2014 IEEE 33rd International Performance Computing and Communications Conference (IPCCC)最新文献_第4页

Worst-case performance guaranteed data cache 最坏情况下的性能保证数据缓存

2014 IEEE 33rd International Performance Computing and Communications Conference (IPCCC) Pub Date : 2014-12-01 DOI: 10.1109/PCCC.2014.7017044

Y. Huangfu, Wei Zhang

引用次数: 1

Thread mapping using system-level throughput prediction model for shared memory multicores 使用系统级吞吐量预测模型的线程映射用于共享内存多核

2014 IEEE 33rd International Performance Computing and Communications Conference (IPCCC) Pub Date : 2014-12-01 DOI: 10.1109/PCCC.2014.7017045

Reshmi Mitra, B. Joshi, R. Adams

引用次数: 0

RainbowRate: MIMO rate adaptation in 802.11n WiLD links RainbowRate: 802.11n WiLD链路的MIMO速率适应

2014 IEEE 33rd International Performance Computing and Communications Conference (IPCCC) Pub Date : 2014-12-01 DOI: 10.1109/PCCC.2014.7017084

Z. Zhao, Fucheng Zhang, Shaoping Guo, Xiangyang Li, Junze Han

引用次数: 9

A centralized latency optimization solution for tree-based application layer multicast 基于树的应用层多播集中延迟优化方案

2014 IEEE 33rd International Performance Computing and Communications Conference (IPCCC) Pub Date : 2014-12-01 DOI: 10.1109/PCCC.2014.7017030

Xinchang Zhang, Weidong Gu, Lu Wang, Xiaomin Zhu, Meng Sun

引用次数: 1

An extended contention period protocol for MIMO wireless networks 一种用于MIMO无线网络的扩展争用周期协议

2014 IEEE 33rd International Performance Computing and Communications Conference (IPCCC) Pub Date : 2014-12-01 DOI: 10.1109/PCCC.2014.7017025

K. Warasup, M. Hamamura

引用次数: 2

Accurate statistical performance modeling and validation of out-of-order processors using Monte Carlo methods 使用蒙特卡罗方法的乱序处理器的精确统计性能建模和验证

2014 IEEE 33rd International Performance Computing and Communications Conference (IPCCC) Pub Date : 2014-12-01 DOI: 10.1109/PCCC.2014.7017075

Waleed Alkohlani, Jeanine E. Cook, J. Cook

{"title":"Accurate statistical performance modeling and validation of out-of-order processors using Monte Carlo methods","authors":"Waleed Alkohlani, Jeanine E. Cook, J. Cook","doi":"10.1109/PCCC.2014.7017075","DOIUrl":"https://doi.org/10.1109/PCCC.2014.7017075","url":null,"abstract":"Although simulation is an indispensable tool in computer architecture research and development, there is a pressing need for new modeling techniques to improve simulation speeds while maintaining accuracy and robustness. It is no longer practical to use only cycle-accurate processor simulation (the dominant simulation method) for design space and performance studies due to its extremely slow speed. To address this and other problems of cycle-accurate simulation, we propose a fast and accurate statistical modeling methodology based on Monte Carlo methods to model the performance of modern out-of-order processors. Using these statistical models, simulation and performance prediction can be achieved in seconds regardless of the modeled application's size. This paper presents the proposed methodology and its first application to model a modern out-of-order execution processor. We present a statistical model for the Opteron (Magny-Cours) processor and validate it against real hardware. Using SPEC CPU2006 and Mantevo benchmarks, the model can predict performance in terms of cycles-per-instruction within 4.79% of actual on average. We also present a novel method for generating CPI stacks which are CPI representations that quantify the contribution of individual performance components to the total CPI. To further validate these CPI stacks, we use a detailed processor simulator, build a statistical model of the simulator architecture, validate the model against the simulator, and then proceed to validate the CPI stacks predicted by our statistical model. The average CPI prediction error is 5.6%, and the average difference between the predicted and measured CPI components is 1.3% with a maximum difference of 5.4%.","PeriodicalId":105442,"journal":{"name":"2014 IEEE 33rd International Performance Computing and Communications Conference (IPCCC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127503489","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: 2

Prediction and correction of traffic matrix in an IP backbone network IP骨干网流量矩阵的预测与校正

