Know how your GPU handles the workloads of 2030, before tape-out.

1. 1

   Pre-silicon workload modelling

   Know how your GPU handles the workloads of 2030 before tape-out. Future rendering and neural workloads, run on simulators and emulators years before the part exists.

   GPU pre-silicon validationBenchmarking and GPU workload researchNeural renderingPre-silicon ray tracing with Imagination

2. 2

   Bring-up and validation

   First silicon against the same workloads, so a number that moves can be attributed to the architecture rather than the scene.

   GPU inference and trainingCharacterising mobile ray tracing before the hardware existsEvolve and neural workloads on mobile silicon

3. 3

   SDK and driver work

   The library and samples a developer meets, built by a team that has been on the integrating end of many of them.

   SDK development for hardware vendorsAcceleration structuresNeural reconstruction and upscaling

4. 4

   Launch demos and publications

   A showcase that runs on retail devices on launch day, and the paper that explains what it does.

   Neural upscaling and frame generation at Snapdragon Summit 2026Ray tracing on Galaxy S24Neural radiance cachingNeural graphics with Arm

5. 5

   Ecosystem and game optimisation

   Games tuned for the silicon once it ships. This is where Traverse Games picks up the same work.

   Game performance optimisationMobile game optimisationEngineering with Embark Studios

Evolve at every stage. The workloads we model before tape-out are the ones the benchmark ships, so the same measurement follows the part from simulator to store shelf. How Evolve stays neutral