So heterogeneous computing is part of the reason but not the sole reason. The fast general-purpose CPU cores on the M1,

Apple’s Unified Memory Architecture tries to solve all these problems without having the disadvantages of old school shared memory. They achieve this in the following ways:

Sure Intel and AMD may simply begin to sell whole finished SoCs. But what are these to contain? PC-makers may have different ideas of what they should contain. You potentially get a conflict between Intel, AMD, Microsoft, and PC-makers about what sort of specialized chips should be included because these will need software support.

AMD has also started putting stronger GPUs on some of their chips and moving gradually toward some form of SoC with the accelerated processing units (APU) which are basically CPU cores and GPU cores placed on the same silicon die.

AMD Ryzen Accelerated Processing Unit (APU) which combines CPU and GPU (Radeon Vega) on one silicon chip. Does however not contain other co-processors, IO-controllers, or unified memory.

For ARM, in contrast, this isn’t an issue. Computer makers such as Dell or HP could simply license ARM intellectual property and buy IP for other chips, to add whatever specialized hardware they think their SoC should have. Next, they ship the finished design over to a semiconductor foundry such as GlobalFoundries or TSMC, which manufactures chips for AMD and Apple today.

But we are quickly moving away from that world. In the new SoC world, you don’t assemble physical components from different vendors. Instead, you assemble IP (intellectual property) from different vendors. You buy the design for graphics cards, CPUs, modems, IO controllers, and other things from different vendors and use that to design an SoC in-house. Then you get a foundry to manufacture this.

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food storage containers: Match every box with its lid, check if any jar is broken or warped, and get rid of them. Food containers are great to store food in the refrigerator or bring it at work, but they can quickly turn the pantry into a mess. Clear it up and try to collect them one inside the other to save space.

Now you got a big problem, because neither Intel, AMD, or Nvidia are going to license their intellectual property to Dell or HP for them to make an SoC for their machines.

There is of course a tradeoff in this strategy. Getting this high bandwidth memory (big servings) require full integration which means you take away the opportunity from customers to upgrade their memory. But Apple seeks to minimize this problem by making the communication with the SSD disks so fast, that they essentially work like old fashion memory.

Here we get a big problem with the Intel and AMD business model. Their business models are based on selling general-purpose CPUs, which people just slot onto a large PC motherboard. Thus computer-makers can simply buy motherboards, memory, CPUs, and graphics cards from different vendors and integrate them into one solution.

Apple uses memory which serves both large chunks of data and serves it fast. In computer speak that is called low latency and high throughput. Thus the need to be connected to separate types of memory is removed.

How Mac’s used GPUs before unified memory. There was even an option of having graphics cards outside the computer using a Thunderbolt 3 cable. There is some speculation that this may still be possible in the future.

For Apple this is simple. They control the whole widget. They give you, for example, the Core ML library for developers to write machine learning stuff. Whether Core ML runs on Apple’s CPU or the Neural Engine is an implementation detail developers don’t have to care about.

Some will say unified memory is not entirely new. It is true that different systems have had it in the past. But then the difference in memory requirements may not have been as large. Secondly what Nvidia calls Unified Memory is not really the same thing. In the Nvidea world Unified Memory simply means that there is software and hardware which takes care of automatically copying data back and forth between the separate CPU and GPU memory. Thus from a programmers perspective Apple and Nvidia Unified Memory may look the same, but it is not the same in a physical sense.

Yet there are important reasons why they cannot do this. An SoC is essentially a whole computer on a chip. That makes it a more natural fit for an actual computer-maker, such as HP and Dell. Let me clarify with a silly car analogy: If your business model is to build and sell car engines, it would be an unusual leap to begin manufacturing and selling whole cars.