You probably have heard the name Intel before, but you might not be familiar with the name of Gordon Moore. The latter is the co-founder of Intel and is reportedly worth a cool $12 billion. But what Moore is known for is an observation that he made in the 1960s. He noticed that transistor densities doubled every other year which gave chip makers something of a roadmap and a goal. TSMC, the world’s largest independent foundry, stuffed a little over 52 million transistors into each square mm on chips made using its 10nm process (like 2017’s Snapdragon 835 for example). The Snapdragon 865 Mobile Platform, which powers many Android flagship models this year, is built using the 7nm process which is equipped with nearly 100 million transistors per square mm.
Huang’s Law could be behind Nvidia’s proposed purchase of ARM Holdings
Huang’s Law could be behind Nvidia’s $40 billion bid for ARM Holdings
GPU chips, like the kind Nvidia is known for, can handle many different tasks simultaneously. CPUs, or Central Processing Units, are better at handling single tasks quickly. Some tasks, including ones related to AI, can be sliced up and handled much faster by a GPU chip using less power. And as AI moves from the cloud to on-device use, ARM Holdings is one of the leaders in supplying the necessary components. And that could explain Nvidia’s $40 billion bid to buy the company.
However, there are some caveats. The processing power available from GPU’s can’t be used in every situation. TuSimple’s co-founder and Chief Technology Officer Xiaodi Hou, notes that even in businesses that rely heavily on AI like self-driving trucks, most of the system’s code requires the use of the CPU. And like Moore’s Law, eventually Huang’s Law will no longer be feasible. That still might leave close to a decade for Huang’s Law to be useful. But it won’t be as of widespread use as Moore’s Law has been and continues to be. And by the time chip makers might need to replace Moore’s Law, hopefully something with more widespread capabilities will be developed that has a long future ahead of it. Still, for Nvidia to spend $40 billion to buy ARM, it must have a very good reason to do so.