Kontron, a leading global provider of IoT/embedded computer technology (ECT), announces new Computer-on-Modules featuring the Intel Xeon D-2700 and Xeon D-1700 processors for the Internet of Things (IoT). Kontron extends the current COM Express® basic type 7 product family with this new Intel Xeon D-1700 processor series, and has selected the Intel Xeon D-2700 processor series as the 1st platform to adopt the new PICMG® COM-HPC® server-type form factor, as it serves best new technology trends set by the COM-HPC® server specification.
The Intel server-grade platform with up to 10 cores for the Intel Xeon D-1700 and a maximum of 20 cores for the Xeon D-2700 combined with a large memory capacity and PCIe Gen4 capability ensures outstanding performance for challenging application requirements.
The broad network connectivity with up to 100GbE provides ideal support for highest data throughput requirements in demanding network structures.
Complemented by real-time capabilities such as low latency and determinism with Intel Time Coordinated Computing (Intel TCC) and Time Sensitive Networking (TSN) available on selected SKUs, the platform is highly suitable for the usage in embedded industrial automation processes.
With extended temperature and 24×7 / 10 years reliability on selected SKUs, the Intel server-grade platform allows robust implementations for harsh environments and extreme conditions.
The COM Express® basic type 7 module supporting the Xeon D-1700 processor offers scalability from 4 to 10 cores on a robust form factor, 32x PCIe lanes and 4x 10 Gbit LAN interfaces. The module accommodates up to 4x SO-DIMM sockets for a max. of 128GB memory.
The COM-HPC® server module size D (160mm x 160mm) with the Xeon D-2700 processor enables the full scalability from 4 to 20 cores, 48x PCIe lanes and 8x 10 Gbit / 4x 25 Gbit LAN interfaces. The high-performance design accommodates 4x DIMM sockets for a large memory capacity.
The two Computer-on-Module designs target applications in embedded IoT for Industry 4.0, use cases such as test & measurement, autonomous vehicles & robotics as well as numerous potential applications of AI workloads. Applications in the network edge include use cases such as multi-access edge computing (MEC) or 5G RAN.