Algorithms and Architectures for Parallel Processing

Graph embeddings are not only used to study the simulation capabilities of a parallel architecture but also to design its VLSI layout. The n-dimensional hypercube is one of the most popular topological structure for interconnection networks in parallel computing and communication systems. The exchanged hypercube EHs,t (where s ≥ 1 and t ≥ 1) is obtained by systematically deleting edges from a hypercube Qs+t+1, which retains several valuable and desirable properties of the hypercube such as a small diameter, bipancyclicity, and super connectivity. In this paper, we identify maximum induced subgraph of EHs,t and study embeddings of EHs,t into a ring and a ladder with minimum wirelength.

[1]  Luis Gravano,et al.  k-Shape: Efficient and Accurate Clustering of Time Series , 2015, SIGMOD Conference.

[2]  Justin J. Miller,et al.  Graph Database Applications and Concepts with Neo4j , 2013 .

[3]  Dhabaleswar K. Panda,et al.  Triple-H: A Hybrid Approach to Accelerate HDFS on HPC Clusters with Heterogeneous Storage Architecture , 2015, 2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing.

[4]  Jian Zhi.  Research on Data Preprocess in Data Mining and Its Application , 2004 .

[5]  Chunkai Zhang,et al.  Design and Application of Electrocardiograph Diagnosis System Based on Multifractal Theory , 2017 .

[6]  Shamkant B. Navathe,et al.  Graph Database Design Challenges Using HPC Platforms , 2012, 2012 SC Companion: High Performance Computing, Networking Storage and Analysis.

[7]  Kristina Chodorow,et al.  MongoDB - The Definitive Guide: Powerful and Scalable Data Storage , 2019 .

[8]  Tomoo Ushio,et al.  “Big Data Assimilation” Revolutionizing Severe Weather Prediction , 2016 .

[9]  Jinjun Chen,et al.  CPU load prediction for cloud environment based on a dynamic ensemble model , 2014, Softw. Pract. Exp..

[10]  Hongsheng Xi,et al.  A Novel Approach to Network Security Situation Awareness Based on Multi-Perspective Analysis , 2007, 2007 International Conference on Computational Intelligence and Security (CIS 2007).

[11]  Dhabaleswar K. Panda,et al.  Accelerating I/O Performance of Big Data Analytics on HPC Clusters through RDMA-Based Key-Value Store , 2015, 2015 44th International Conference on Parallel Processing.

[12]  Christof Fetzer,et al.  Sieve: actionable insights from monitored metrics in distributed systems , 2017, Middleware.

[13]  Yu Zhang,et al.  Highway long short-term memory RNNS for distant speech recognition , 2015, 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[14]  Fan Ming-hui.  Review of Outlier Detection , 2006 .

[15]  Koji Terasaki,et al.  Big Ensemble Data Assimilation in Numerical Weather Prediction , 2015, Computer.

[16]  Noah A. Smith,et al.  Improved Transition-based Parsing by Modeling Characters instead of Words with LSTMs , 2015, EMNLP.

[17]  Qin Yu,et al.  An Improved ARIMA-Based Traffic Anomaly Detection Algorithm for Wireless Sensor Networks , 2016, Int. J. Distributed Sens. Networks.

[18]  Wei Ge,et al.  The Sunway TaihuLight supercomputer: system and applications , 2016, Science China Information Sciences.

[19]  Chen Wenguang.  Big Data and High Performance Computing , 2015 .

[20]  Elizabeth Chang,et al.  Profile-Based Viable Service Level Agreement (SLA) Violation Prediction Model in the Cloud , 2015, 2015 10th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC).