"We are convinced that the AI Embedded Computer will help shape the future of industrial automation," explains Florian Egger, Sales Manager at Syslogic. Accordingly, Syslogic is working flat out to develop a complete deep learning solution together with a software partner. In addition, Syslogic hardware engineers are already planning an AI box PC with the new Nvidia Xavier platform. However, they are relying on Nvidia's Jetson TX2i module for the first AI box PC.
The heart of the Jetson TX2 is the ARM-SoC Tegra X2 with the code name Parker. It combines two computing cores with the Denver 2 microarchitecture developed by Nvidia itself with four Cortex A57 cores and a Pascal GPU. The latter has 256 shader cores. The embedded computer thus supports CUDA applications (CUDA: Compute Unified Device Architecture) and is suitable for various AI sub-areas such as machine vision, intelligent control, and deep learning. Thanks to optional Wi-Fi, GPS, and LTE functions, the AI computer can be easily integrated into the industrial internet of things (IIoT).
Axiomtek also uses Nvidia's Jetson-TX2 module with up to 8 GB LPDDR4 memory and an 802.11ac Wi-Fi module with Bluetooth for eBOX560-900-FL. It supports the Nvidia JetPack 3.2 SDK, as well as TensorRT, cuDNN, CUDA Toolkit, VisionWorks, GStreamer, and OpenCV. The slim and rugged box PC is IP40 certified and ready for use in temperatures from -10 °C to +50 °C and vibrations up to 3G. The eBOX560-900-FL has one USB 2.0 port, two Gigabit Ethernet ports, one HDMI 2.0 port and four SMA-type antenna connectors. The fanless system has an additional 32 GB eMMC and an M.2 SSD PCIe 2.0 x4 socket. The PCI Express mini card slot allows the PC to be connected via 3G/4G/LTE/GPRS, Wi-Fi, and Bluetooth.
With dBOX800, Axiomtek offers a further AI-Edge computer that uses the same hardware base as eBOX560-900-FL and therefore differs mainly in the housing and the integrated LTE module.
ICP Germany has chosen a different path for its AI-IPC and is using Intel hardware. The Tank-870AI is an inference system with pre-installed Ubuntu 16.04 LTS operating system and ready-to-use software. The hardware is based on Intel's Skylake or Kaby Lake CPUs and has up to 32 GB of pre-installed memory. Different AI accelerator cards can be used via the available slots: Mustang-200 is a dual CPU card with Intel's i7/i5 processors. Mustang-F100-A10 uses an FPGA for acceleration and Mustang-V100-MX8 uses Intel's AI processor Movidius.
All the computer systems described prove that AI applications do not necessarily have to run in a cloud, but can also be executed on site.