Lattice Circuitry Printed 514570034

Low-Power FPGA Targets Low-Cost Apps

June 24, 2020
Lattice Semiconductor just released its Certus-NX FPGA family that has its sights set on high-volume, low-cost applications.
Lattice Semiconductor’s Certus-NX FPGA family is designed to handle high-volume, low-cost applications (Fig. 1). The new family is smaller, faster, and more power-efficient that its predecessor. It includes hard interfaces for Gigabit Ethernet and Gen 5 PCI Express. Chips are available with up to 192 I/O pins.

Developers can take advantage of the low-power or high-performance mode. There’s a mix of DSP blocks, embedded memory, and up to 40K logic cells. Off-chip DDR3 memory is accessible via a 1066-Mb/s interface; differential I/O SERDES work up to 1.5 Gb/s. LVDS and subLVDS interfaces are supported. Versions are available with an ADC, too.

The instant-on operation of the chips allows I/O to be configured within 3 ms. Total device configuration takes 8 to 14 ms.

The Certus-NX is the second Nexus architecture solution from Lattice (Fig. 2). The initial version was the CrosssLink-NX. The Nexus platform is based on fully depleted silicon-on-insulator (FDSOI); the FD-SOI support comes from Samsung. It reduces transistor leakage in half versus bulk CMOS.

The Certus-NX will be used in a range of applications, including connected IoT solutions. On-chip security support allows a public key to be stored to verify information coming from outside (Fig. 3); the Elliptic Curve Digital Signature Algorithm (ECDSA) is used for this purpose. The chips also support AES-256 encryption.

The Certus-NX comes in package sizes ranging from a 6- × 6-mm csfBGA to 14- × 14-mm csfBGA. The compact layout delivers twice the number of I/O pins in these form factors.

Lattice’s Radiant software-development suite supports the Certus-NX as well as its other FPGA solutions like the CrossLink-NX. Certus-NX also works with Lattice’s SensAI. The SensAI tools provide machine-learning (ML) support, including FPGA-based binarized-neural-network (BNN) and convolutional-neural-network (CNN) acceleration. The SensAI neural-network compiler can accept models from frameworks like Caffe and TensorFlow.

Sponsored Recommendations

The Importance of PCB Design in Consumer Products

April 25, 2024
Explore the importance of PCB design and how Fusion 360 can help your team react to evolving consumer demands.

PCB Design Mastery for Assembly & Fabrication

April 25, 2024
This guide explores PCB circuit board design, focusing on both Design For Assembly (DFA) and Design For Fabrication (DFab) perspectives.

What is Design Rule Checking in PCBs?

April 25, 2024
Explore the importance of Design Rule Checking (DRC) in manufacturing and how Autodesk Fusion 360 enhances the process.

Unlocking the Power of IoT Integration for Elevated PCB Designs

April 25, 2024
What does it take to add IoT into your product? What advantages does IoT have in PCB related projects? Read to find answers to your IoT design questions.

Comments

To join the conversation, and become an exclusive member of Electronic Design, create an account today!