Collaboration enables lower power consumption for IoT applications

Cypress’ high-endurance, scalable SONOS embedded Flash memory is optimised for low power, making it suitable for microcontroller and IoT applications. The technology and design IP will be available for full production by HLMC customers in the second half of 2017. The company claims that Cypress' SONOS embedded nonvolatile memory (NVM) offers significant advantages over other embedded NVM technologies. SONOS provides a competitive cell size with lower manufacturing costs, as it requires only three mask layers to insert it into a standard CMOS process compared with the 9-12 additional masks generally needed for other embedded Flash technologies. SONOS delivers intrinsically high yields, ten years of data retention, 200,000 programme/erase endurance cycles, and robust resistance to soft errors. Cypress has demonstrated the ability to scale SONOS to 40nm and 28nm nodes, expediting future IP development.

"With the escalating demand for low-cost and low-power embedded Flash for IoT applications, we are excited to reach this milestone and look forward to a fast production ramp to meet our customers’ demand,” said Jack Qi Shu, Vice President at HLMC. "Cypress’ SONOS is a cost-effective embedded nonvolatile memory that delivers proven high yields. Its reliability and efficiency are ideal to enable high-volume production for low-power embedded Flash products."

“The combination of HLMC’s robust 55nm LP process technology and manufacturing expertise along with the high-performance and leading reliability of our SONOS Flash memory enabled a smooth path to achieve risk production of these low power embedded Flash products,” said Sam Geha, Senior Vice President of the Memory Products Division at Cypress. “Our collaboration with HLMC is another example of how Cypress is working with the world’s leading foundries to establish SONOS as the industry's top choice for an embedded nonvolatile memory platform. It also demonstrates Cypress’ focus on solving the power-consumption problem facing emerging IoT applications.”