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3. An Improvement Over Threads Communications on Multi-Core Processors

Author

Fotohi, Reza, Effatparvar, Mehdi, Sarkohaki, Fateme, Behzad, Shahram, and balov, Jaber Hoseini

Subjects
Computer Science - Operating Systems
Abstract

Multicore is an integrated circuit chip that uses two or more computational engines (cores) places in a single processor. This new approach is used to split the computational work of a threaded application and spread it over multiple execution cores, so that the computer system can benefits from a better performance and better responsiveness of the system. A thread is a unit of execution inside a process that is created and maintained to execute a set of actions/ instructions. Threads can be implemented differently from an operating system to another, but the operating system is in most cases responsible to schedule the execution of different threads. Multi-threading improving efficiency of processor performance with a cost-effective memory system. In this paper, we explore one approach to improve communications for multithreaded. Pre-send is a software Controlled data forwarding technique that sends data to destination's cache before it is needed, eliminating cache misses in the destination's cache as well as reducing the coherence traffic on the bus. we show how we could improve the overall system performance by addition of these architecture optimizations to multi-core processors., Comment: This submission has been withdrawn by arXiv administrators due to inappropriate text reuse from external sources

Published
2019

6. Network Layer Challenges of IEEE 802.11n Wireless Ad Hoc Networks

Author

EffatParvar, Mehdi, Yazdani, Nasser, EffatParvar, MohammadReza, Teymoori, Peyman, Movaghar, Ali, Akan, Ozgur, Series editor, Bellavista, Paolo, Series editor, Cao, Jiannong, Series editor, Dressler, Falko, Series editor, Ferrari, Domenico, Series editor, Gerla, Mario, Series editor, Kobayashi, Hisashi, Series editor, Palazzo, Sergio, Series editor, Sahni, Sartaj, Series editor, Shen, Xuemin (Sherman), Series editor, Stan, Mircea, Series editor, Xiaohua, Jia, Series editor, Zomaya, Albert, Series editor, Coulson, Geoffrey, Series editor, Sénac, Patrick, editor, Ott, Max, editor, and Seneviratne, Aruna, editor

Published
2012
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7. Pattern Recognition in Online Environment by Data Mining Approach

Author

EffatParvar, MohammadReza, EffatParvar, Mehdi, Rahgozar, Maseud, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Cao, Longbing, editor, Bazzan, Ana L. C., editor, Gorodetsky, Vladimir, editor, Mitkas, Pericles A., editor, Weiss, Gerhard, editor, and Yu, Philip S., editor

Published
2010
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8. Improvement of on Demand Multicast Routing Protocol in Ad Hoc Networks to Achieve Good Scalability and Reliability

Author

EffatParvar, MohammadReza, EffatParvar, Mehdi, Fathy, Mahmoud, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Gervasi, Osvaldo, editor, Murgante, Beniamino, editor, Laganà, Antonio, editor, Taniar, David, editor, Mun, Youngsong, editor, and Gavrilova, Marina L., editor

Published
2008
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15. IMLFQ Scheduling Algorithm with Combinational Fault Tolerant Method

Author

MohammadReza EffatParvar, Bemana, Akbar, and EffatParvar, Mehdi

Subjects
Computer Science::Performance, Queue, Recurrent Neural Network, Fault Tolerant, Scheduling, Computer Science::Operating Systems, IMLFQ
Abstract

Scheduling algorithms are used in operating systems to optimize the usage of processors. One of the most efficient algorithms for scheduling is Multi-Layer Feedback Queue (MLFQ) algorithm which uses several queues with different quanta. The most important weakness of this method is the inability to define the optimized the number of the queues and quantum of each queue. This weakness has been improved in IMLFQ scheduling algorithm. Number of the queues and quantum of each queue affect the response time directly. In this paper, we review the IMLFQ algorithm for solving these problems and minimizing the response time. In this algorithm Recurrent Neural Network has been utilized to find both the number of queues and the optimized quantum of each queue. Also in order to prevent any probable faults in processes' response time computation, a new fault tolerant approach has been presented. In this approach we use combinational software redundancy to prevent the any probable faults. The experimental results show that using the IMLFQ algorithm results in better response time in comparison with other scheduling algorithms also by using fault tolerant mechanism we improve IMLFQ performance., {"references":["M. R. EffatParvar, M. EffatParvar, A. T. Haghoghat, R. Mahini, and\nM. Zarei, \"An Intelligent MLFQ Scheduling Algorithm (IMLFQ),\"\nReal-Time Computing Systems & Applications (RTCOMP), Jun 2006.","K. U. Herath, and Sh. Hashimoto, \"Automated trend diagnosis using\nneural networks,\" 0-7803-6583- IEEE, 1186-1191, 2000.","C. Molter, U. Salihoglu, and H. Bersini, \"Introduction of an hebbian\nunsupervised learning algorithm to boost the encoding capacity of\nHopfield networks,\" Proceedings of the IJCNN, 2005.","Ma. Sheng, and Ji. Chuanyi, \"Fast Training of Recurrent Networks\nBased on the EM Algorithm. Transactions on Neural Networks,\" IEEE,\nVol. 9, No.1, Jan 1998.","N. K. Kasabov, Foundations of Neural Networks, Fuzzy Systems, and\nKnowledge Engineering, A Bradford Book The MIT Press Cambridge,\nMassachusetts London, England, 1996, Massachusetts Institute of\nTechnology, 1998.","F. A. Gers, and J. Schmidhuber, \"LSTM recurrent networks learn\nsimple context free and context sensitive languages,\" Transactions on\nNeural Networks, IEEE, 12(6):1333-1340, 2001.","J. Guynes, \"Impact of System Response Time on Stat Anxiety,\"\nCommunications of the ACM, 1988.","A. Memon, A. Porter, C. Yilmaz, A. Nagarajan, D. C. Schmidt, and B.\nNatarajan, \"Skoll: Distributed Continuous Quality Assurance,\" Proc,\nInt-l Conf, Software Eng, (ICSE), pp. 459- 468, 2004.","S. Ghosh, R. Melhem, and D. Mosse, \"Fault-tolerance through\nscheduling of aperiodic tasks in hard real-time mul-tiprocessor\nsystems,\" IEEE Trans, Parallel and Distributed Systems, vol.8, no.3,\npp.272-183, Mar 1997.\n[10] G. Manimaran, and C. Siva Ram Murthy, \"A fault-tolerant dynamic\nscheduling algorithm for multiprocessor real-time systems and its\nanalysis,\" IEEE Trans, Parallel and Distributed Systems, vol.9, no.11,\nNov 1998."]}

Published
2008
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