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Cache Hit Ratio Maximization in Device-to-Device Communications Overlaying Cellular Networks
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作者 Liang Zhong Xueqian Zheng +2 位作者 Yong Liu Mengting Wang Yang Cao 《China Communications》 SCIE CSCD 2020年第2期232-238,共7页
This paper investigates the content placement problem to maximize the cache hit ratio in device-to-device(D2D)communications overlaying cellular networks.We consider offloading contents by users themselves,D2D communi... This paper investigates the content placement problem to maximize the cache hit ratio in device-to-device(D2D)communications overlaying cellular networks.We consider offloading contents by users themselves,D2D communications and multicast,and we analyze the relationship between these offloading methods and the cache hit ratio.Based on this relationship,we formulate the content placement optimization as a cache hit ratio maximization problem,and propose a heuristic algorithm to solve it.Numerical results demonstrate that the proposed scheme can outperform existing schemes in terms of the cache hit ratio. 展开更多
关键词 cache hit ratio content placement device-to-device MULTICAST
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A cache-friendly sampling strategy for texture-based volume rendering on GPU 被引量:1
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作者 Junpeng Wang Fei Yang Yong Cao 《Visual Informatics》 EI 2017年第2期92-105,共14页
The texture-based volume rendering is a memory-intensive algorithm.Its performance relies heavily on the performance of the texture cache.However,most existing texture-based volume rendering methods blindly map comput... The texture-based volume rendering is a memory-intensive algorithm.Its performance relies heavily on the performance of the texture cache.However,most existing texture-based volume rendering methods blindly map computational resources to texture memory and result in incoherent memory access patterns,causing low cache hit rates in certain cases.The distance between samples taken by threads of an atomic scheduling unit(e.g.a warp of 32 threads in CUDA)of the GPU is a crucial factor that affects the texture cache performance.Based on this fact,we present a new sampling strategy,called Warp Marching,for the ray-casting algorithm of texture-based volume rendering.The effects of different sample organizations and different thread-pixel mappings in the ray-casting algorithm are thoroughly analyzed.Also,a pipeline manner color blending approach is introduced and the power of warp-level GPU operations is leveraged to improve the efficiency of parallel executions on the GPU.In addition,the rendering performance of the Warp Marching is view-independent,and it outperforms existing empty space skipping techniques in scenarios that need to render large dynamic volumes in a low resolution image.Through a series of micro-benchmarking and real-life data experiments,we rigorously analyze our sampling strategies and demonstrate significant performance enhancements over existing sampling methods. 展开更多
关键词 Warp marching Texture cache hit rate GPU Volume rendering
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