Abstract: Embodiments are generally directed to compression for compression for sparse data structures utilizing mode search approximation. An embodiment of an apparatus includes one or more processors including a graphics processor to process data; and a memory for storage of data, including compressed data. The one or more processors are to provide for compression of a data structure, including identification of a mode in the data structure, the data structure including a plurality of values and the mode being a most repeated value in a data structure, wherein identification of the mode includes application of a mode approximation operation, and encoding of an output vector to include the identified mode, a significance map to indicate locations at which the mode is present in the data structure, and remaining uncompressed data from the data structure.

Abstract: Embodiments are generally directed to compression for compression for sparse data structures utilizing mode search approximation. An embodiment of an apparatus includes one or more processors including a graphics processor to process data; and a memory for storage of data, including compressed data. The one or more processors are to provide for compression of a data structure, including identification of a mode in the data structure, the data structure including a plurality of values and the mode being a most repeated value in a data structure, wherein identification of the mode includes application of a mode approximation operation, and encoding of an output vector to include the identified mode, a significance map to indicate locations at which the mode is present in the data structure, and remaining uncompressed data from the data structure.

Abstract: Generation and storage of compressed z-planes in graphics processing is described. An example of a processor includes a rasterizer to generate a fragment of pixel data including blocks of pixel data; a depth pipeline to receive the fragment, the pipeline including a first and second depth test hardware, the first depth test hardware to perform a coarse depth test including determining minimum and maximum depths for each block; and a depth buffer, wherein the processor is to determine whether the fragment meets requirements that the fragment fully covers a tile of pixel data and passes a first depth test, and that each of the minimum and maximum depths of the fragment has a same sign and exponent, and, upon determining that the fragment meets the requirements, to generate a compressed depth plane utilizing the first depth test and update the depth buffer with the compressed depth plane.

Abstract: Generation and storage of compressed z-planes in graphics processing is described. An example of a processor includes a rasterizer to generate a fragment of pixel data including blocks of pixel data; a depth pipeline to receive the fragment, the pipeline including a first and second depth test hardware, the first depth test hardware to perform a coarse depth test including determining minimum and maximum depths for each block; and a depth buffer, wherein the processor is to determine whether the fragment meets requirements that the fragment fully covers a tile of pixel data and passes a first depth test, and that each of the minimum and maximum depths of the fragment has a same sign and exponent, and, upon determining that the fragment meets the requirements, to generate a compressed depth plane utilizing the first depth test and update the depth buffer with the compressed depth plane.

Abstract: Apparatus and method for grouping rays based on quantized ray directions. For example, one embodiment of an apparatus comprises: An apparatus comprising: a ray generator to generate a plurality of rays; ray direction evaluation circuitry/logic to generate approximate ray direction data for each of the plurality of rays; ray sorting circuitry/logic to sort the rays into a plurality of ray queues based, at least in part, on the approximate ray direction data.

Abstract: Embodiments are generally directed to compression for compression for sparse data structures utilizing mode search approximation. An embodiment of an apparatus includes one or more processors including a graphics processor to process data; and a memory for storage of data, including compressed data. The one or more processors are to provide for compression of a data structure, including identification of a mode in the data structure, the data structure including a plurality of values and the mode being a most repeated value in a data structure, wherein identification of the mode includes application of a mode approximation operation, and encoding of an output vector to include the identified mode, a significance map to indicate locations at which the mode is present in the data structure, and remaining uncompressed data from the data structure.

Abstract: An apparatus to facilitate compression of memory data is disclosed. The apparatus comprises one or more processors to receive uncompressed data, adapt a format of the uncompressed data to a compression format, perform a color transformation from a first color space to a second color space, perform a residual computation to generate residual data, compress the residual data via entropy encoding to generate compressed data and packing the compressed data.

Abstract: Embodiments are generally directed to compression for compression for sparse data structures utilizing mode search approximation. An embodiment of an apparatus includes one or more processors including a graphics processor to process data; and a memory for storage of data, including compressed data. The one or more processors are to provide for compression of a data structure, including identification of a mode in the data structure, the data structure including a plurality of values and the mode being a most repeated value in a data structure, wherein identification of the mode includes application of a mode approximation operation, and encoding of an output vector to include the identified mode, a significance map to indicate locations at which the mode is present in the data structure, and remaining uncompressed data from the data structure.

Abstract: An apparatus to facilitate compression of memory data is disclosed. The apparatus comprises one or more processors to receive uncompressed data, adapt a format of the uncompressed data to a compression format, perform a color transformation from a first color space to a second color space, perform a residual computation to generate residual data, compress the residual data via entropy encoding to generate compressed data and packing the compressed data.

Abstract: Apparatus and method for grouping rays based on quantized ray directions. For example, one embodiment of an apparatus comprises: An apparatus comprising: a ray generator to generate a plurality of rays; ray direction evaluation circuitry/logic to generate approximate ray direction data for each of the plurality of rays; ray sorting circuitry/logic to sort the rays into a plurality of ray queues based, at least in part, on the approximate ray direction data.

