![]() To be sure, it’s always been possible to scale up LPDDR in this fashion, but at least in the consumer SoC space, it’s never been done before. But being power-minded and building their own SoC, Apple has instead built an incredibly large LPDDR5 memory interface M1 Max has a 512-bit interface, four-times the size of the original M1’s 128-bit interface. GPUs require a lot of memory bandwidth, which is why discrete GPUs typically come with a sizable amount of dedicated VRAM using high-speed interfaces like HBM2 or GDDR6. Integrating a high-end GPU means Apple has inherited the design and production costs of a high-end GPU.ĪLUs and GPU cores aside, the most interesting thing Apple has done to make this possible comes via their memory subsystem. That not only includes die space for the GPU blocks themselves, but the fatter fabric needed to pass that much data around, the extra cache needed to keep the GPU immediately fed, and the extra external memory bandwidth needed to keep the GPU fed over the long run. The trade-off for Apple, in turn, is that the M1 inherits the costs of providing such a powerful GPU. ![]() Apple has already been pushing this paradigm for years in its A-series SoC, but this is still new territory in the laptop space – no PC processor has ever shipped with such a powerful GPU integrated into the main SoC. And, again leveraging Apple’s ecosystem advantage, it means they can provide the infrastructure for developers to use the GPU in a heterogeneous computing fashion – able to quickly pass data back and forth with the CPU since they’re all processing blocks on the same chip, sharing the same memory. Bringing what would have been the dGPU into their high-end laptop SoCs eliminates the drawbacks of a discrete part. ![]() But like any other engineering decision, it’s a trade-off: discrete GPUs result in multiple display adapters, require their own VRAM, and come with a power/cooling cost.Īpple has long been a vertically integrated company, so it’s only fitting that they’ve been focused on SoC integration as well. ![]() It’s cost and performance effective: you only need to add as big of a dGPU as the customer needs performance, and even laptop-grade dGPUs can offer very high performance. Traditional OEMs have been fine with a small(ish) CPU and then adding a discrete GPU as necessary. It’s the latter that is arguably the unique aspect of Apple’s position right now. Ultimately, all of this has pushed Apple to develop their own GPU architecture, not only to offer a complete SoC for lower-tier parts, but also to be able to keep the GPU integrated in their high-end parts as well. For their largest 15/16-inch MacBook Pros, Apple has been able to turn to discrete GPUs to make up the difference, but the lack of space and power for a dGPU in the 13-inch MacBook Pro form factor has been a bit more constraining. But even Iris was never quite enough for what Apple would like to do. This has led to Apple using Intel’s advanced Iris iGPU configurations over most of the last 10 years (often being the only OEM to make significant use of them). Though often rooted in efficiency gains and getting incredibly taxing tasks off of the CPU, these have also pushed up Apple’s GPU performance requirements. GPU-accelerated composition (Quartz Extreme), OpenCL, GPU-accelerated machine learning, and more have all been developed or first implemented by Apple. With tight control over their ecosystem and little fear over pushing (or pulling) developers forward, Apple has been on the cutting edge of expanding the role of GPUs within a system for nearly the past two decades. Last year Apple proved that it could develop competitive, high-end CPU cores for a laptop now they are taking their same shot on the GPU side of matters.ĭriving this has been one of the biggest needs for Apple – and one of the greatest friction points between Apple and former partner Intel – which is GPU performance. While Apple doesn’t break down how much of their massive, 57 billion transistor budget on the M1 Max went to the GPU, it and its associated hardware were the only thing to be quadrupled versus the original M1 SoC. Section by Ryan Smith GPU Performance: 2-4x For Productivity, Mixed GamingĪrguably the star of the show for Apple’s latest Mac SoCs is the GPU, as well as the significant resources that go into feeding it.
0 Comments
Leave a Reply. |
Details
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |