IP Block – IP for CAN and CAN FD
IP Block: The Synective CAN 2.0/CAN FD IP core implements a complete CAN controller for integration into FPGAs and ASICs.
The IP is compliant to the new ISO 11898-1:2015 standard, supporting both standard CAN and CAN FD. CAN FD is a new version of the CAN standard, where the payload is sent at a higher bitrate (up to 10 Mbit/s). The payload can also be up to 64 bytes long, compared to 8 bytes for normal CAN.
The IP is available for most Xilinx, Altera, Lattice and Microsemi FPGA devices, supporting native bus interfaces like AXI, Avalon and APB. Processor integration is available for SOC type of FPGAs.
The IP is designed with many features for diagnosis and CAN bus debugging, making it ideal for data loggers and similar devices. All these features can be disabled at build time, to minimize footprint for more traditional applications.

CAN FD, both ISO and non-ISO
CAN 2.0A and 2.0B
Small Footprint
System Bus Interfaces: AXI, Avalon, APB
Common receive interface for multiple Channels
Configurable Hardware Buffer Size
Status Updates in Data Stream
Interrupt Logic
Transmit Rate Adaptation
Low-Latency DMA with Interrupt Rate Adaptation
Timestamps
Listen Only-mode
Auto Acknowledge Mode
Self-Listen-Mode
Single Shot Mode
Separate System Bus and Core Clocks
Support for Xilinx, Intel, Lattice and Microsemi FPGAs
Want to know more?
High Performance Embedded
Synective Labs provides high performance embedded solution to a wide range of customers, with a focus on computational and data intense problems.
FPGA/ASIC design
Synective Labs is a leading design house and consulting company within FPGA and ASIC design in the Nordic region.
IP block
The Synective CAN 2.0/CAN FD IP core implements a complete CAN controller for integration into FPGAs and ASICs.
Image and Signal Processing
Synective Labs specializes in algorithm development for image and signal processing, with many years of experience from advanced camera, radar and sensor systems.
Server Based Acceleration
Synective Labs work with some of the world’s leading providers of hardware for server-based acceleration, in order to reach state of the art results.
Machine Learning
Synective Labs is actively researching and implementing machine learning with deep neural networks designed to fit on small edge FPGAs and other low power embedded systems.