Dynics, Inc., a U.S.-based manufacturer of industrial-grade computer hardware, visualization software, network security, network monitoring and software-defined networking solutions, today announced the XiT4 Inference Server, which helps industrial manufacturing companies increase their yield and provide more consistent manufacturing quality.
Artificial intelligence (AI) is increasingly being integrated into modern manufacturing to improve and automate processes, including 3D vision applications. The XiT4 Inference Server, powered by the NVIDIA T4 Tensor Core GPUs, is a fan-less hardware platform for AI, machine learning and 3D vision applications. AI technology is allowing manufacturers to increase efficiency and throughput of their production, while also providing more consistent quality due to higher accuracy and repeatability. Additional benefits are fewer false negatives (test escapes) and fewer false positives, which reduce downstream re-inspection needs, all leading to lower costs of manufacturing.
The XiT4 is powered by an NVIDIA T4 Tensor Core GPU, which features 320 NVIDIA Turing Tensor Cores and 2,560 NVIDIA CUDA cores for critical processes that can benefit from processing large sets of data very efficiently. The T4 supports a variety of AI frameworks for training and inference and is supported by several SDKs, such as NVIDIA DeepStream, for data analysis and visualization. The XIT4 also features an Intel Core i7-8700T CPU, 32 GB DDR4 RAM and up to several terabytes of SSD storage capacity. Operating system choices are Linux Ubuntu 20.04 LTS and Windows 10 Enterprise 2019 LTSC. Additionally, other Linux distributions are available upon request.
Standard I/O configuration includes three USB 3.0, four 1 Gb Ethernet ports and DVI video with additional USB ports and options for 10 Gb Ethernet, 1 Gb PoE+, and fiber optic. The system uses an L-coded cable for 24vdc input supply power.
The XiT4 is rated for 24/7 operation at 0 – 50 deg C and a standard ingress protection rating of IP50 with an option for IP65. This on-premises solution allows for data collection and computing at the edge complementing current or future cloud solutions.
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