Kopta, DanielShkurko, KonstantinSpjut, JosefBrunvand, ErikDavis, AlKayvon Fatahalian and Christian Theobalt2016-02-182016-02-182013978-1-4503-2135-82079-8687https://doi.org/10.1145/2492045.2492058We propose two hardware mechanisms to decrease energy consumption on massively parallel graphics processors for ray tracing while keeping performance high. First, we use a streaming data model and configure part of the L2 cache into a ray stream memory to enable efficient data processing through ray reordering. This increases the L1 hit rate and reduces off-chip memory accesses substantially. Second, we employ reconfigurable specialpurpose pipelines than are constructed dynamically under program control. These pipelines use shared execution units (XUs) that can be configured to support the common compute kernels that are the foundation of the ray tracing algorithm, such as acceleration structure traversal and triangle intersection. This reduces the overhead incurred by memory and register accesses. These two synergistic features yield a ray tracing architecture that significantly reduces both power consumption and off-chip memory traffic when compared to a more traditional cache only approach.CR CategoriesI.3.1 [Computer Graphics]Hardware ArchitectureParallel ProcessingI.3.7 [Computer Graphics]Three Dimensional Graphics and RealismRaytracingKeywordsray tracingstreamingpersistent pipelinesbandwidth reductionenergy reduction10.1145/2492045.2492058121-128