Atmel® Corporation , a leader in microcontroller and touch technology solutions, announced sampling of the Atmel SAM4S16, the first device in the Cortex™-M4 processor-based family, to lead customers.
STMicroelectronics’ new STM32 series redefines entry-level microcontroller performance and value for smart devices everywhereSTM32C5 with ...
Highlighting its role as a leader in ARM®-based embedded processing, Freescale Semiconductor (NYSE: FSL) announced it will demonstrate its new Kinetis L series microcontrollers (MCUs) built on the ...
NXP could be planning to combine the ARM Cortex-M0 and M3 processors cores in a new multicore device. NXP is already working on new versions of its Cortex-M0 based microcontroller, the LPC1100. It is ...
Energy Micro is offering a development kit for its ARM Cortex-M3-based EFM32 Giant Gecko microcontrollers, which provides users with full J-Trace and J-Link support. According to Andreas Koller, v-p ...
February 22, 2010-- NXP Semiconductors today announced it is one of the first ARM partners to license the latest ARM® Cortex™-M4 processor. The Cortex-M4 processor is a highly efficient solution ...
STMicroelectronics is now delivering the first samples of its new STM32 F3 series of microcontrollers to major OEM customers, enabling early evaluation of this important new line in ST's product ...
Standard provides a single, scalable interface standard across all Cortex-M series processor vendors enabling easier code sharing and re-use CAMBRIDGE, UK – Nov. 12, 2008 – ARM [(LSE: ARM); ...
TOKYO--(BUSINESS WIRE)--Toshiba Electronic Devices & Storage Corporation (“Toshiba”), as a Silicon Partner of Mbed (a device management solution for IoT platforms developed by Arm Ltd), acquired the ...
Highly integrated, innovative and space-saving semiconductor technology that shortens the design process, improves reliability and reduces footprint for the design of mission critical systems.
CMSIS-NN is an open-source library of optimized software kernels that maximize NN performance on Cortex-M cores with minimal memory footprint overhead. Machine learning (ML) algorithms are moving to ...
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