Open Access

This work integrates two distinct research areas of parallel and distributed computing, (1) automatic loop parallelization, and (2) component-based Grid programming. The latter includes technologies developed within CoreGRID for simplifying Grid programming: the Grid ComponentModel (GCM) and Higher- Order Components (HOCs). Components support developing applications on the Grid without taking all the technical details of the particular platform type into account (network communication, heterogeneity, etc.). The GCMenables a hierarchical composition of programpieces and HOCs enable the reuse of component code in the development of new applications by specifying application-specific operations in a program via code parameters. When a programmer is provided, e. g., with a compute farm HOC, only the independent worker tasks must be described. But, once an application exhibits data or control dependences, the trivial farm is no longer sufficient. Here, the power of loop parallelization tools, like LooPo, comes into play: by embedding LooPo into a HOC, we show that these two technologies in combination facilitate the automatic transformation of a sequential loop nest with complex dependences (supplied by the user as a HOC parameter) into an ordered task graph, which can be processed on the Grid in parallel. This technique can significantly simplify GCM-based systems which combine multiple HOCs and other components. We use an equation system solver based on the successive overrelaxation method (SOR) as our motivating application example and for performance experiments.

Programming GPUs with low-level libraries like CUDA and OpenCL is a tedious and error-prone task. Fortunately, algorithmic skeletons can shield developers from the complexity of parallel programming by encapsulating common parallel computing patterns. However, this simplification typically constrains programmers to write their applications using the GPU library employed by the skeleton implementation. In this work, we combine skeletal programming with modeldriven software development (MDSD) to increase the freedom of choice regarding the employed GPU library instead of leaving all technical decisions to the skeleton implementation. We present a code-generator that transforms models comprising skeletons, their input data and input functions to parallel C++ code while taking care of data-offset calculations. The generator has been tested using different GPU and multi-GPU communication libraries such as Thrust and CUDA-MPI. We demonstrate our novel approach to GPU programming with two example applications: affinity propagation and n-body simulation.

A major challenge in grid computing remains the application software development for this new kind of infrastructure. Grid application programmers have to take into account several complicated aspects: distribution of data and computations, parallel computations on different sites and processors, heterogeneity of the involved computers, load balancing, etc. Grid programmers thus demand novel programming methodologies that abstract over such technical details while preserving the beneficial features of modern grid middleware. For this purpose, the authors introduce Higher-Order Components (HOCs). HOCs implement generic parallel/distributed processing patterns, together with the required middleware support, and they are offered to users via a high-level service interface. Users only have to provide the application-specific pieces of their programs as parameters, while low-level implementation details, such as the transfer of data across the grid, are handled by the HOCs. HOCs were developed within the CoreGRID European Network of Excellence and have become an optional extension of the popular Globus middleware. The book provides the reader with hands-on experience, describing a broad collection of example applications from various fields of science and engineering, including biology, physics, etc. The Java code for these examples is provided online, complementing the book. The expected application performance is studied and reported for extensive performance experiments on different testbeds, including grids with worldwide distribution. The book is targeted at graduate students, advanced professionals, and researchers in both academia and industry. Readers can raise their level of knowledge about methodologies for programming contemporary parallel and distributed systems, and, furthermore, they can gain practical experience in using distributed software. Practical examples show how the complementary online material can easily be adopted in various new projects.

Recent advances in the development of smart homes have led to the availability of a wide variety of devices providing a high level of convenience via gesture and speech control or fully automated operation. Many smart home appliances also address the aspects of safety and electricity savings by automatically powering themselves off after not being used for a while. However, many devices remain in a typical household that are not themselves "smart", or are not primarily electric (such as heating systems). We address the savings aspect by identifying processes involving the use of multiple devices in the electrical flow data, as captured by a smart meter in a modern household, rather than focusing on a single appliance. Therefore, we introduce a novel approach to usage pattern analysis based on the idea that a pattern of device usages as a result of a resident's 'routine' (such as making breakfast) can be interpreted similarly to a natural language 'sentence'; Natural Language Processing (NLP) algorithms can then be used for interpreting the residents' behavior. We introduce the notion of bag-of-devices (BoD), derived from the bag-of-words model used in document classification. In an experiment, we show how we use this model to infer predictions about the inhabitants from device usage, such as the resident leaving for the day or just to fetch the newspaper.

The current efforts on programming grid applications often rely on service-oriented approaches like grid services. This work presents HOC-SA -a service architecture for higher-order components, which provides the programmer with reusable and composable patterns of parallelism and is interoperable with the latest Globus toolkit implementations. We describe our implementation of HOC-SA using OGSA-DAI, a framework for integrating grids with distributed databases. We present a simple example application and report first measurements on our grid testbed.