2012 IEEE International Conference on Cluster Computing最新文献

On Optimal and Balanced Sparse Matrix Partitioning Problems 关于最优平衡稀疏矩阵划分问题

2012 IEEE International Conference on Cluster Computing Pub Date : 2012-09-24 DOI: 10.1109/CLUSTER.2012.77

Anaël Grandjean, J. Langguth, B. Uçar

{"title":"On Optimal and Balanced Sparse Matrix Partitioning Problems","authors":"Anaël Grandjean, J. Langguth, B. Uçar","doi":"10.1109/CLUSTER.2012.77","DOIUrl":"https://doi.org/10.1109/CLUSTER.2012.77","url":null,"abstract":"We investigate one dimensional partitioning of sparse matrices under a given ordering of the rows/columns. The partitioning constraint is to have load balance across processors when different parts are assigned to different processors. The load is defined as the number of rows, or columns, or the nonzeros assigned to a processor. The partitioning objective is to optimize different functions, including the well-known total communication volume arising in a distributed memory implementation of parallel sparse matrix-vector multiplication operations. The difference between our problem in this work and the general sparse matrix partitioning problem is that the parts should correspond to disjoint intervals of the given order. Whereas the partitioning problem without the interval constraint corresponds to the NP-complete hyper graph partitioning problem, the restricted problem corresponds to a polynomial-time solvable variant of the hyper graph partitioning problem. We adapt an existing dynamic programming algorithm designed for graphs to solve two related partitioning problems in graphs. We then propose graph models for a given hyper graph and a partitioning objective function so that the standard cut size definition in the graph model exactly corresponds to the hyper graph partitioning objective function. In extensive experiments, we show that our proposed algorithm is helpful in practice. It even demonstrates performance superior to the standard hyper graph partitioners when the number of parts is high.","PeriodicalId":143579,"journal":{"name":"2012 IEEE International Conference on Cluster Computing","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114661377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Hierarchical Clustering Strategies for Fault Tolerance in Large Scale HPC Systems 大规模高性能计算系统容错的分层聚类策略

2012 IEEE International Conference on Cluster Computing Pub Date : 2012-09-24 DOI: 10.1109/CLUSTER.2012.71

L. Bautista-Gomez, Thomas Ropars, N. Maruyama, F. Cappello, S. Matsuoka

{"title":"Hierarchical Clustering Strategies for Fault Tolerance in Large Scale HPC Systems","authors":"L. Bautista-Gomez, Thomas Ropars, N. Maruyama, F. Cappello, S. Matsuoka","doi":"10.1109/CLUSTER.2012.71","DOIUrl":"https://doi.org/10.1109/CLUSTER.2012.71","url":null,"abstract":"Future high performance computing systems will need to use novel techniques to allow scientific applications to progress despite frequent failures. Checkpoint-Restart is currently the most popular way to mitigate the impact of failures during long-running executions. Different techniques try to reduce the cost of Checkpoint-Restart, some of them such as local check pointing and erasure codes aim to reduce the time to checkpoint while others such as uncoordinated checkpoint and message-logging aim to decrease the cost of recovery. In this paper, we study how to combine all these techniques together in order to optimize both: check pointing and recovery. We present several clustering and topology challenges that lead us to an optimization problem in a four-dimensional space: reliability level, recovery cost, encoding time and message logging overhead. We propose a novel clustering method inspired from brain topology studies in neuroscience and evaluate it with a Tsunami simulation application in TSUBAME2. Our evaluation with 1024 processes shows that our novel clustering method can guarantee good performance for all of the four mentioned dimensions of our optimization problem.","PeriodicalId":143579,"journal":{"name":"2012 IEEE International Conference on Cluster Computing","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122161287","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

Memory Affinity: Balancing Performance, Power, Thermal and Fairness for Multi-core Systems 内存亲和性:多核系统的平衡性能、功耗、热和公平性

