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Diman Zad Tootaghaj 's publications

Diman Zad Tootaghaj 's publications
1.D. Z. Tootaghaj, F. Farhat. Optimal placement of Cores, Caches and Memory controllers in NoC. arXiv, 2016. [link] [pdf] 2.F. Farhat, D. Z. Tootaghaj, M. Arjomand. Towards optimizing data computing in the cloud. arXiv, 2016. [link] [pdf] 3. F. Farhat, D. Z. Tootaghaj, Y. He, A. Sivasubramaniam, M. T. Kandemir, C. R. Das. Stochastic modeling and optimization of stragglers. IEEE transaction on Cloud Computing (TCC), 2016. [link] [pdf]
4.D. Z. Tootaghaj,  Evaluating cloud workload characteritics. Master’s thesis, The Pennsylvania State University, 2015. [link] [pdf] 5.D. Z. Tootaghaj, F. Farhat, M. Arjomand, P. Faraboschi, M. T. Kandemir, A. Sivasubramaniam, C. R. Das, Evaluating the Combined Impact of Datacenter Architecture and Cloud Workload Characteristics on Performance, Network Traffic and Cost, IEEE International Symposium on Workload Characterization (IISWC) 2015. [link] [pdf] 6.F. Farhat, D. Z. Tootaghaj, A. Sivasubramaniam, M. T. Kandemir, C. …

Towards Stochastically Optimizing Data Computing Flows

Optimal Placement of Cores Caches and MemoryControllers in NoC

FORK-JOIN QUEUE MODELING AND OPTIMAL SCHEDULING IN PARALLEL PROGRAMMING FRAMEWORKS

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FORK-JOIN QUEUE MODELING AND OPTIMAL SCHEDULING IN PARALLEL PROGRAMMING FRAMEWORKS ABSTRACT MapReduce framework is widely used to parallelize batch jobs since it exploits a high degree of multi-tasking to process them. However, it has been observed that when the number of servers increases, the map phase can take much longer than expected. This thesis analytically shows that the stochastic behavior of the servers has a negative effect on the completion time of a MapReduce job, and continuously increasing the number of servers without accurate scheduling can degrade the overall performance. We analytically model the map phase in terms of hardware, system, and application parameters to capture the effects of stragglers on the performance. Mean sojourn time (MST), the time needed to sync the completed tasks at a reducer, is introduced as a performance metric and mathematically formulated. Following that, we stochastically investigate the optimal task scheduling which leads to an equilibri…

Shahrzad Series

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