Cyclone Board FPGA reference board for industrial edge and TSN applications

From Margit Kuther | Translated by AI 1 min Reading Time

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Arrow Electronics has launched the flexible Cyclone 10LP Refkit Industrial developed in collaboration with Trenz Electronic. This builds on the already proven commercial reference design of the Cyclone 10LP.

Cyclone 10LP Refkit: for smart and networked applications.(Image: Arrow)
Cyclone 10LP Refkit: for smart and networked applications.
(Image: Arrow)

The Cyclone 10LP Refkit Industrial with the designation TEI0009-02-PHIQ2R is intended to significantly accelerate the development of smart and networked solutions such as Industrial IoT, automation, communication, data processing, and Smart Energy.

Based on the already available commercial Cyclone 10LP reference kit, Arrow has now optimized the existing design for industrial use in collaboration with Trenz Electronic, co-developer of the commercial board.

Technical specifications

The new Cyclone 10LP Refkit Industrial offers an integrated 128-MBit flash memory chip for executing complex and flexible applications and is suitable for applications with industrial Ethernet connections and Time Sensitive Networking (TSN). All flash and DRAM chips meet common industrial temperature requirements.

The heart of the board, Intel's FPGA Cyclone 10 LP 10CL055YU484I7G, is specially designed for high speeds and use under industrial temperatures. The FPGA contains 55,000 logic elements and 156 DSP blocks with 2.34 MBit integrated memory and 321 I/Os, which the developers can configure for their applications.

Arrow assists with modifications

Arrow offers flexible support service for customers, including assistance with custom PCB modifications, development of alternative form factors if required for adaptation, integration of alternative building blocks on the board, as well as harnessing the full potential of the integrated Intel FPGA Cyclone 10 LP.

Intel's Cyclone 10 LP is designed for industrial and embedded applications and is particularly distinguished by extensive functions and high performance for edge applications, low power consumption, high efficiency, and sufficient capacity to execute AI algorithms.

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