DDR4 DRAM Lives On The Edge

To keep up with the unrelenting growth of the IoT and the challenges of harsh environments, Innodisk fortifies its DRAM portfolio with the DDR4 2666 SODIMM series. The memory modules are tailored for edge devices and can handle large temperature variations via an industrial design. Another worrying trend is the sulfur pollution seen in many industries. To combat this, Innodisk is implementing across-the-board anti-sulfuration measures in all DDR4 modules.

 

Edge computing is an integral concept of IoT. The on-site device handles analytics and computing, thus decreasing bandwidth to the centralized server. However, this balancing of computational power causes a shift of increasingly powerful components to remote areas.

Free Monthly Newsletter

Compelling read? Subscribe to FierceEmbeddedTech!

The embedded tech sector runs the market’s trends. FierceEmbeddedTech subscribers rely on our suite of newsletters as their must-read source for the latest news, developments and analysis impacting their world. Sign up today to get news and updates delivered to your inbox and read on the go.

 

Applications such as smart-city solutions, petrochemical installations, and mining facilities must all endure challenging conditions from weather, temperature and pollution. It is under these conditions that the high-reliability 2666 MT/s DDR4 WT SODIMM excels – bringing IoT to the very forefront of harsh and challenging environments.

 

Another risk factor in these environments is sulfide gasses. These mostly stem from pollution and mining, oil and gas activities, and can have a detrimental effect on DRAM modules. Even in lower quantities, the sulfide reacts with silver alloys inside the chips and hampers performance, ultimately causing product failure. According to reports, sulfuration is also a prominent issue in data centers where the air intake also sucks in contaminants from the surroundings. For more details, visit Innodisk.

Read more on

Suggested Articles

Critics are concerned about a false sense of public health safety when temperature scanning is used in hospitals and other settings

Machine learning challenge will look for vocal communication between elephants and other behaviors

Iowa State University researchers are working with NSF grant