Titlebook: Network and Parallel Computing; 15th IFIP WG 10.3 In Feng Zhang,Jidong Zhai,Mateo Valero Conference proceedings 2018 IFIP International Fed

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GRAM: A GPU-Based Property Graph Traversal and Query for HPC Rich Metadata Management,ent variables, and the parameters of all executions, etc. Recent studies have shown the feasibility of using property graph to model rich metadata and utilizing graph traversal to query rich metadata stored in the property graph. We propose to utilize GPU to process the rich metadata graphs. There a

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HPC-SFI: System-Level Fault Injection for High Performance Computing Systems,arious kinds of techniques have been proposed, such as hardware-level fault-tolerance, checkpointing, replication, algorithm-base fault-tolerance, etc. There are also many software systems to monitor and handle system-failures, e.g. management and job-scheduling system of HPC systems. To evaluate th

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Data Fine-Pruning: A Simple Way to Accelerate Neural Network Training, loss trend of the training data during the training process. We find that given a fixed set of hyper-parameters, pruning specific types of training data can reduce the time consumption of the training process while maintaining the accuracy of the neural network. We developed a data fine-pruning app

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Balancing the QOS and Security in Dijkstra Algorithm by SDN Technology,eatures of the network routing area using software defined networks (SDN). The SDN framework enables an efficient decoupled implementation of dynamic routing protocols which could aware the communication network status. In this work we consider the varying delay status of the communication network a

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Labeled Network Stack: A Co-designed Stack for Low Tail-Latency and High Concurrency in Datacenter pays more attention to throughput and average performance, considering little on tail latency and priority. We address this question by proposing a hardware-software co-designed Labeled Network Stack (LNS) for future datacenters. The key innovation is a payload labeling mechanism that distinguishes

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