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Embedded Technology Trends for 2021

An Embedded system is typically a combination of electronic hardware elements such as silicon (micro), firmware, Field Programmable Gate Array (FPGA), and software components like Real-time Operating Systems (RTOS). Generally, embedded systems are powered by software integrated circuits that are designed to be programmed. More industries, products, and their associated services now rely on embedded systems than ever before.

The market size of embedded systems is predicted to hit US$127.50 billion by 2027 with a 5.70% CAGR, according to Data Bridge Market Research. The newest wave of embedded systems is bringing innovation to a wide range of applications, often using Artificial Intelligence and machine learning, including IoT security, robotics, medical devices, autonomous vehicles, vision technologies, System-on-Chip solutions, and more.

Software dominates the embedded system design process; analysis estimate that software development can now consume up to 70% of a project’s resources. Traditionally, software development started when the hardware arrived, but not anymore: software engineers are using virtual prototypes to get their projects started in time to meet the deadlines.

Virtual platforms are ideal for system-level performance optimisation and software development before, during and after hardware design and manufacture. Virtual models are often easier to reconfigure, deploy, and debug than electronic hardware, leading to quicker development cycles and faster time to market.

Read on to discover some of the latest embedded tech announcements in 2021.

Open Flashloader programs any RISC-V system

SEGGER’s new Open Flashloader enables engineers to program any RISC-V system and works with any software that supports J-Link. Its tiny size, fitting into just 2 kB of RAM, allows J-Link debug probes to download directly and into RISC-V microcontrollers and SoCs’ flash memory.

SmartClockTM keeps an eye on your car clock

Silicon Labs is building new SmartClockTM features into its Si5332-AM clock generators, which actively monitor automotive clocks to detect faults and provide a backup in case of failure. If it detects a fault, it transmits the information to external safety managers or system microcontrollers and tells the chip to switch to backup.

Quadro MXM GPU boards boost capacity for smart factories

Cincoze has created two new Quadro MXM GPU boards for its GM-1000 machine vision line modules. The MXM-RTX3000 and MXM-T1000  have the extra GPU capacity smart factories need to rapidly adopt machine vision, with environmental perception applications like identification, measurement, positioning and more.

Both boards  use the latest version of NVIDIA’s Quadro Turing GPU architecture and support GDDR6 memory; the MXM-RTX3000 has a 6GB capacity and 336 GB/s memory bandwidth, and the slightly smaller MXM-T1000 has 4 GB capacity and 192 GB/s memory bandwidth, and runs on only 50W of power, making it a green solution to high-speed computing.

New deep learning platform accelerates AI at the edge

ADLINK Technology’s new DLAP x86 deep learning acceleration platforms are optimised to boost the performance of edge AI in industrial applications by speeding up memory-hungry, compute-intensive learning and inferencing tasks. They also take advantage of NVIDIA's Turing GPU architecture and are designed to withstand hard knocks, strong vibrations, and temperatures up to 500C, making them ideal for manufacturing, industrial and healthcare environments.

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