How “Unified Memory” Speeds Up Apple’s M1 ARM Macs - How-To Geek
Nov 30, 2020 1 min, 56 secs

RAM stands for Random Access Memory.

The CPU then takes all the data it needs for these operations and loads the necessary information into memory.

“What’s the big deal?” Well, first of all, this means faster access to memory, which inevitably improves performance.

Apple calls its approach a “Unified Memory Architecture” (UMA).

The basic idea is that the M1’s RAM is a single pool of memory that all parts of the processor can access.

First, that means that if the GPU needs more system memory, it can ramp up usage while other parts of the SoC ramp down.

Even better, there’s no need to carve out portions of memory for each part of the SoC and then shuttle data between the two spaces for different parts of the processor.

Instead, the GPU, CPU, and other parts of the processor can access the same data at the same memory address.

The graphics card then takes all that data and works on it within its own processor (the GPU) and built-in RAM.

They both work on the same data independently and then shuttle the results back and forth between their memory fiefdoms.

For example, here’s how Apple describes its unified memory architecture on the official M1 website:.

“M1 also features our unified memory architecture, or UMA.

M1 unifies its high‑bandwidth, low‑latency memory into a single pool within a custom package.

As a result, all of the technologies in the SoC can access the same data without copying it between multiple pools of memory.

For NVIDIA, Unified Memory provides a single memory location that is “accessible from any processor in a system.” In NVIDIA’s world, as far as the CPU and GPU are concerned, they are going to the same location for the same data.

However, behind the scenes, the system is paging the required data between separate CPU and GPU memory.

Instead, each portion of the SoC is able to access the exact same location for data in memory.

The bottom line with Apple’s UMA is better performance from faster access to RAM and a shared memory pool that removes performance penalties for moving data around to different addresses.

When your PC runs out of RAM, it carves out available SSD or hard drive storage as a temporary pool of memory.


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