Scalar Engine Cluster for Ray Traversal Acceleration
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Solution Overview
Problem
Existing ray tracing technologies face challenges in achieving real-time performance due to the resource-intensive nature of ray traversal operations, particularly in processing visibility queries for ray-scene intersections within bounding volume hierarchies (BVH).
Innovation Solution
The proposed solution involves a graphics processor architecture that incorporates a scalable execution unit array with multiple execution units, each capable of executing multiple hardware threads in parallel. This architecture includes a thread dispatcher and execution units that support SIMD instructions, enabling efficient processing of ray traversal operations through parallel execution and optimized memory access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If traditional ray traversal operations are used to process visibility queries for ray-scene intersections, then accuracy of intersection detection is maintained, but processing speed and real-time performance deteriorate due to resource-intensive operations
Solution Approach 1:
The invention segments the BVH traversal task by creating multiple independent scalar engines (first scalar engine, second scalar engine, etc.) that can simultaneously process different rays or different portions of the BVH structure. Each scalar engine functions as an independent processing unit, enabling parallel execution of ray traversal operations without interfering with each other, thus increasing overall processing speed while maintaining accurate intersection detection
Solution Approach 2:
The invention transitions from sequential single-threaded ray traversal to multi-dimensional parallel processing by organizing scalar engines in a clustered architecture that exploits both thread-level parallelism (multiple threads per engine) and data-level parallelism (multiple engines processing multiple rays simultaneously). This dimensional expansion of processing capability enables real-time performance by processing vast numbers of rays in parallel
2Productivity
If scalar processing elements are used to process multiple threads in parallel, then thread-level parallelism is exploited, but instruction-level parallelism and datapath utilization are insufficient
Solution Approach 1:
The invention merges multiple scalar processing elements into a unified scalar engine cluster architecture where shared resources (such as memory interfaces, control logic, and BVH data structures) are common to all scalar engines. This consolidation reduces overall device complexity compared to having fully independent processing units, while still maintaining high thread-level parallelism through the clustered organization of scalar engines that can be dynamically configured
Data Source
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AI summary
Cluster of acceleration engines to accelerate intersections. For example, one embodiment of an apparatus comprises: a set of graphics cores to execute a first set of instructions of a primary graphics thread; a scalar cluster comprising a plurality of scalar execution engines; and a communication fabric interconnecting the set of graphics cores and the scalar cluster; the set of graphics cores to offload execution of a second set of instructions associated with ray traversal and/or intersection operations to the scalar cluster; the scalar cluster comprising a plurality of local memories, each local memory associated with one of the scalar execution engines, wherein each local memory is to store a portion of a hierarchical acceleration data structure required by an associated scalar execution engine to execute one or more of the second set of instructions; the plurality of scalar execution engines to store results of the execution of the second set of instructions in a memory accessible by the set of graphics cores; wherein the set of graphics cores are to process the results within the primary graphics thread.