CONTEXT-AWARE COMPRESSION WITH QUANTIZATION OF HIERARCHICAL TRANSFORM MATRICES

    公开(公告)号:US20210082154A1

    公开(公告)日:2021-03-18

    申请号:US17003040

    申请日:2020-08-26

    Abstract: Apparatus and method for context-aware compression. For example, one embodiment of an apparatus comprises: ray traversal/intersection circuitry to traverse rays through a hierarchical acceleration data structure to identify intersections between rays and primitives of a graphics scene; matrix compression circuitry/logic to compress hierarchical transformation matrices to generate compressed hierarchical transformation matrices by quantizing N-bit floating point data elements associated with child transforms of the hierarchical transformation matrices to variable-bit floating point numbers or integers comprising offsets from a parent transform of the child transform; and an instance processor to generate a plurality of instances of one or more base geometric objects in accordance with the compressed hierarchical transformation matrices.

    APPARATUS AND METHOD FOR A HIERARCHICAL BEAM TRACER

    公开(公告)号:US20210049808A1

    公开(公告)日:2021-02-18

    申请号:US17003011

    申请日:2020-08-26

    Abstract: Apparatus and method for a hierarchical beam tracer. For example, one embodiment of an apparatus comprises: a beam generator to generate beam data associated with a beam projected into a graphics scene; a bounding volume hierarchy (BVH) generator to generate BVH data comprising a plurality of hierarchically arranged BVH nodes; a hierarchical beam-based traversal unit to determine whether the beam intersects a current BVH node and, if so, to responsively subdivide the beam into N child beams to test against the current BVH node and/or to traverse further down the BVH hierarchy to select a new BVH node, wherein the hierarchical beam-based traversal unit is to iteratively subdivide successive intersecting child beams and/or to continue to traverse down the BVH hierarchy until a leaf node is reached with which at least one final child beam is determined to intersect; the hierarchical beam-based traversal unit to generate a plurality of rays within the final child beam; and intersection hardware logic to perform intersection testing for any rays intersecting the leaf node, the intersection testing to determine intersections between the rays intersecting the leaf node and primitives bounded by the leaf node.

    APPARATUS AND METHOD FOR A HIERARCHICAL BEAM TRACER

    公开(公告)号:US20240233244A1

    公开(公告)日:2024-07-11

    申请号:US18413286

    申请日:2024-01-16

    CPC classification number: G06T15/06 G06T1/60 G06T15/005 G06T17/005 G06T2210/21

    Abstract: Apparatus and method for a hierarchical beam tracer. For example, one embodiment of an apparatus comprises: a beam generator to generate beam data associated with a beam projected into a graphics scene; a bounding volume hierarchy (BVH) generator to generate BVH data comprising a plurality of hierarchically arranged BVH nodes; a hierarchical beam-based traversal unit to determine whether the beam intersects a current BVH node and, if so, to responsively subdivide the beam into N child beams to test against the current BVH node and/or to traverse further down the BVH hierarchy to select a new BVH node, wherein the hierarchical beam-based traversal unit is to iteratively subdivide successive intersecting child beams and/or to continue to traverse down the BVH hierarchy until a leaf node is reached with which at least one final child beam is determined to intersect; the hierarchical beam-based traversal unit to generate a plurality of rays within the final child beam; and intersection hardware logic to perform intersection testing for any rays intersecting the leaf node, the intersection testing to determine intersections between the rays intersecting the leaf node and primitives bounded by the leaf node.

    CACHE STREAMING APPARATUS AND METHOD FOR DEEP LEARNING OPERATIONS

    公开(公告)号:US20230297513A1

    公开(公告)日:2023-09-21

    申请号:US17699062

    申请日:2022-03-18

    CPC classification number: G06F12/0897 G06N20/00 G06F2212/60

    Abstract: A cache streaming apparatus and method for machine learning. For example, one embodiment of an apparatus comprises: a plurality of compute units to perform machine learning operations; a cache subsystem comprising a hierarchy of cache levels, at least some of the cache levels shared by two or more of the plurality of compute units; and data streaming hardware logic to stream machine learning data in and out of the cache subsystem based on the machine learning operations, the data streaming hardware logic to load data into the cache subsystem from memory before the data is needed by a first portion of the machine learning operations and to ensure that results produced by the first portion of machine learning operations are maintained in the cache subsystem until used by a second portion of the machine learning operations.

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