Imagination Announces A-Series GPU Architecture: "Most Important Launch in 15 Years"

HyperLane Technology

Another new addition to the A-Series GPU is Imagination's “HyperLane” technology, which promises to vastly expand the flexibility of the architecture in terms of multi-tasking as well as security. Imagination GPUs have had virtualization abilities for some time now, and this had given them an advantage in focus areas such as automotive designs.

The new HyperLane technology is said to be an extension to virtualization, going beyond it in terms of separation of tasks executed by a single GPU.

In your usual rendering flows, there are different kinds of “master” controllers each handling the dispatching of workloads to the GPU; geometry is handled by the geometry data master, pixel processing and shading by the 3D data master, 2D operations are handled by the 2D data, master, and compute workloads are processed by the, you guessed it, the compute data master.

In each of these processing flows various blocks of the GPU are active for a given task, while other blocks remain idle.

HyperLane technology is said to be able to enable full task concurrency of the GPU hardware, with multiple data masters being able to be active simultaneously, executing work dynamically across the GPU’s hardware resources. In essence, the whole GPU becomes multi-tasking capable, receiving different task submissions from up to 8 sources (hence 8 HyperLanes).

The new feature sounded to me like a hardware based scheduler for task submissions, although when I brought up this description the Imagination spokespeople were rather dismissive of the simplification, saying that HyperLanes go far deeper into the hardware architecture, with for example each HyperLane having being able to be configured with its own virtual memory space (or also sharing arbitrary memory spaces across hyperlanes).

Splitting GPU resources can happens on a block-level concurrently with other tasks, or also be shared in the time-domain with time-slices between HyperLanes. Priority can be given to HyperLanes, such as prioritizing graphics over a possible background AI task using the remaining free resources.

The security advantages of such a technology also seem advanced, with the company use-cases such as isolation for protected content and rights management.

An interesting new development feature that is enabled by profiling the GPU’s hardware counters through the firmware processor is creating tile heatmaps of execution resources used. This seems relatively banal, but isn’t something that’s readily available for software developers and could be extremely useful in terms of quick debugging and optimizations of 3D workloads thanks to a more visual approach.