Axiomtek is proud to announce the launch of iNA600, a DIN-rail industrial-grade network appliance designed for fast and effective customization and deployment. It is created especially for applications such as edge AI inference, cybersecurity and function virtualization. The iNA600 can handle large data transition with computing acceleration. With its modular design, it is highly flexible and can be easily integrated into existing or new networks.
The iNA600 is well equipped with many desirable features, i.e., built-in 16-port Layer 2 managed switch, two DDR4-2666 U-DIMMs for up to 32GB of non-ECC/ECC memory and NVIDIA® MXM GPU card and Intel® Movidius™ M.2 VPU card support to boost the performance of various workloads. The system is scalable, with options of Intel® Core™ i9/i7/i5/i3 or Xeon® processor (Coffee Lake) CPU. It can withstand harsh operating environments with a wide operating temperature range of -20°C to 60°C and offers a 24V DC terminal block power input.
“Our iNA600 features a 16-port L2 managed switch (8-port PoE for optional) which ensures the data flows at a pace that will not overwhelm the sending and receiving devices,” ,” said Gordon Cho, a product manager of the Network Computing Platform Division at Axiomtek. “In addition, this industrial IoT edge computing platform supports Intelligent Platform Management Interface 2.0 (IPMI 2.0) to monitor data transition and operations between servers or systems. It also supports Trusted Platform Module 2.0 (TPM 2.0) to securely store critical data. The iNA600 aims to fulfill system integrators’ needs and meets the changing demands of diverse industrial IoT applications.”
- Intel® Core™ i9/i7/i5/i3 & Xeon® processor (Coffee Lake)
- 2 DDR4-2666 U-DIMM for up to 32GB of memory
- 16 ports L2 managed switch (8 port PoE for optional)
- Supports IPMI 2.0 remote management
- Modular design for flexible and fast provision
- Supports NVIDIA® MXM GPU card (optional)
- Supports Intel® Movidius™ M.2 VPU card (optional)
- Ideal for edge AI inference, cybersecurity and function virtualization