If you’ve considered purchasing a recent Mac, you might have encountered the term unified memory instead of RAM. But what does it mean, and how is it different from conventional RAM? Let’s delve into the details.
What Is Unified Memory?
People often think the Apple silicon chip is merely a CPU, but it’s actually an SoC (System-on-a-Chip). This includes various components such as the CPU, GPU, Neural Engine, and more within a single package.
All these components need a temporary data storage solution to function, and that’s where Apple’s unified memory comes into play. Unified memory is composed of highly efficient DRAM chips located within the same package, resulting in lower power consumption and enhanced performance.
The primary benefit of this setup is the ability to use a single pool of high-speed, low-latency memory accessible to all components. This removes the necessity to copy data between different memory locations, a process that is both time-consuming and power-intensive.
How Is Unified Memory Different From Traditional RAM?
In a traditional system, the CPU and GPU have separate architectures, relying on different types of RAM to fetch data. There are typically two types of RAM in such systems: system RAM and VRAM (video memory).
VRAM handles data transfer to the GPU, while system RAM serves the CPU. The most significant bottleneck with traditional RAM is that it connects to the CPU via a motherboard socket, which is generally slower than RAM integrated within an SoC.
Apple silicon, however, mounts the RAM and the SoC on the same substrate. The RAM, although not part of the SoC, is connected to it using a silicon interposer.
In simpler terms, this architecture places RAM very close to the components that need to access it, eliminating the bottlenecks and making the system more power-efficient and faster. This setup is also suitable for GPU use without any compromises.
Is Unified Memory Faster Than Traditional RAM?
As previously mentioned, traditional settings maintain separate memory pools for the GPU and CPU. Apple, conversely, allows the GPU, CPU, and Neural Engine to use the same memory pool. This means data does not need to be transferred between different memory systems, enhancing overall efficiency.
This unique memory architecture results in high data bandwidth for the SoC. For instance, the M2 Ultra provides 800GB/s of bandwidth, significantly higher than discrete GPUs like the AMD Radeon RX 7800 XT, which offers 624GB/s.
However, the M2 Ultra is not the top performer in its class. NVIDIA’s GeForce RTX 4090 and AMD’s Radeon RX 7900 XTX offer even higher bandwidths of 1008GB/s and 960GB/s, respectively, along with superior overall performance.
This high bandwidth enables the CPU, GPU, and Neural Engine to access large data pools in nanoseconds. However, it also means you might exhaust memory more quickly when performing tasks that utilize both the CPU and GPU, such as gaming, since the RAM is shared across the entire SoC.
How Much Unified Memory Do You Need?
The primary drawback of Apple’s unified memory architecture is that the memory is integrated into the SoC, making it non-upgradable. Apple typically charges a high premium for memory upgrades, such as $200 for 16GB of unified memory. It’s crucial to evaluate your memory needs both now and for the future carefully.
Using an M1 MacBook Air with 8GB of unified memory, I’ve found it sufficient for general tasks, though it occasionally struggles. Hence, I intend to configure my next Mac with at least 16GB of unified memory. If you’re uncertain about your needs, we have an extensive guide to help you determine how much memory is appropriate for your Mac.
Though the initial cost of higher unified memory might seem substantial, it can be more cost-effective than having to purchase a new Mac if you find your current configuration unsuitable for your tasks in a few years.