Using MPI – Portable Parallel Programming with the Message–Passing Interface
Using OpenMP – Portable Shared Memory Parallel Programming
Why purchase expensive add-on cards or bus interfaces when you can develop effective and economical data acquisition and process controls using C programs? Using the under employed printer adapter (that is, the parallel port of your PC, you can turn yourcomputer into a powerful tool for developing microprocessor applications. Learn how to build a complete data acquisition system and such varied applications as a CCD camera controller, a photometer interface, and a wave form generator. The book also covers the Enhanced Parallel Port (EPP), the Extended Capabilities Port (ECP), interfacing Analog to Digital converters, and data acquisition under Linux. This extraordinary software approach to interfacing through the parallel port will be especially appealing to programmers involved in control systems design and device development, as well as to those who work with real-time and embedded systems.
The objective of this project report is to explore the architecture of E1350 IBM eServer Cluster and parallel programming in OpenMP, MPI and MPI+OpenMP using Intel C/C++ Compilers. By implementing some applications using these programming models, we can analyze the effects of each of the model on speedup. I have used four applications to analyze the effects that are Jacobi Iterative Method, Alternating Direction Implicit (ADI), Matrix Multiplication and Bucket Sorting. The general observations are as follows: • Using MPI and MPI+OpenMP will not give significant speedup if used directly with the same program structure. We need to have modified the structure of the programs to reduce communication-to-computation ratio as much as possible. • Running threads on different physical processors can cause significant barrier. • When using 8-threads, synchronization must occur between all threads and this need communications between two physical processors. • Communications between two physical processors is expensive compare to communications between cores. Thus, more cost is paid in term of more waiting time at barrier.
Book Description* Helps readers examine exactly what it means to program computers * Emphasizes the development of problem-solving techniques through concepts and exercises that reflect today's programming practices * Unique focus on problem solving, rather than technology, supported by real-world business applications * Focuses on structured programming techniques, the building blocks of all forms of programming
The book describes the implementation of a structured programming environment providing stream parallel skeletons/patterns(pipelines and Task-farms) implemented on top of MPI and targeting shared memory multi-cores.The MPI framework performance is evaluated and the results compared with the ones achieved when executing the same applications using FastFlow. The framework provides an easy interface for a user and totally abstracts the requirement of knowledge of MPI. While the implementation was based on MPI and C language, a programmer can use the framework with only the knowledge of C language. More Stream parallel applications can be satisfied by this framework by arbitrarily composing supported skeleton patterns. Which makes it more powerful and usable for almost all application that can be computed in stream parallel pattern. More skeleton patterns can also be further implemented and add to the existing skeleton pattern set.
"Patterns for Parallel Software Design" is essential reading for developers looking to understand patterns for parallel programming. Written from an architectural point of view, "Patterns for Parallel Software Design" presents a pattern-oriented software architecture approach to parallel software design providing solutions in concurrent and distributed programming, based on existing design knowledge. A pattern-oriented approach to parallel software design is not a design method in the classic sense, but a new way of managing and utilizing existing design knowledge for designing parallel programs. Using this approach leads to parallel software systems that are modular, adaptable, understandable and evolvable. Thus, this method aims to enhance not only build-time properties of parallel systems, but also their run-time properties. Key topics include: use of known solutions in concurrent and distributed programming, applied to the development of parallel programs. significant architectural patterns that describe how to divide an algorithm and/or data to find a suitable partition, and hence, link it with a programming structure that allows for such a division. delivers proven solutions to the problems faced by parallel programmers. Coverage is aimed at developers new to parallel programming, who require a base to understand parallel software design and implementation for future parallel platforms. "Patterns for Parallel Software Design" is an essential must-have guide for developers and programmers who want to solve unique design problems.
Nowadays, GPUs are multi-core parallel processors with very high memory bandwidth. Recently for last few years developers and researchers are offloading computationally intensive tasks to GPUs to gain significant speedup compared to the CPU. Most of the image processing algorithms perform same operation on a large number of pixels, which can be parallelized on single instruction multiple data GPU architecture. Initially shader based frameworks like GLSL, Cg etc have been used for GP-GPU. NVIDIA has developed CUDA to write scalable parallel programs in C like language. GLSL, Cg and CUDA provide significant speedup, however they offer complex integration frameworks and require specialized programming skills. Most of GPU based frameworks are developed using procedural programming, which limits the scope of flexibility, code reusability, information and complexity hiding. In this book, we bring in an object oriented framework for the CUDA based image processing. We demonstrate a set of design patterns exploiting programming advantages of an object oriented language, such as encapsulation, information hiding, code reusability, complexity hiding and extensibility.
Programming Massively Parallel Processors: A Hands-on Approach shows both student and professional alike the basic concepts of parallel programming and GPU architecture. Various techniques for constructing parallel programs are explored in detail. Case studies demonstrate the development process, which begins with computational thinking and ends with effective and efficient parallel programs. Topics of performance, floating-point format, parallel patterns, and dynamic parallelism are covered in depth. This best-selling guide to CUDA and GPU parallel programming has been revised with more parallel programming examples, commonly-used libraries such as Thrust, and explanations of the latest tools. With these improvements, the book retains its concise, intuitive, practical approach based on years of road-testing in the authors' own parallel computing courses. Updates in this new edition include: New coverage of CUDA 5.0, improved performance, enhanced development tools, increased hardware support, and more. Increased coverage of related technology, OpenCL and new material on algorithm patterns, GPU clusters, host programming, and data parallelism. Two new case studies (on MRI reconstruction and molecular visualization) explore the latest applications of CUDA and GPUs for scientific research and high-performance computing.