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Eta Compute Selects IAR Embedded Workbench as the Preferred Toolchain for New Neural Network-based AI SoCs


News provided by

IAR Systems

24 Jan, 2019, 14:10 GMT

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The company selects IAR Systems' code quality and extensive support services

UPPSALA, Sweden, January 24, 2019 /PRNewswire/ --

IAR Systems®, the future-proof supplier of software tools and services for embedded development, announces that it has been selected by Eta Compute, the company that removes power as an obstacle for the infinite Internet of Things (IoT), as the preferred tools vendor for its new innovative machine-learning SoCs. Using IAR Embedded Workbench® for Arm® with Eta Compute SoCs, developers will be able to fully leverage the power-efficient features of the SoC, boosting development of AI-based IoT applications.

Eta Compute is part of the Arm DesignStart™ program, which enables the creation of custom SoCs with low cost and fast access, and provides a verified subsystem for a wide range of applications, including IoT, gateways, sensor, control and mixed signal SoCs, as well as design services and support. At Arm TechCon in October 2018, Eta Compute won the Design Innovation of the Year and the Best Use of Advanced Technologies awards. By implementing the popular and proven Arm Cortex®-M3 architecture with dramatically improved power efficiency, Eta Compute opened up opportunities for applying more comprehensive AI processing on edge devices.

"IAR Systems' tools have a demonstrated capability of generating the smallest, most efficient code, while maintaining application integrity," said Paul Washkewicz, Vice President and co-founder of Eta Compute. "IAR Embedded Workbench is fast and lightweight, resulting in an IDE that aids in development. Additionally, their quick, knowledgeable, and professional support teams help accelerate the time it takes to move from prototype to production."

"Eta Compute is an exciting startup that has accomplished game changing technology in the three years since its start," says Robert DeOliveira, Director Strategic Sales, IAR Systems. "They are actively exploring new application areas for their technology. Their decision to standardize development on IAR Embedded Workbench underscores the importance of having sophisticated, smart tools to overcome challenges and complexities in next-generation embedded applications."

IAR Embedded Workbench is the most widely used C/C++ compiler and debugger toolchain for developing Arm Cortex-based applications. Powerful add-ons and integrations, including easy-to-use debugging probes and integrated code analysis tools, add additional capabilities. More information about the toolchain is available at www.iar.com/iar-embedded-workbench.

Eta Compute's DIAL™ Technology is the world's lowest power embedded platform that delivers significantly more machine intelligence to energy-constrained products. For a given power source, DIAL delivers the most compute power enabling local intelligence on the device, which increases accuracy and speed of decisions. Processing at the network edge also reduces power hungry RF transmissions extending battery life while improving security and privacy. For more information visit EtaCompute.com or contact the company via email at info@etacompute.com.

Editor's Note: IAR Systems, IAR Embedded Workbench, Embedded Trust, IAR Connect, C-SPY, C-RUN, C-STAT, IAR Visual State, IAR KickStart Kit, I-jet, I-jet Trace, I-scope, IAR Academy, IAR, and the logotype of IAR Systems are trademarks or registered trademarks owned by IAR Systems AB. All other product names are trademarks of their respective owners. 

IAR Systems Contacts

Tora Fridholm, Product Marketing Manager, IAR Systems
Tel: +46-18-16-78-00 Email: tora.fridholm@iar.com

Stefan Skarin, CEO, IAR Systems
Tel: +46-18-16-78-00 Email: stefan.skarin@iar.com

This information was brought to you by Cision http://news.cision.com

http://news.cision.com/iar-systems/r/eta-compute-selects-iar-embedded-workbench-as-the-preferred-toolchain-for-new-neural-network-based-a,c2725259

The following files are available for download:

https://mb.cision.com/Main/386/2725259/981107.pdf

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