Programming Multicore and Many-core Computing Systems

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Programming multi-core and many-core computing systems

Sabri Pllana, Linnaeus University, Sweden

Fatos Xhafa, Technical University of Catalonia, Spain

Provides state-of-the-art methods for programming multi-core and many-core systems

The book comprises a selection of twenty two chapters covering: fundamental techniques and algorithms; programming approaches; methodologies and frameworks; scheduling and management; testing and evaluation methodologies; and case studies for programming multi-core and many-core systems.

Program development for multi-core processors, especially for heterogeneous multi-core processors, is significantly more complex than for single-core processors. However, programmers have been traditionally trained for the development of sequential programs, and only a small percentage of them have experience with parallel programming. In the past, only a relatively small group of programmers interested in High Performance Computing (HPC) was concerned with the parallel programming issues, but the situation has changed dramatically with the appearance of multi-core processors on commonly used computing systems. It is expected that with the pervasiveness of multi-core processors, parallel programming will become mainstream.

The pervasiveness of multi-core processors affects a large spectrum of systems, from embedded and general-purpose, to high-end computing systems. This book assists programmers in mastering the efficient programming of multi-core systems, which is of paramount importance for the software-intensive industry towards a more effective product-development cycle.

Key features:

  • Lessons, challenges, and roadmaps ahead.
  • Contains real world examples and case studies.
  • Helps programmers in mastering the efficient programming of multi-core and many-core systems.

The book serves as a reference for a larger audience of practitioners, young researchers and graduate level students. A basic level of programming knowledge is required to use this book.

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About the author

Sabri Pllana is an Associate Professor in the Department of Computer Science at Linnaeus University, Sweden. Before joining Linnaeus University, he worked for 12 years at the Research Group Scientific Computing, University of Vienna in Austria. His current research interests include performance-oriented software engineering and self-adaptive techniques for performance portability across various heterogeneous computing systems. He contributed to several EU-funded projects and coordinated the FP7 project PEPPHER. He has contributed as member/chair to more than 60 program committees. He holds a PhD degree (with distinction) in computer science from the Vienna University of Technology. He is a Senior Member of the IEEE, a member of the European Network of Excellence on High Performance and Embedded Architecture and Compilation (HiPEAC) and of the European ICT COST Action (IC1406) on High-Performance Modelling and Simulation for Big Data Applications, an associate member of ETP4HPC, and a member of the Euro-Par Advisory Board.

Fatos Xhafa received his PhD in Computer Science in 1998 from the Technical University of Catalonia (UPC), Barcelona, Spain. Currently, he holds a permanent position of Professor Titular d’Universitat at UPC. He was a Visiting Professor at University of London (UK), 2009-2010, and Research Associate at Drexel University (USA), 2004/2005. He has widely published in international journals, conferences/workshops, book chapters, edited books and proceedings in the field. He is editor in Chief of the International Journal of Grid and Utility Computing, International Journal of Space-based and Situated Computing, Inderscience. He is Editor in Chief of the Elsevier Book Series “Intelligent Data-Centric Systems” and of Springer Lecture Notes in Data Engineering and Communication Technologies. He is a member of IEEE Communications Society, IEEE Systems, Man & Cybernetics Society and Emerging Technical Subcommittee of IoT. His research interests include parallel and distributed computing, massive data processing, collective intelligence, optimization, trustworthy computing, machine learning, etc.
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Additional Information

Publisher
John Wiley & Sons
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Published on
Jan 23, 2017
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Pages
528
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ISBN
9781119332008
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Language
English
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Genres
Computers / Computer Engineering
Computers / Networking / General
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Content Protection
This content is DRM protected.
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Ciprian Dobre

Pervasive Computing: Next Generation Platforms for Intelligent Data Collection

presents current advances and state-of-the-art work on methods, techniques, and algorithms designed to support pervasive collection of data under ubiquitous networks of devices able to intelligently collaborate towards common goals.

