Download Advanced Parallel Processing Technologies: 11th by Yunji Chen, Paolo Ienne, Qing Ji PDF

By Yunji Chen, Paolo Ienne, Qing Ji

ISBN-10: 3319232150

ISBN-13: 9783319232157

This ebook constitutes the lawsuits of the eleventh foreign Symposium on complicated Parallel Processing applied sciences, APPT 2015, held in Jinan, China, in August 2015. The eight papers offered during this quantity have been rigorously reviewed and chosen from 24 submissions. They care for the new advances in gigantic facts processing; parallel architectures and structures; parallel software program; parallel algorithms and purposes; and dispensed and cloud computing.

Show description

Read or Download Advanced Parallel Processing Technologies: 11th International Symposium, APPT 2015, Jinan, China, August 20-21, 2015, Proceedings PDF

Similar international_1 books

Advances in Cryptology - CRYPTO 2003: 23rd Annual International Cryptology Conference, Santa Barbara, California, USA, August 17-21, 2003. Proceedings

Crypto 2003, the twenty third Annual Crypto convention, used to be backed via the Int- nationwide organization for Cryptologic study (IACR) in cooperation with the IEEE computing device Society Technical Committee on defense and privateness and the pc technological know-how division of the collage of California at Santa Barbara.

Computational Logistics: 5th International Conference, ICCL 2014, Valparaiso, Chile, September 24-26, 2014. Proceedings

This e-book constitutes the refereed court cases of the fifth overseas convention on Computational Logistics, ICCL 2014, held in Valparaiso, Chile, in September 2014. The eleven papers offered during this quantity have been rigorously reviewed and chosen for inclusion within the ebook. they're prepared in topical sections entitled: optimization of shipping difficulties; box terminal purposes; simulation and environmental sustainability functions.

Machine Learning, Optimization, and Big Data: Second International Workshop, MOD 2016, Volterra, Italy, August 26-29, 2016, Revised Selected Papers

This booklet constitutes revised chosen papers from the second one overseas Workshop on computing device studying, Optimization, and massive information, MOD 2016, held in Volterra, Italy, in August 2016. The forty papers provided during this quantity have been rigorously reviewed and chosen from ninety seven submissions. those complaints comprise papers within the fields of computing device studying, Computational Optimization and DataScience providing a considerable array of principles, applied sciences, algorithms, equipment and functions.

Additional resources for Advanced Parallel Processing Technologies: 11th International Symposium, APPT 2015, Jinan, China, August 20-21, 2015, Proceedings

Sample text

45–59, 2015. 1007/978-3-319-23216-4_4 46 L. Wang et al. g. ) [2, 3]. In non-identical-ISA HMPs, cores have non-identical ISAs [4, 5] and different architectures correspondingly. In this paper, we focus on single-ISA HMPs, since it maximizes the flexibility of scheduling. The overall performance of single-ISA HMPs mainly relies on the efficiency of scheduling, which dynamically assigns applications to the appropriate cores. However, since the current operate system is unaware of the heterogeneity of architectures, the inefficient random algorithm and round-robin algorithm are the most frequently used [6].

However, one challenge is that how to dig the huge value from the large scale data set whin an acceptable time. To deal with this urge, MapReduce framework [1] is proposed by Google, which could process a huge data set by utilizing the computing resources in parallel. Moreover, developers only need to write the map and reduce functions, and the other works are handled by MapReduce runtime automatically. Therefore, the open-source implementations, such as Hadoop and Spark, have been widely used in internet enterprises and research communities.

Overall, the goal of our work is to utilize the power of CPU-MIC cluster to process large scale data set in efficient, fault tolerant, and easy programming ways. 1 The Overall Framework Like other MapReduce frameworks, the overall workflow of our system includes task distribution, map, shuffle, and reduce, etc. The most difference is that the tasks are not only processed by CPUs, but also by MIC coprocessors. Figure 1 shows the overall framework. The job manager manages a MapReduce job. When a new job comes, it splits the job into small tasks firstly.

Download PDF sample

Rated 4.77 of 5 – based on 48 votes