Starpu 13 Reference Manual

This book constitutes the proceedings of the 30th International Workshop on Languages and Compilers for Parallel Computing, LCPC 2017, held in College Station, TX, USA, in October 2017. The 17 full papers presented together with abstracts of 5 keynote talks, 11 invited speakers and 4 poster papers in this volume were carefully reviewed and selected from 26 submissions. LCPC encourages submissions that go outside its original scope of scientific computing to diverse areas that are enable or enhanced by the power of parallel systems such as mobile computing, big data, relevant aspects of machine learning, data centers, cognitive computing, etc. LCPC strongly encourages personal interaction and technical discussions along the initial material.

The two volumes LNCS 8805 and 8806 constitute the thoroughly refereed post-conference proceedings of 18 workshops held at the 20th International Conference on Parallel Computing, Euro-Par 2014, in Porto, Portugal, in August 2014. The 100 revised full papers presented were carefully reviewed and selected from 173 submissions. The volumes include papers from the following workshops: APCI&E (First Workshop on Applications of Parallel Computation in Industry and Engineering - BigDataCloud (Third Workshop on Big Data Management in Clouds) - DIHC (Second Workshop on Dependability and Interoperability in Heterogeneous Clouds) - FedICI (Second Workshop on Federative and Interoperable Cloud Infrastructures) - Hetero Par (12th International Workshop on Algorithms, Models and Tools for Parallel Computing on Heterogeneous Platforms) - HiBB (5th Workshop on High Performance Bioinformatics and Biomedicine) - LSDVE (Second Workshop on Large Scale Distributed Virtual Environments on Clouds and P2P) - MuCoCoS (7th International Workshop on Multi-/Many-core Computing Systems) - OMHI (Third Workshop on On-chip Memory Hierarchies and Interconnects) - PADAPS (Second Workshop on Parallel and Distributed Agent-Based Simulations) - PROPER (7th Workshop on Productivity and Performance) - Resilience (7th Workshop on Resiliency in High Performance Computing with Clusters, Clouds, and Grids) - REPPAR (First International Workshop on Reproducibility in Parallel Computing) - ROME (Second Workshop on Runtime and Operating Systems for the Many Core Era) - SPPEXA (Workshop on Software for Exascale Computing) - TASUS (First Workshop on Techniques and Applications for Sustainable Ultrascale Computing Systems) - UCHPC (7th Workshop on Un Conventional High Performance Computing) and VHPC (9th Workshop on Virtualization in High-Performance Cloud Computing.

Using the new OpenCL (Open Computing Language) standard, you can write applications that access all available programming resources: CPUs, GPUs, and other processors such as DSPs and the Cell/B.E. processor. Already implemented by Apple, AMD, Intel, IBM, NVIDIA, and other leaders, OpenCL has outstanding potential for PCs, servers, handheld/embedded devices, high performance computing, and even cloud systems. This is the first comprehensive, authoritative, and practical guide to OpenCL 1.1 specifically for working developers and software architects. Written by five leading OpenCL authorities, OpenCL Programming Guide covers the entire specification. It reviews key use cases, shows how OpenCL can express a wide range of parallel algorithms, and offers complete reference material on both the API and OpenCL C programming language. Through complete case studies and downloadable code examples, the authors show how to write complex parallel programs that decompose workloads across many different devices. They also present all the essentials of OpenCL software performance optimization, including probing and adapting to hardware. Coverage includes Understanding OpenCL’s architecture, concepts, terminology, goals, and rationale Programming with OpenCL C and the runtime API Using buffers, sub-buffers, images, samplers, and events Sharing and synchronizing data with OpenGL and Microsoft’s Direct3D Simplifying development with the C++ Wrapper API Using OpenCL Embedded Profiles to support devices ranging from cellphones to supercomputer nodes Case studies dealing with physics simulation; image and signal processing, such as image histograms, edge detection filters, Fast Fourier Transforms, and optical flow; math libraries, such as matrix multiplication and high-performance sparse matrix multiplication; and more Source code for this book is available at https://code.google.com/p/opencl-book-samples/

