Abstract:
A graphics virtual texturing system in which textures stored in a storage medium of a host system are divided into respective pages that are then loaded into a local memory of a graphics processing system for use. Each page of a graphics texture has an associated fade factor value that can be set by an application that is to use the texture to control the contribution that the page will be used to make to any texturing result that is generated using the texture page in question. The graphics processing system then controls the contribution of texture data from a texture page to texturing result data to be generated in accordance with the fade factor value associated with the texture page in question. This allows texture paging to be done in a more visually pleasing manner than just a binary “page-is-here”/“page-is-not-here” switch.
Abstract:
A data processing apparatus processes a set of weight values for an artificial neural network by representing the set of weight values in the form of an array of weight values and by using an image compression scheme to provide compressed weight data for the artificial neural network. The data processing apparatus uses an image decompression scheme to derive decompressed weight values from the compressed weight data and applies the decompressed weight values when producing a result from an input to the artificial neural network. The data processing apparatus can provide for efficient storage and processing of the weight values for the artificial neural network.
Abstract:
A graphics virtual texturing system in which textures stored in a storage medium of a host system are divided into respective pages that are then loaded into a local memory of a graphics processing system for use. Each page of a graphics texture has an associated fade factor value that can be set by an application that is to use the texture to control the contribution that the page will be used to make to any texturing result that is generated using the texture page in question. The graphics processing system then controls the contribution of texture data from a texture page to texturing result data to be generated in accordance with the fade factor value associated with the texture page in question. This allows texture paging to be done in a more visually pleasing manner than just a binary “page-is-here”/“page-is-not-here” switch.
Abstract:
A data processing apparatus implements an artificial neural network to generate a result that indicates one or more encoding options to use when encoding a set of data elements using an encoding scheme. The data processing apparatus can provide an efficient way of selecting between possible encoding options that can be used to encode a set of data elements.
Abstract:
A data processing apparatus implements an artificial neural network to generate a result that indicates one or more encoding options to use when encoding a set of data elements using an encoding scheme. The data processing apparatus can provide an efficient way of selecting between possible encoding options that can be used to encode a set of data elements.
Abstract:
A graphics virtual texturing system in which textures stored in a storage medium of a host system are divided into respective pages that are then loaded into a local memory of a graphics processing system for use. If the texture page that is required for performing a texturing operation at an originally desired level of detail (52) is not present in the local memory of the graphics processing system (53), the virtual texture lookup process loops back to try to sample the texture at an increased level of detail (55), and so on, until texture data that can be used is found in the local memory of the graphics processing system (53). This allows the texturing operation to proceed using texture data for the texel positions in question from a higher level (less detailed) mipmap in place of the originally desired texture data.
Abstract:
A data processing apparatus processes a set of weight values for an artificial neural network by representing the set of weight values in the form of an array of weight values and by using an image compression scheme to provide compressed weight data for the artificial neural network. The data processing apparatus uses an image decompression scheme to derive decompressed weight values from the compressed weight data and applies the decompressed weight values when producing a result from an input to the artificial neural network. The data processing apparatus can provide for efficient storage and processing of the weight values for the artificial neural network.
Abstract:
A graphics virtual texturing system in which textures stored in a storage medium of a host system are divided into respective pages that are then loaded into a local memory of a graphics processing system for use. If the texture page that is required for performing a texturing operation at an originally desired level of detail (52) is not present in the local memory of the graphics processing system (53), the virtual texture lookup process loops back to try to sample the texture at an increased level of detail (55), and so on, until texture data that can be used is found in the local memory of the graphics processing system (53). This allows the texturing operation to proceed using texture data for the texel positions in question from a higher level (less detailed) mipmap in place of the originally desired texture data.