Lattice sensAI Solution Stack Simplifies Deployment of AI/ML Models on Smart Edge Devices

Rhea-AI Summary

Lattice Semiconductor Corporation (NASDAQ: LSCC) has enhanced its Lattice sensAI™ solution stack for AI/ML application development on low power FPGAs. Notable updates include support for TensorFlow Lite, integration with the Lattice Propel™ design environment, and the introduction of Lattice sensAI Studio for ML model training and validation. The new features allow for faster AI/ML inferencing and simplified development processes, aimed at optimizing performance for edge devices like security cameras and industrial robots. These advancements respond to the growing demand for low-power AI solutions.

Positive

• Support for TensorFlow Lite improves performance, running 2 to 10 times faster on FPGAs compared to traditional MCUs.
• New drag-and-drop interface in Lattice Propel allows easier design processes for developers unfamiliar with FPGA.
• Launch of Lattice sensAI Studio simplifies ML model training and deployment, enhancing user experience.

Negative

• None.

Lattice Semiconductor Corporation (NASDAQ: LSCC), the low power programmable leader, today announced enhancements to its award-winning Lattice sensAI™ solution stack for accelerating AI/ML application development on low power Lattice FPGAs. Enhancements include support for the Lattice Propel™ design environment for embedded processor-based development and the TensorFlow Lite deep-learning framework for on-device inferencing. The new version includes the Lattice sensAI Studio design environment for end-to-end ML model training, validation, and compilation. With sensAI 4.0, developers can use a simple drag-and-drop interface to build FPGA designs with a RISC-V processor and a CNN acceleration engine to enable the quick and easy implementation of ML applications on power-constrained Edge devices.

The award-winning Lattice sensAI solution stack provides modular hardware platforms, example demonstrations, reference designs, neural network IP cores, software tools for development, and custom design services to help customers evaluate, develop, and deploy FPGA-based ML/AI applications. (Graphic: Business Wire)

There is growing demand in multiple end markets to add support for low power AI/ML inferencing for applications like object detection and classification. AI/ML models can be trained to support applications for a range of devices that require low-power operation at the Edge, including security and surveillance cameras, industrial robots, and consumer robotics and toys. The Lattice sensAI solution stack helps developers rapidly create AI/ML applications that run on flexible, low power Lattice FPGAs.

“Lattice’s low-power FPGAs for embedded vision and sensAI solution stack for Edge AI/ML applications play a vital role in helping us bring leading-edge intelligent IoT devices to market quickly and efficiently,” said Hideto Kotani, Unit Executive, Canon Inc.

“With support for TensorFlow Lite and the new Lattice sensAI Studio, it’s now easier than ever for developers to leverage our sensAI stack to create AI/ML applications capable of running on battery-powered Edge devices,” said Hussein Osman, Marketing Director, Lattice.

Enhancements to the Lattice sensAI solution stack 4.0 include:

• TensorFlow Lite – support for the framework reduces power consumption and increases data co-processing performance in AI/ML inferencing applications. TensorFlow Lite runs anywhere from 2 to 10 times faster on a Lattice FPGA than it does on an ARM® Cortex®-M4-based MCU.
• Lattice Propel – the stack supports the Propel environment’s GUI and command-line tools to create, analyze, compile, and debug both the hardware and software design of an FPGA-based processor system. Even developers unfamiliar with FPGA design can use the tool’s easy-to-use, drag-and-drop interface to create AI/ML applications on low power Lattice FPGAs with support for RISC-V-based co-processing.
• Lattice sensAI Studio – a GUI-based tool for training, validating, and compiling ML models optimized for Lattice FPGAs. The tool makes it easy to take advantage of transfer learning to deploy ML models.
• Improved performance - by leveraging advances in ML model compression and pruning, sensAI 4.0 can support image processing at 60 FPS with QVGA resolution or 30 FPS with VGA resolution.

For More Information

To learn more about the Lattice technologies mentioned above, please visit:

• www.latticesemi.com/sensAI
• www.latticesemi.com/Propel

About Lattice Semiconductor

Lattice Semiconductor (NASDAQ: LSCC) is the low power programmable leader. We solve customer problems across the network, from the Edge to the Cloud, in the growing communications, computing, industrial, automotive, and consumer markets. Our technology, long-standing relationships, and commitment to world-class support let our customers quickly and easily unleash their innovation to create a smart, secure, and connected world.

For more information about Lattice, please visit www.latticesemi.com. You can also follow us via LinkedIn, Twitter, Facebook, YouTube, WeChat, Weibo, or Youku.

Lattice Semiconductor Corporation, Lattice Semiconductor (& design), and specific product designations are either registered trademarks or trademarks of Lattice Semiconductor Corporation or its subsidiaries in the United States and/or other countries. The use of the word “partner” does not imply a legal partnership between Lattice and any other entity.

GENERAL NOTICE: Other product names used in this publication are for identification purposes only and may be trademarks of their respective holders.

View source version on businesswire.com: https://www.businesswire.com/news/home/20210525005283/en/

FAQ

What enhancements has Lattice made to its sensAI solution stack on September 25, 2023?

Lattice announced new features including support for TensorFlow Lite, an updated Lattice Propel design environment, and the introduction of Lattice sensAI Studio for easier ML model training.

How does TensorFlow Lite perform on Lattice's FPGAs compared to traditional MCUs?

TensorFlow Lite runs 2 to 10 times faster on Lattice FPGAs than on ARM Cortex-M4-based MCUs, significantly reducing power consumption and improving performance.

What applications can benefit from Lattice's sensAI 4.0 enhancements?

The enhancements support AI/ML applications in various low power devices, including security cameras, industrial robots, and consumer robotics.

How can developers utilize the new Lattice Propel environment?

Developers can use the drag-and-drop interface in Lattice Propel to create FPGA designs easily, making it accessible for those with little FPGA experience.