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SiMa.ai Achieves First Silicon Success with Synopsys Solutions, Launching the Industry’s Most Power-Efficient MLSoC Platform for the Embedded Edge

Business Wire India
SiMa.ai, the machine learning (ML) company enabling effortless deployment and scaling at the embedded edge, today announced it has achieved first silicon success for its new Machine Learning System-on-Chip (MLSoC) Platform using Synopsys’ design, verification, IP and design services solutions. The SiMa.ai MLSoC was designed and verified using Synopsys tools and incorporated a broad range of Synopsys IP, including the Synopsys ARC® EV Processor for real-time vision processing. The collaboration between SiMa.ai and Synopsys optimizes power, flexibility, scalability and future proofing for robotics, smart vision, government, autonomous vehicles, drones and healthcare at the embedded edge.
 

The SiMa.ai MLSoC, which is shipping to customers now, offers a heterogeneous compute platform to address any computer vision application and deliver a 10x better performance/power solution – all with a push-button software experience. It operates at the lowest power, effortlessly scaling in minutes for computer vision applications.
 

“SiMa.ai is the engine making machine learning at the edge a reality,” said Krishna Rangasayee, CEO and Founder, SiMa.ai. “World-class partners are essential to enabling that mission. Synopsys and SiMa.ai know the barriers and pain points to ML adoption and scaling and we’re solving them together. The powerful combination of SiMa.ai and Synopsys perfectly positions our customers for success because we are using Synopsys’ IP, design, verification and emulation products, as well as design services, to fuel our innovation.”
 

 

Embedded edge applications can now process the entire computer vision application pipeline, which consists of sensor data capture, pre-processing, inference, post-processing and more, via the integrated Synopsys ARC® EV74 embedded vision processor and SiMa.ai’s machine learning technology in the MLSoC Platform. Embedded edge customers can partition workloads across the heterogeneous compute architecture of SiMa.ai’s MLSoC Platform to achieve the best accuracy and performance at the lowest power and latency, all at the push of a button.
 

“As advanced machine learning capabilities are developed for the edge, designers require superior hardware technology and software tools to optimize power and performance while simplifying ML deployment,” said John Koeter, senior vice president of marketing and strategy for the Synopsys Solutions Group. “By providing a broad IP portfolio, optimized implementation tools, and industry-leading hardware and software verification solutions, Synopsys is enabling innovative companies like SiMa.ai to meet their advanced design needs, accelerate SoC development, and achieve first-time-right silicon.”
 

The SiMa.ai MLSoC Platform is available today. For more information, visit https://sima.ai/get-10x-now/.
 

About SiMa.ai
 

SiMa.ai is a Machine Learning company delivering the industry’s first software-centric, purpose-built MLSoC platform. With push-button performance, we enable Effortless ML deployment and scaling at the embedded edge by allowing customers to address any computer vision problem while achieving 10x better performance at the lowest power. Initially focused on computer vision applications, SiMa.ai is led by technologists and business veterans backed by a set of top investors committed to helping customers bring ML on their platforms.
 

© Copyright 2022 SiMa Technologies, Inc. SiMa.ai logo and other designated brands included herein are trademarks in the United States and other countries.
 

SiMa.ai Achieves First Silicon Success with Synopsys Solutions, Launching the Industry’s Most Power-Efficient MLSoC Platform for the Embedded Edge
 

SiMa.ai Achieves First Silicon Success with Synopsys Solutions, Launching the Industry’s Most Power-Efficient MLSoC Platform for the Embedded Edge

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SiMa.ai Achieves First Silicon Success with Synopsys Solutions, Launching the Industry’s Most Power-Efficient MLSoC Platform for the Embedded Edge

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