Abstract: Apparatus and method for grouping rays based on quantized ray directions. For example, one embodiment of an apparatus comprises: An apparatus comprising: a ray generator to generate a plurality of rays; ray direction evaluation circuitry/logic to generate approximate ray direction data for each of the plurality of rays; ray sorting circuitry/logic to sort the rays into a plurality of ray queues based, at least in part, on the approximate ray direction data.

Abstract: Embodiments are generally directed to compression for compression for sparse data structures utilizing mode search approximation. An embodiment of an apparatus includes one or more processors including a graphics processor to process data; and a memory for storage of data, including compressed data. The one or more processors are to provide for compression of a data structure, including identification of a mode in the data structure, the data structure including a plurality of values and the mode being a most repeated value in a data structure, wherein identification of the mode includes application of a mode approximation operation, and encoding of an output vector to include the identified mode, a significance map to indicate locations at which the mode is present in the data structure, and remaining uncompressed data from the data structure.

Abstract: Embodiments are generally directed to compression for compression for sparse data structures utilizing mode search approximation. An embodiment of an apparatus includes one or more processors including a graphics processor to process data; and a memory for storage of data, including compressed data. The one or more processors are to provide for compression of a data structure, including identification of a mode in the data structure, the data structure including a plurality of values and the mode being a most repeated value in a data structure, wherein identification of the mode includes application of a mode approximation operation, and encoding of an output vector to include the identified mode, a significance map to indicate locations at which the mode is present in the data structure, and remaining uncompressed data from the data structure.

Abstract: Generation and storage of compressed z-planes in graphics processing is described. An example of a processor includes a rasterizer to generate a fragment of pixel data including blocks of pixel data; a depth pipeline to receive the fragment, the pipeline including a first and second depth test hardware, the first depth test hardware to perform a coarse depth test including determining minimum and maximum depths for each block; and a depth buffer, wherein the processor is to determine whether the fragment meets requirements that the fragment fully covers a tile of pixel data and passes a first depth test, and that each of the minimum and maximum depths of the fragment has a same sign and exponent, and, upon determining that the fragment meets the requirements, to generate a compressed depth plane utilizing the first depth test and update the depth buffer with the compressed depth plane.

Abstract: Apparatus and method for grouping rays based on quantized ray directions. For example, one embodiment of an apparatus comprises: An apparatus comprising: a ray generator to generate a plurality of rays; ray direction evaluation circuitry/logic to generate approximate ray direction data for each of the plurality of rays; ray sorting circuitry/logic to sort the rays into a plurality of ray queues based, at least in part, on the approximate ray direction data.

Abstract: An apparatus to facilitate compression of memory data is disclosed. The apparatus comprises one or more processors to receive uncompressed data, adapt a format of the uncompressed data to a compression format, perform a color transformation from a first color space to a second color space, perform a residual computation to generate residual data, compress the residual data via entropy encoding to generate compressed data and packing the compressed data.

Abstract: Apparatus and method for grouping rays based on quantized ray directions. For example, one embodiment of an apparatus comprises: An apparatus comprising: a ray generator to generate a plurality of rays; ray direction evaluation circuitry/logic to generate approximate ray direction data for each of the plurality of rays; ray sorting circuitry/logic to sort the rays into a plurality of ray queues based, at least in part, on the approximate ray direction data.

Abstract: Apparatus and method for grouping rays based on quantized ray directions. For example, one embodiment of an apparatus comprises: An apparatus comprising: a ray generator to generate a plurality of rays; ray direction evaluation circuitry/logic to generate approximate ray direction data for each of the plurality of rays; ray sorting circuitry/logic to sort the rays into a plurality of ray queues based, at least in part, on the approximate ray direction data.

Abstract: An apparatus to facilitate packing compressed data is disclosed. The apparatus includes compression hardware to compress memory data into a plurality of compressed data components and packing hardware to receive the plurality of compressed data components and pack a first of the plurality of compressed data components beginning at a least significant bit (LSB) location of a compressed bit stream and pack a second of the plurality of compressed data components beginning at a most significant bit (MSB) of the compressed bit stream.

Abstract: Apparatus and method including cell primitive for unstructured volume rendering. For example, one embodiment of an apparatus comprises: a ray generator to generate a plurality of rays in a first graphics scene; a hierarchical acceleration data structure generator to construct a hierarchical acceleration data structure comprising a plurality of hierarchically arranged nodes including leaf nodes and inner nodes; traversal circuitry to traverse one or more of the rays through the hierarchical acceleration data structure; unstructured volume intersection circuitry to intersect a ray with an unstructured volume primitive within a leaf node of the hierarchical acceleration data structure, the unstructured volume intersection circuitry to determine multiple intersection hits between a ray and an unstructured volume primitive.