2014 IEEE 33rd International Performance Computing and Communications Conference (IPCCC) Pub Date : 2014-12-01 DOI: 10.1109/PCCC.2014.7017051

Wei Liu, Ao Hong, Liang Ou, Wenchao Ding, Ge Zhang

{"title":"Prediction and correction of traffic matrix in an IP backbone network","authors":"Wei Liu, Ao Hong, Liang Ou, Wenchao Ding, Ge Zhang","doi":"10.1109/PCCC.2014.7017051","DOIUrl":"https://doi.org/10.1109/PCCC.2014.7017051","url":null,"abstract":"The prediction of traffic matrices (TM) is critical for many IP network management tasks. With the recent development of high-speed traffic measurement technologies, complete TM could be collected from operational IP networks. In this paper, we report our efforts in predicting the TM measured from a real IP backbone network in China. The new problem here is how to deal with the rich but noisy TM data and predict various traffics, ranging from the original-destination (OD) flow traffic, the node traffic to the total network traffic. After examining the traffic characteristics, we choose the node traffic as the principal data for prediction, and propose three prediction and correction methods: Independent Node Prediction (INP), Total Matrix Prediction with Key Element Correction (TMP-KEC) and Principle Component Prediction with Fluctuation Component Correction (PCP-FCC). TMP-KEC and PCP-FCC are designed with different purposes, i.e., for smaller prediction errors of the total network and the OD flows, respectively. The results show that, INP performs worst; TMP-KEC efficiently reduces the prediction errors of the large matrix elements; while, PCP-FCC achieves smaller average prediction errors for the elements as well as the complete matrix.","PeriodicalId":105442,"journal":{"name":"2014 IEEE 33rd International Performance Computing and Communications Conference (IPCCC)","volume":"264 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124895278","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: 12

ReMA: Real-time 3D video streaming system for mobile devices ReMA:移动设备的实时3D视频流系统

2014 IEEE 33rd International Performance Computing and Communications Conference (IPCCC) Pub Date : 2014-12-01 DOI: 10.1109/PCCC.2014.7017111

Suk kyu Lee, Hyunsoon Kim, Woonghee Lee, Hwantae Kim, Jongtack Jung, Hwangnam Kim

引用次数: 2

Effects of quality of service schemes on the capacity and dimensioning of LTE networks 服务质量方案对LTE网络容量和规模的影响

2014 IEEE 33rd International Performance Computing and Communications Conference (IPCCC) Pub Date : 2014-12-01 DOI: 10.1109/pccc.2014.7017070

Fatima Furqan, D. Hoang, I. Collings

{"title":"Effects of quality of service schemes on the capacity and dimensioning of LTE networks","authors":"Fatima Furqan, D. Hoang, I. Collings","doi":"10.1109/pccc.2014.7017070","DOIUrl":"https://doi.org/10.1109/pccc.2014.7017070","url":null,"abstract":"With high data rate and mobility support wireless networks are becoming an integral part of the ubiquitous broadband access. Appropriate dimensioning of the wireless access networks is essential to satisfy users' Quality of Service (QoS) requirements. Once the network is dimensioned, dynamic variations in traffic or population distribution can affect the capability of the network to deliver the agreed QoS of connections. Consequently, re-dimension the network may be necessary. Current researches do not discuss the effects of QoS schemes on the capacity of the network. In this paper, we investigate the impact of QoS schemes on the capacity of the network. The objective is to determine the capability of the network to deal with the variations in the demography of the covered area and the user's traffic profile with the proposed QoS schemes including Congestion Control (CC) and Radio Admission Control (RAC). Different scenarios are presented to evaluate the effects of QoS schemes on the capacity of the network. This investigation will assist network operators to determine the point after which the network needs to be re-dimensioned.","PeriodicalId":105442,"journal":{"name":"2014 IEEE 33rd International Performance Computing and Communications Conference (IPCCC)","volume":"2246 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130210678","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: 5

Blackbox security evaluation of chromecast network communications chromecast网络通信黑箱安全性评价

2014 IEEE 33rd International Performance Computing and Communications Conference (IPCCC) Pub Date : 2014-12-01 DOI: 10.1109/PCCC.2014.7017050

Ali Tekeoglu, A. Tosun

引用次数: 12