This book constitutes the thoroughly refereed post-conference proceedings of the 28th International Workshop on Languages and Compilers for Parallel Computing, LCPC 2015, held in Raleigh, NC, USA, in September 2015. The 19 revised full papers were carefully reviewed and selected from 44 submissions. The papers are organized in topical sections on programming models, optimizing framework, parallelizing compiler, communication and locality, parallel applications and data structures, and correctness and reliability.

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.

This book constitutes the thoroughly refereed post-conference proceedings of the 29th International Workshop on Languages and Compilers for Parallel Computing, LCPC 2016, held in Rochester, NY, USA, in September 2016. The 20 revised full papers presented together with 4 short papers were carefully reviewed. The papers are organized in topical sections on large scale parallelism, resilience and persistence, compiler analysis and optimization, dynamic computation and languages, GPUs and private memory, and runt-time and performance analysis.

This book constitutes the refereed proceedings of the 21st International Conference on Parallel and Distributed Computing, Euro-Par 2015, held in Vienna, Austria, in August 2015. The 51 revised full papers presented together with 2 invited papers were carefully reviewed and selected from 190 submissions. The papers are organized in the following topical sections: support tools and environments; performance modeling, prediction and evaluation; scheduling and load balancing; architecture and compilers; parallel and distributed data management; grid, cluster and cloud computing; distributed systems and algorithms; parallel and distributed programming, interfaces and languages; multi- and many-core programming; theory and algorithms for parallel computation; numerical methods and applications; and accelerator computing.

This book brings together two important trends: graph algorithms and high-performance computing. Efficient and scalable execution of graph processing applications in data or network analysis requires innovations at multiple levels: algorithms, associated data structures, their implementation and tuning to a particular hardware. Further, programming languages and the associated compilers play a crucial role when it comes to automating efficient code generation for various architectures. This book discusses the essentials of all these aspects. The book is divided into three parts: programming, languages, and their compilation. The first part examines the manual parallelization of graph algorithms, revealing various parallelization patterns encountered, especially when dealing with graphs. The second part uses these patterns to provide language constructs that allow a graph algorithm to be specified. Programmers can work with these language constructs without worrying about their implementation, which is the focus of the third part. Implementation is handled by a compiler, which can specialize code generation for a backend device. The book also includes suggestive results on different platforms, which illustrate and justify the theory and practice covered. Together, the three parts provide the essential ingredients for creating a high-performance graph application. The book ends with a section on future directions, which offers several pointers to promising topics for future research. This book is intended for new researchers as well as graduate and advanced undergraduate students. Most of the chapters can be read independently by those familiar with the basics of parallel programming and graph algorithms. However, to make the material more accessible, the book includes a brief background on elementary graph algorithms, parallel computing and GPUs. Moreover it presents a case study using Falcon, a domain-specific language for graph algorithms, to illustrate the concepts.

This book constitutes the thoroughly refereed post-conference proceedings of the 31st International Workshop on Languages and Compilers for Parallel Computing, LCPC 2018, held in Salt Lake City, UT, USA, in October 2018. The 14 revised full papers were carefully reviewed and selected from 26 submissions. Specific topics are compiling for parallelism and parallel compilers, static, dynamic, and adaptive optimization of parallel programs, parallel programming models and languages, formal analysis and verification of parallel programs, parallel runtime systems and libraries, performance analysis and debugging tools for concurrency and parallelism, parallel algorithms and concurrent data structures, parallel applications, synchronization and concurrency control, software engineering for parallel programs, fault tolerance for parallel systems, and parallel programming and compiling for heterogeneous systems.