2012 IEEE International Conference on Cluster Computing Pub Date : 2012-09-24 DOI: 10.1109/CLUSTER.2012.33

Gangyong Jia, Xi Li, Chao Wang, Xuehai Zhou, Zongwei Zhu

引用次数: 12

Dynamic Network Forecasting Using SimGrid Simulations 使用SimGrid模拟的动态网络预测

2012 IEEE International Conference on Cluster Computing Pub Date : 2012-09-24 DOI: 10.1109/CLUSTER.2012.40

Matthieu Imbert, E. Caron

引用次数: 0

Replication Based QoS Framework for Flash Arrays 基于复制的Flash阵列QoS框架

2012 IEEE International Conference on Cluster Computing Pub Date : 2012-09-24 DOI: 10.1109/CLUSTER.2012.53

Nihat Altiparmak, A. Tosun

引用次数: 2

Synergy: A Middleware for Energy Conservation in Mobile Devices 协同:移动设备节能中间件

2012 IEEE International Conference on Cluster Computing Pub Date : 2012-09-24 DOI: 10.1109/CLUSTER.2012.64

Harshit Kharbanda, Manoj Krishnan, R. Campbell

{"title":"Synergy: A Middleware for Energy Conservation in Mobile Devices","authors":"Harshit Kharbanda, Manoj Krishnan, R. Campbell","doi":"10.1109/CLUSTER.2012.64","DOIUrl":"https://doi.org/10.1109/CLUSTER.2012.64","url":null,"abstract":"The combined effect of Moore's law and the failure of Den nard scaling have led to multi-core mobile devices with immense computation capabilities. The biggest limitation of the computation capability for any mobile device is its battery. Mobile cloud computing is used to offload compute intensive tasks that affect a mobile device's battery. Mobile ad-hoc computing can be used as an alternative to mobile cloud computing in cases where cloud access is not available or is inhibitive to application performance, although battery drain remains a critical argument against mobile ad-hoc computing. In this paper, we present Synergy, a middleware that increases the battery life for a system of mobile devices connected in a peer-to-peer ad-hoc network. Synergy conserves energy by scaling core frequencies and by intelligently distributing the computation among peer devices. The middleware is not restricted to mobile phones and in no way restricts the mobility of the devices. Synergy considers the mobile devices connected in a peer-to-peer fashion as a single multicore device with Wifi as the interconnect. With Synergy running on Google Nexus phones we were able to conserve up to 30.6% of the system battery while incurring a latency penalty of less than 5%.","PeriodicalId":143579,"journal":{"name":"2012 IEEE International Conference on Cluster Computing","volume":"128 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132425901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

Towards a Cost-Aware Data Migration Approach for Key-Value Stores 基于成本意识的键值存储数据迁移方法

2012 IEEE International Conference on Cluster Computing Pub Date : 2012-09-24 DOI: 10.1109/CLUSTER.2012.14

Xiulei Qin, Wen-bo Zhang, Wei Wang, Jun Wei, Xin Zhao, Tao Huang

{"title":"Towards a Cost-Aware Data Migration Approach for Key-Value Stores","authors":"Xiulei Qin, Wen-bo Zhang, Wei Wang, Jun Wei, Xin Zhao, Tao Huang","doi":"10.1109/CLUSTER.2012.14","DOIUrl":"https://doi.org/10.1109/CLUSTER.2012.14","url":null,"abstract":"Live data migration is an important technique for key-value stores. However, due to the stateful feature, new virtualization technology, stringent low latency requirements and unexpected workload changes, key-value stores deployed in cloud environment have to face new challenges for data migration: effects of VM interference, and the need to trade off between the two ingredients of migration cost, say migration time and performance impact. To address these challenges, we focus on the data migration problem in a load rebalancing scenario and build a new framework that aims to rebalance load while minimizing migration costs. We build two interference-aware prediction models to predict the migration time and performance impact for each action using statistical machine learning and then create a cost model to strike a right balance between the two ingredients of cost. A cost-aware migration algorithm is designed to utilize the cost model and balance rate to guide the choice of possible migration actions. We demonstrate the effectiveness of the data migration approach as well as the cost model and two prediction models using YCSB.","PeriodicalId":143579,"journal":{"name":"2012 IEEE International Conference on Cluster Computing","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133946686","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

Built-in Device Simulator for OS Performance Evaluation 用于操作系统性能评估的内置设备模拟器

2012 IEEE International Conference on Cluster Computing Pub Date : 2012-09-24 DOI: 10.1109/CLUSTER.2012.30

Junjie Mao, Yu Chen, Yaozu Dong

引用次数: 0

BWCC: A FS-Cache Based Cooperative Caching System for Network Storage System 基于FS-Cache的网络存储系统协同缓存系统

2012 IEEE International Conference on Cluster Computing Pub Date : 2012-09-24 DOI: 10.1109/CLUSTER.2012.41

Liu Shi, Zhenjun Liu, Lu Xu

引用次数: 14

Overlay-Centric Load Balancing: Applications to UTS and B&B 以覆盖为中心的负载平衡:在UTS和B&amp中的应用

2012 IEEE International Conference on Cluster Computing Pub Date : 2012-09-24 DOI: 10.1109/CLUSTER.2012.17

Trong-Tuan Vu, B. Derbel, Ali Asim, A. Bendjoudi, N. Melab

引用次数: 5