Coherency gathering in ray tracing: the benefits of hardware ray tracking
Despite the theoretically infinite ways to implement a modern GPU, the truly efficient ways to make one come to life in silicon tend to force the hands of those making them for real. The reality of manufacturing modern high-performance semiconductors, and the problem at hand when trying to accelerate the current view of programmable rasterisation, have uncovered trends in implementation across the GPU hardware industry.
For example, SIMD processing and fixed-function texture hardware are a cast-iron necessity in a modern GPU, to the point where not implementing a GPU with them would almost certainly mean it wasn’t commercially viable or useful outside of research. Even the wildest vision of any GPU in the last two decades didn’t abandon those core tenets. (Rest in peace, Larrabee).
Real-time ray tracing acceleration is the biggest upset to the unwritten rules of the GPU in the last 15 years. The dominant specification for how ray tracing should work on a GPU, Microsoft’s DXR, demands an execution model that doesn’t really blend in with the way GPUs like to work, giving any GPU designer that needs to support it some serious potential headaches. That’s especially true if real-time ray tracing is something they haven’t been thinking about for the last decade or so and here at Imagination, we have been.
To read the full article, click here
Related Semiconductor IP
- Arm's most performance and efficient GPU till date, offering unparalled mobile gaming and ML performance
- Highest performance automotive GPU IP, with revolutionary functional safety technology
- 3D OpenGL ES GPU (Graphics Processing Unit)
- High performance GPU for cloud gaming with DirectX support
- Arm’s latest flagship GPU is based on the new 5th Gen GPU architecture, bringing the next generation of visual computing to mobile
Related Blogs
- Software is from Mars, hardware is from Pluto
- Tracking the Big Semiconductor Story of 2012
- Differentiation Through Hardware is Not Going Away
- Opinion: Why IDEs for hardware design fail
Latest Blogs
- The Growing Importance of PVT Monitoring for Silicon Lifecycle Management
- Unlock early software development for custom RISC-V designs with faster simulation
- HBM4 Boosts Memory Performance for AI Training
- Using AI to Accelerate Chip Design: Dynamic, Adaptive Flows
- Locking When Emulating Xtensa LX Multi-Core on a Xilinx FPGA