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Arteris Collaborates with SiMa.ai to Optimize ML Implementation With Efficient Topology Interconnect IP for the Embedded Edge

Daniel Nenni

Admin
Staff member
SAN JOSE and CAMPBELL, Calif. -- August 30, 2022 - Arteris Inc. (Nasdaq: AIP), a leading provider of system IP consisting of network-on-chip (NoC) interconnect and IP deployment software that accelerate system-on-chip (SoC) creation, today announced its collaboration with SiMa.ai integrating the Arteris highly adaptable FlexNoC interconnect IP into the SiMa.ai Machine Learning System-on-Chip (MLSoC). The joint work enables customers to meet the high speed and low latency requirements necessary for implementing AI/ML computing at the edge.

Arteris interconnect IP capabilities enable SiMa.ai’s SoC and ML accelerator IPs to connect seamlessly and efficiently, which is critical to delivering a push-button experience that SiMa.ai customers need. The MLSoC platform is available to customers now.

“The powerful combination of SiMa.ai accelerators and Arteris FlexNoC IP enables the interleaving of data between ML accelerators, allowing the MLSoC to maintain quality of service and performance while moving calculations in and out of memory,” said Michal Siwinski, chief marketing officer, Arteris Inc. “SiMa.ai delivers an embedded edge solution that is quite revolutionary, and we are proud that Arteris can be a key building block of that innovation.”

“Since the inception of our MLSoC Platform, we have been utilizing Arteris interconnect IP,” said Srivi Dhruvanarayan, VP hardware engineering, SiMa.ai. “The configurability and adaptability of the Arteris FlexNoC and the ability to compare and contrast implementations were crucial during the design process. We appreciate everything Arteris has done in helping us get to this point and look forward to continuing our great collaboration for future products.”

About Arteris
Arteris is a leading provider of system IP, consisting of network-on-chip (NoC) interconnect IP and IP deployment technology to accelerate system-on-chip (SoC) semiconductor development and integration for a wide range of electronic products. Vertical applications include automotive, mobile, consumer electronics, enterprise datacenters, 5G communications, industrial and IoT, leveraging technologies such as AI/ML and functional safety for customers such as BMW, Bosch, Baidu, Mobileye, Samsung, Toshiba and NXP. Arteris IP products include the FlexNoC® interconnect IP, Ncore® cache coherent IP, CodaCache® standalone last level cache, ISO 26262 safety, Artificial Intelligence, automated timing closure and Magillem SoC assembly automation. Customer results obtained by deploying Arteris IP include higher performance, lower power and area, more efficient design reuse and faster SoC development, leading to lower development and production costs. For more information, visit www.arteris.com or find us on LinkedIn: https://www.linkedin.com/company/arteris.

© 2004-2022 Arteris, Inc. All rights reserved worldwide. Arteris, Arteris IP, the Arteris IP logo and other Arteris marks are trademarks of Arteris, Inc. or its subsidiaries. Other names and brands may be claimed as the respective property of other entities.

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.  For more information, visit: sima.ai

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


Contact:
Nina Korfias
fama PR for SiMa.ai
Sima@famapr.com


Michele Kinman
The Edge Marketing
408-218-8815
mkinman@the-edgemarketing.us
 
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