Abstract: A method is provided for generating a mipmap. A processor comprises a neural processing engine comprising a plurality of hardware units suitable for performing integer operations on machine learning models. The method comprises receiving initial image data and one or more commands to perform an operation for generating a further layer of image data from the initial image data that has a different resolution to the initial image data. The method processes the commands to generate the further layer using the neural processing engine of the processor.

Abstract: A method is provided for generating a mipmap. A processor comprises a neural processing engine comprising a plurality of hardware units suitable for performing integer operations on machine learning models. The method comprises receiving initial image data and one or more commands to perform an operation for generating a further layer of image data from the initial image data that has a different resolution to the initial image data. The method processes the commands to generate the further layer using the neural processing engine of the processor.

Abstract: The present disclosure relates to A data processing apparatus, comprising: graph partitioning circuitry configured to receive a computation graph, the computation graph comprising a plurality of nodes representing operators and a plurality of edges representing relationships amongst the plurality of operators, and to divide the computation graph into a plurality of partitions, each partition comprising one or more nodes and/or edges; graph compilation circuitry configured to compile a computation graph to generate one or more compilation outputs; and storage to store the one or more compilation outputs; wherein the graph compilation circuitry is configured to: compile a first partition of the plurality of partitions to generate a first compilation output; and output the first compilation output to a first target portion of the storage assigned to the first partition.

Abstract: A graphics processing system performs a final gather process so as to generate final gather lighting data for a scene. The final gather process comprises casting sampling rays from a final gather point within the scene. Radiosity data provided for the scene is sampled using the sampling rays cast from the final gather point. Final gather lighting data is then generated from the sampled radiosity data. The sampling rays are cast from the final gather point in an informed manner based on directional irradiance data provided for the scene. The final gather process can therefore be carried out by the graphics processing system more efficiently and effectively.

Abstract: A graphics processing system performs a final gather process so as to generate final gather lighting data for a scene. The final gather process comprises casting sampling rays from a final gather point within the scene. Radiosity data provided for the scene is sampled using the sampling rays cast from the final gather point. Final gather lighting data is then generated from the sampled radiosity data. The sampling rays are cast from the final gather point in an informed manner based on directional irradiance data provided for the scene. The final gather process can therefore be carried out by the graphics processing system more efficiently and effectively.