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Pervasive computing has developed technology that allows sensing, computing, and wireless communication to be embedded in everyday objects, from cell phones to running shoes, enabling a range of context-aware applications. Pervasive computing is supported by technology able to acquire and make use of the ubiquitous data sensed or produced by many sensors blended into our environment, designed to make available a wide range of new context-aware applications and systems. While such applications and systems are useful, the time has come to develop the next generation of pervasive computing systems. Future systems will be data oriented and need to support quality data, in terms of accuracy, latency and availability.

Pervasive Computing is intended as a platform for the dissemination of research efforts and presentation of advances in the pervasive computing area, and constitutes a flagship driver towards presenting and supporting advanced research in this area.

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Offers a coherent and realistic image of today’s architectures, techniques, protocols, components, orchestration, choreography, and development related to pervasive computingExplains the state-of-the-art technological solutions necessary for the development of next-generation pervasive data systems, including: components for intelligently collecting data, resource and data management issues, fault tolerance, data security, monitoring and controlling big data, and applications for pervasive context-aware processingPresents the benefits of pervasive computing, and the development process of scientific and commercial applications and platforms to support them in this fieldProvides numerous illustrative examples and follows both theoretical and practical results to serve as a platform for the dissemination of research advances in the pervasive computing area
Fatos Xhafa
During the past decades scheduling has been among the most studied op- mization problemsanditisstillanactiveareaofresearch!Schedulingappears in many areas of science, engineering and industry and takes di?erent forms depending on the restrictions and optimization criteria of the operating en- ronments [8]. For instance, in optimization and computer science, scheduling has been de?ned as “the allocation of tasks to resources over time in order to achieve optimality in one or more objective criteria in an e?cient way” and in production as “production schedule, i. e. , the planning of the production or the sequence of operations according to which jobs pass through machines and is optimal with respect to certain optimization criteria. ” Although there is a standardized form of stating any scheduling problem, namely “e?cient allocation ofn jobs onm machines –which can process no more than one activity at a time– with the objective to optimize some - jective function of the job completion times”, scheduling is in fact a family of problems. Indeed, several parameters intervene in the problem de?nition: (a) job characteristics (preemptive or not, precedence constraints, release dates, etc. ); (b) resource environment (single vs. parallel machines, un- lated machines, identical or uniform machines, etc. ); (c) optimization criteria (minimize total tardiness, the number of late jobs, makespan, ?owtime, etc. ; maximize resource utilization, etc. ); and, (d) scheduling environment (static vs. dynamic,intheformerthenumberofjobstobeconsideredandtheirready times are available while in the later the number of jobs and their charact- istics change over time).
Nik Bessis
Nik Bessis
Sabri Pllana
Programming multi-core and many-core computing systems

Sabri Pllana, Linnaeus University, Sweden

Fatos Xhafa, Technical University of Catalonia, Spain

Provides state-of-the-art methods for programming multi-core and many-core systems

The book comprises a selection of twenty two chapters covering: fundamental techniques and algorithms; programming approaches; methodologies and frameworks; scheduling and management; testing and evaluation methodologies; and case studies for programming multi-core and many-core systems.

Program development for multi-core processors, especially for heterogeneous multi-core processors, is significantly more complex than for single-core processors. However, programmers have been traditionally trained for the development of sequential programs, and only a small percentage of them have experience with parallel programming. In the past, only a relatively small group of programmers interested in High Performance Computing (HPC) was concerned with the parallel programming issues, but the situation has changed dramatically with the appearance of multi-core processors on commonly used computing systems. It is expected that with the pervasiveness of multi-core processors, parallel programming will become mainstream.

The pervasiveness of multi-core processors affects a large spectrum of systems, from embedded and general-purpose, to high-end computing systems. This book assists programmers in mastering the efficient programming of multi-core systems, which is of paramount importance for the software-intensive industry towards a more effective product-development cycle.

Key features:

Lessons, challenges, and roadmaps ahead. Contains real world examples and case studies. Helps programmers in mastering the efficient programming of multi-core and many-core systems.

The book serves as a reference for a larger audience of practitioners, young researchers and graduate level students. A basic level of programming knowledge is required to use this book.

Thanasis Daradoumis
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