracování signálů Department of Signal Processing ZS ZS Department of Signal Processing Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0101179 Pohl Zdeněk UTIA-B Zpracování signálů Department of Signal Processing ZS ZS Department of Signal Processing Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0101120 Kadlec Jiří UTIA-B Zpracování signálů Department of Signal Processing ZS ZS Department of Signal Processing Ústav teorie informace a automatizace AV ČR, v. v. i. https://zs.utia.cas.cz/index.php?ids=results&id=te0802_2cg_vitis_ai_resnet50 8A21009 GA MŠk cav_un_auth*0432581 A tutorial describing setup and run Vitis AI 2.0 facedetect and resnet50 demos on Trenz TE0802-02 board with ZU2CG and 1GB LPDD4. The system uses a Xilinx DPU unit to accelerate calculations. The DPU unit used in zcu104 or zcu102 does not fit into the used ZU2CG device. For this reason, a reduced DPU configuration is provided as well as precompiled models for demos. This text also describes how to move the system filesystem to the M.2 PCIe SSD. JC 20000 20200 20206 2024 3 https://hdl.handle.net/11104/0342451 S 2023 2023