The LNCS journal Transactions on Large-Scale Data- and Knowledge-Centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for resource sharing across different sites connected through networks has led to an evolution of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high scalability. Current decentralized systems still focus on data and knowledge as their main resource. Feasibility of these systems relies basically on P2P (peer-to-peer) techniques and the support of agent systems with scaling and decentralized control. Synergy between grids, P2P systems, and agent technologies is the key to data- and knowledge-centered systems in large-scale environments. This special issue contains extended and revised versions of 4 papers, selected from the 25 papers presented at the satellite events associated with the 17th East-European Conference on Advances in Databases and Information Systems (ADBIS 2013), held on September 1-4, 2013 in Genoa, Italy. The three satellite events were GID 2013, the Second International Workshop on GPUs in Databases; SoBI 2013, the First International Workshop on Social Business Intelligence: Integrating Social Content in Decision Making; and OAIS 2013, the Second International Workshop on Ontologies Meet Advanced Information Systems. The papers cover various topics in large-scale data and knowledge-centered systems, including GPU-accelerated database systems and GPU-based compression for large time series databases, design of parallel data warehouses, and schema matching. The special issue content, which combines both theoretical and application-based contributions, gives a useful overview of some of the current trends in large-scale data and knowledge management and will stimulate new ideas for further research and development within both the scientific and industrial communities.

Software is the essential enabling means for science and the new economy. It helps us to create a more reliable, flexible and robust society. But software often falls short of our expectations. Current methodologies, tools, and techniques remain expensive and are not yet sufficiently reliable, while many promising approaches have proved to be no more than case-by-case oriented methods. This book contains extensively reviewed papers from the eleventh International Conference on New Trends in software Methodology, Tools and Techniques (SoMeT_12), held in Genoa, Italy, in September 2012. The conference provides an opportunity for scholars from the international research community to discuss and share research experiences of new software methodologies and techniques, and the contributions presented here address issues ranging from research practices and techniques and methodologies to proposing and reporting solutions for global world business. The emphasis has been on human-centric software methodologies, end-user development techniques and emotional reasoning, for an optimally harmonized performance between the design tool and the user.Topics covered include the handling of cognitive issues in software development to adapt it to the user's mental state and intelligent software design in software utilizing new aspects on conceptual ontology and semantics reflected on knowledge base system models. This book provides an opportunity for the software science community to show where we are today and where the future may take us.

Every area of science and engineering today has to process voluminous data sets. Using exact, or even approximate, algorithms to solve intractable problems in critical areas, such as computational biology, takes time that is exponential in some of the underlying parameters. Parallel computing addresses this issue and has become affordable with the

The US, Europe, Japan and China are racing to develop the next generation of supercomputers – exascale machines capable of 10 to the 18th power calculations a second – by 2020. But the barriers are daunting: the challenge is to change the paradigm of high-performance computing. The 2012 biennial high performance workshop, held in Cetraro, Italy in June 2012, focused on the challenges facing the computing research community to reach exascale performance in the next decade. This book presents papers from this workshop, arranged into four major topics: energy, scalability, new architectural concepts and programming of heterogeneous computing systems. Chapter 1 introduces the status of present supercomputers, which are still about two orders of magnitude separated from the exascale mark. Chapter 2 examines energy demands, a major limiting factor of today's fastest supercomputers; the quantum leap in performance required for exascale computing will require a shift in architectures and technology. In Chapter 3, scalable computer paradigms for dense linear algebra on massive heterogeneous systems are presented, and Chapter 4 discusses architectural concepts. Finally, Chapter 5 addresses the programming of heterogeneous systems. This book will be of interest to all those wishing to understand how the development of modern supercomputers is set to advance in the next decade.

XcalableMP is a directive-based parallel programming language based on Fortran and C, supporting a Partitioned Global Address Space (PGAS) model for distributed memory parallel systems. This open access book presents XcalableMP language from its programming model and basic concept to the experience and performance of applications described in XcalableMP. XcalableMP was taken as a parallel programming language project in the FLAGSHIP 2020 project, which was to develop the Japanese flagship supercomputer, Fugaku, for improving the productivity of parallel programing. XcalableMP is now available on Fugaku and its performance is enhanced by the Fugaku interconnect, Tofu-D. The global-view programming model of XcalableMP, inherited from High-Performance Fortran (HPF), provides an easy and useful solution to parallelize data-parallel programs with directives for distributed global array and work distribution and shadow communication. The local-view programming adopts coarray notation from Coarray Fortran (CAF) to describe explicit communication in a PGAS model. The language specification was designed and proposed by the XcalableMP Specification Working Group organized in the PC Consortium, Japan. The Omni XcalableMP compiler is a production-level reference implementation of XcalableMP compiler for C and Fortran 2008, developed by RIKEN CCS and the University of Tsukuba. The performance of the XcalableMP program was used in the Fugaku as well as the K computer. A performance study showed that XcalableMP enables a scalable performance comparable to the message passing interface (MPI) version with a clean and easy-to-understand programming style requiring little effort.