What Apple’s M1 chip means for big data and analytics

This month, Apple announced its M1 chip for Mac. The M1 uses system-on-a-chip (SoC) technology that integrates all of the functionality that formerly had to be supplied by multiple chips on one single chip.

Apple said that the M1 chip is “remarkably complex—packing the largest number of transistors we’ve ever put into a single chip. It’s also the first personal computer chip built using industry‑leading 5‑nanometer process technology.”

While SoC is a new step for Apple’s Mac architecture, it is not a new step in IT.

With significantly smaller footprints, SoCs are already widely used on iPhones, Androids, and other smaller digital devices. They are one reason that when I benchmark an internet search on my iPhone versus my non-SoC Mac, the iPhone completes the search first.

SoC is also a widely used technology in Internet of Things (IoT) edge sensors; and in artificial intelligence (AI), deep learning and neural networks, where it’s important to expedite high-performance processing.

“[The] AI chips include graphics processing units (GPUs), field-programmable gate

arrays (FPGAs), and application-specific integrated circuits (ASICs) that are specialized for AI,” wrote Saif M. Khan and Alexander Mann of the Georgetown University Center for Security and Emerging Technology. “General-purpose chips like central processing units (CPUs) can also be used for some simpler AI tasks, but CPUs are becoming less and less useful as AI advances.”

With Apple’s announcement, this SoC power is being incorporated into desktop devices as well as their handheld counterparts. From a big data perspective, when SOC is coupled with 5G bandwidth, SoC will speed time to market of big data such as videos, photos, schematics, voice records, etc., and make them more readily available to business users and consumers on a plurality of devices. This helps achieve one of the four Vs of big data—velocity—and it will also accommodate greater data volumes.

How M1 and other SoCs can help businesses

Business units throughout the enterprise will find it easier to access and manipulate big data such as videos, photos, voice recordings, etc., and the delivery quality of remote conferencing platforms like Zoom and Slack will improve. Collectively these advances will put more real-time and near-real-time big data directly into users’ hands.

As more compute gravitates toward the SoC architecture, IT will need to evaluate its systems and applications under management to see which vendors are ahead of the curve in adapting their products to work on an SoC architecture, and which are lagging. For a time, this will require a “split” architecture between SoC systems and systems that run on more traditional CPU-style chipsets.

Security and intellectual property (IP) protection could benefit

“We put IP (proprietary intellectual property) into chips …that allows you to optimise software for safety and security,” Rupert Baines, CEO of UltraSoC, which provides embedded monitoring hardware, told eeNews Europe. With security protections as well as other processing functionality embedded directly into each chip, security is hardened and offers additional protection for systems and applications.

What to expect next from SoC

As SoC technology gains a foothold in desktop machines like Macs and in vendor-supplied AI and big data systems, AI output, capability, and processing will become more universally available to users.

This enhanced AI speed to market will assist IT and data scientists in delivering analytics results to the end business and shorten time to decision.