Graphics processing units(GPUs)employ the single instruction multiple data(SIMD)hardware to run threads in parallel and allow each thread to maintain an arbitrary control flow.Threads running concurrently within a war...Graphics processing units(GPUs)employ the single instruction multiple data(SIMD)hardware to run threads in parallel and allow each thread to maintain an arbitrary control flow.Threads running concurrently within a warp may jump to different paths after conditional branches.Such divergent control flow makes some lanes idle and hence reduces the SIMD utilization of GPUs.To alleviate the waste of SIMD lanes,threads from multiple warps can be collected together to improve the SIMD lane utilization by compacting threads into idle lanes.However,this mechanism induces extra barrier synchronizations since warps have to be stalled to wait for other warps for compactions,resulting in that no warps are scheduled in some cases.In this paper,we propose an approach to reduce the overhead of barrier synchronizat ions induced by compactions,In our approach,a compaction is bypassed by warps whose threads all jump to the same path after branches.Moreover,warps waiting for a compaction can also bypass this compaction when no warps are ready for issuing.In addition,a compaction is canceled if idle lanes can not be reduced via this compaction.The experimental results demonstrate that our approach provides an average improvement of 21%over the baseline GPU for applications with massive divergent branches,while recovering the performance loss induced by compactions by 13%on average for applications with many non-divergent control flows.展开更多
首先借鉴Leighton M icali协议中的多重单向散列建立密钥思想,设计了一种基本的多重单向散列密钥分配协议。该协议能确保所有邻居节点能建立安全链路,但是安全性能差。然后结合多重单向散列与随机密钥预分配,提出了多重单向散列随机密...首先借鉴Leighton M icali协议中的多重单向散列建立密钥思想,设计了一种基本的多重单向散列密钥分配协议。该协议能确保所有邻居节点能建立安全链路,但是安全性能差。然后结合多重单向散列与随机密钥预分配,提出了多重单向散列随机密钥预分配协议,并详细分析了性能。与现有的协议相比,该协议只需很少的单向散列运算,计算负载小,安全性能高,非常适用于传感器网络。展开更多
基金the National Natural Science Foundation of China(No.61702521)the Natural Science Foundation of Tianjin(No.18JCQNJC00400)+1 种基金the Scientific Research Foundation of Civil Aviation University of China(No.2017QD12S)the Fundamental Research Funds for the Central Universities of Civil Aviation University of China(Nos.3122018C023 and 3122018C021)。
文摘Graphics processing units(GPUs)employ the single instruction multiple data(SIMD)hardware to run threads in parallel and allow each thread to maintain an arbitrary control flow.Threads running concurrently within a warp may jump to different paths after conditional branches.Such divergent control flow makes some lanes idle and hence reduces the SIMD utilization of GPUs.To alleviate the waste of SIMD lanes,threads from multiple warps can be collected together to improve the SIMD lane utilization by compacting threads into idle lanes.However,this mechanism induces extra barrier synchronizations since warps have to be stalled to wait for other warps for compactions,resulting in that no warps are scheduled in some cases.In this paper,we propose an approach to reduce the overhead of barrier synchronizat ions induced by compactions,In our approach,a compaction is bypassed by warps whose threads all jump to the same path after branches.Moreover,warps waiting for a compaction can also bypass this compaction when no warps are ready for issuing.In addition,a compaction is canceled if idle lanes can not be reduced via this compaction.The experimental results demonstrate that our approach provides an average improvement of 21%over the baseline GPU for applications with massive divergent branches,while recovering the performance loss induced by compactions by 13%on average for applications with many non-divergent control flows.
文摘首先借鉴Leighton M icali协议中的多重单向散列建立密钥思想,设计了一种基本的多重单向散列密钥分配协议。该协议能确保所有邻居节点能建立安全链路,但是安全性能差。然后结合多重单向散列与随机密钥预分配,提出了多重单向散列随机密钥预分配协议,并详细分析了性能。与现有的协议相比,该协议只需很少的单向散列运算,计算负载小,安全性能高,非常适用于传感器网络。
