4 Data Center Trends in 2022 That Enterprises Need to Know
The past 2 years of the COVID-19 pandemic have pushed businesses to accelerate their innovation and adoption of new technologies. As we step into 2022 and toward the 2-year anniversary of this global pandemic, it’s important to take a look at how our industry is growing and evolving. Here are some key trends that we are noticing this year.
1) Machine Learning for HPC in Enterprise
High Performance Computing (HPC), traditionally associated with scientific and research fields, has been utilized in enterprise applications for quite some time now, from genetic decoding in the pharmaceutical industry to high-performance trading on Wall Street. The current trend is now for enterprises to start integrating machine learning into HPC. Instead of just using rule-based high-performance computing, enterprises are increasingly using machine learning and artificial intelligence to diversify methods, inquiries, and outcomes to derive more precise, better results.
2) Expansion and Diversification of Open Computing
The Open Compute Project has come a long way since its start 10 years ago when it was focused solely on hardware innovation. Since then, the community has expanded with the gradual influx of enterprise and cloud service providers, who brought with them a great variety of requirement features, ideas, innovations, and challenges. To date, one of the biggest achievements for OCP is ensuring that all the firmware, not just hardware, is open-source; this is an initiative that would typically be driven by an open software community, but OCP has taken the lead on diversifying the open ecosystem. There is currently a lot of demand from the enterprise level for open-source firmware, simply because in the event of an infrastructure attack it would be easier to identify the attacker. As we see this increasing amount of variety and nuance in data center requirements in the open compute project, it becomes clear that OCP is something that will eventually affect every aspect of data center infrastructure.
3) AI and 5G Moving in Tandem
AI and 5G are two of today’s hottest, most talked-about applications and there is much excitement over the directions in which they are heading. However, it is worth noting that they are not two individual applications going on separate paths. In fact, AI and 5G go hand in hand: 5G’s high-speed low-latency connectivity generates massive volumes of data which AI can then process, analyze, and learn from, deriving new insights. 5G networks can more efficiently deploy AI services at scale, and AI can be integrated to address complexities in the 5G network. One real-world example of the AI and 5G’s synergistic relationship would be the dissemination of AI inferencing across the edge and the cloud via 5G in a smart city to improve the performance of Intelligent Connected Vehicles.
4) Liquid Cooling Advancements for Sustainability
Over the last few years, we’ve been seeing growing interest in many creative approaches to liquid cooling. Many major cloud service providers have picked up on this new method and transitioned from air cooling to liquid cooling for their hardware. With sustainability becoming a growing priority, it will be interesting to see what new cooling technologies will emerge, how they will be leveraged, and how this affects hardware design. Aivres aims to use our expertise to innovate and integrate a solution that is both sustainable and cost-effective while requiring as few infrastructure changes as possible.
What’s next for Aivres?
Expanding beyond our current capabilities in AI training hardware, we are making a deeper foray into AI inference applications at the edge, particularly in remote, satellite locations where customers experience more specific challenges. Unlike a hyperscale data center, these edge AI products will not be deployed in a “control environment”, so we will have to consider many more factors – like cooling, extreme weather conditions, dust, and durability – in our design choices and testing process to guarantee the highest performance system under any condition. Pursuing this area will present interesting challenges that will advance and bolster our strengths in product design and engineering.