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Compressed textures are indispensable in most 3D graphics applications to reduce memory traffic and increase performance. For higher-quality graphics, the number and size of textures in an application have continuously increased. Additionally, the ETC2 texture format, which is mandatory in OpenGL ES 3.0, OpenGL 4.3, and Android 4.3 (and later versions), requires more complex texture compression than the traditional ETC1 format. As a result, texture compression becomes more and more time-consuming. To accelerate ETC2 compression, we introduce two new compression techniques, named QuickETC2. The first technique is an early compression-mode decision scheme. Instead of testing all ETC1/2 modes to compress a texel block, we select proper modes for each block by exploiting the luma difference of the block to reduce unnecessary compression overhead. The second technique is a fast luma-based T- and H-mode compression method. When clustering each texel into two groups, we replace the 3D RGB space with the 1D luma space and quickly find the two groups that have the minimum luma differences. We also selectively perform the T- or H-mode and reduce its distance candidates, according to the luma differences of each group. We have implemented both techniques with AVX2 intrinsics to exploit SIMD parallelism. According to our experiments, QuickETC2 can compress more than 2000 1K×1K-sized images per second on an octa-core CPU. [ABSTRACT FROM AUTHOR]

We propose a method for moving the view position to the origin and moving the coordinates of primitives so that they are at the same distance in order to improve ray-tracing precision. This approach exploits the principle that a floating-point number provides higher precision near zero. In this way, we can significantly reduce the number of self-intersections occurring in ray tracing that are caused by limited floating-point precision. The experimental results show that the number of self-intersections is reduced by up to 84.6 %. We also propose a hardware approach to resolve the computational overhead in the proposed algorithm. Its contribution to the hardware size is very small in comparison with the size of the entire ray-tracing hardware. [ABSTRACT FROM AUTHOR]

We present a hybrid architecture, inspired by asynchronous BVH construction [1] , for ray tracing animated scenes. Our hybrid architecture utilizes heterogeneous hardware resources: dedicated ray-tracing hardware for BVH updates and ray traversal and a CPU for BVH reconstruction. We also present a traversal scheme using a primitive’s axis-aligned bounding box (PrimAABB). This scheme reduces ray-primitive intersection tests by reusing existing BVH traversal units and the primAABB data for tree updates; it enables the use of shallow trees to reduce tree build times, tree sizes, and bus bandwidth requirements. Furthermore, we present a cache scheme that exploits consecutive memory access by reusing data in an L1 cache block. We perform cycle-accurate simulations to verify our architecture, and the simulation results indicate that the proposed architecture can achieve real-time Whitted ray tracing animated scenes at 1,920\;\times\;1,200 resolution. This result comes from our high-performance hardware architecture and minimized resource requirements for tree updates. [ABSTRACT FROM PUBLISHER]

We present RayCore, a mobile ray-tracing hardware architecture. RayCore facilitates high-quality rendering effects, such as reflection, refraction, and shadows, on mobile devices by performing real-time Whitted ray tracing. RayCore consists of two major components: ray-tracing units (RTUs) based on a unified traversal and intersection pipeline and a tree-building unit (TBU) for dynamic scenes. The overall RayCore architecture offers considerable benefits in terms of die area, memory access, and power consumption. We have evaluated our architecture based on FPGA and ASIC evaluations and demonstrate its performance on different benchmarks. According to the results, our architecture demonstrates high performance per unit area and unit energy, making it highly suitable for use in mobile devices. [ABSTRACT FROM AUTHOR]