Inviwo -- A Visualization System with Usage Abstraction Levels

The complexity of today's visualization applications demands specific visualization systems tailored for the development of these applications. Frequently, such systems utilize levels of abstraction to improve the application development process, for instance by providing a data flow network editor. Unfortunately, these abstractions result in several issues, which need to be circumvented through an abstraction-centered system design. Often, a high level of abstraction hides low level details, which makes it difficult to directly access the underlying computing platform, which would be important to achieve an optimal performance. Therefore, we propose a layer structure developed for modern and sustainable visualization systems allowing developers to interact with all contained abstraction levels. We refer to this interaction capabilities as usage abstraction levels, since we target application developers with various levels of experience. We formulate the requirements for such a system, derive the desired architecture, and present how the concepts have been exemplary realized within the Inviwo visualization system. Furthermore, we address several specific challenges that arise during the realization of such a layered architecture, such as communication between different computing platforms, performance centered encapsulation, as well as layer-independent development by supporting cross layer documentation and debugging capabilities

Astrophysical Supercomputing with GPUs: Critical Decisions for Early Adopters

General purpose computing on graphics processing units (GPGPU) is dramatically changing the landscape of high performance computing in astronomy. In this paper, we identify and investigate several key decision areas, with a goal of simplyfing the early adoption of GPGPU in astronomy. We consider the merits of OpenCL as an open standard in order to reduce risks associated with coding in a native, vendor-specific programming environment, and present a GPU programming philosophy based on using brute force solutions. We assert that effective use of new GPU-based supercomputing facilities will require a change in approach from astronomers. This will likely include improved programming training, an increased need for software development best-practice through the use of profiling and related optimisation tools, and a greater reliance on third-party code libraries. As with any new technology, those willing to take the risks, and make the investment of time and effort to become early adopters of GPGPU in astronomy, stand to reap great benefits.Comment: 13 pages, 5 figures, accepted for publication in PAS

Parallel Programming Recipes

Parallel programming has become vital for the success of commercial applications since Moore’s Law will now be used to double the processors (or cores) per chip every technology generation. The performance of applications depends on how software executions can be mapped on the multi-core chip, and how efficiently they run the cores. Currently, the increase of parallelism in software development is necessary, not only for taking advantage of multi-core capability, but also for adapting and surviving in the new silicon implementation. This project will provide the performance characteristics of parallelism for some common algorithms or computations using different parallel languages. Based on concrete experiments, where each algorithm is implemented on different languages and the program’s performance is measured, the project provides the recipes for the problem computations. The following are the central problems and algorithms of the project: Arithmetic Algebra: Maclaurin Series Calculation for ex, Dot-Product of Two Vectors: each vector has size n; Sort Algorithms: Bubble sort, Odd-Event sort; Graphics: Graphics rendering. The languages are chosen based on commonality in the current market and ease of use; i.e., OpenMP, MPI, and OpenCL. The purpose of this study is to provide reader a broad knowledge about parallel programming, the comparisons, in terms of performance and implementation cost, across languages and application types. It is hoped to be very useful for programmers/computer-architects to decide which language to use for a certain applications/problems and cost estimations for the projects. Also, it is hoped that the project can be expanded in the future so that more languages/technologies as well as applications can be analyze

A pilgrimage to gravity on GPUs

In this short review we present the developments over the last 5 decades that have led to the use of Graphics Processing Units (GPUs) for astrophysical simulations. Since the introduction of NVIDIA's Compute Unified Device Architecture (CUDA) in 2007 the GPU has become a valuable tool for N-body simulations and is so popular these days that almost all papers about high precision N-body simulations use methods that are accelerated by GPUs. With the GPU hardware becoming more advanced and being used for more advanced algorithms like gravitational tree-codes we see a bright future for GPU like hardware in computational astrophysics.Comment: To appear in: European Physical Journal "Special Topics" : "Computer Simulations on Graphics Processing Units" . 18 pages, 8 figure

PARALLEL √3-SUBDIVISION with ANIMATION in CONSIDERATION of GEOMETRIC COMPLEXITY

We look at the broader field of geometric subdivision and the emerging field of parallel computing for the purpose of creating higher visual fidelity at an efficient pace. Primarily, we present a parallel algorithm for √3-Subdivision. When considering animation, we find that it is possible to do subdivision by providing only one variable input, with the rest being considered static. This reduces the amount of data transfer required to continually update a subdividing mesh. We can support recursive subdivision by applying the technique in passes. As a basis for analysis, we look at performance in an OpenCL implementation that utilizes a local graphics processing unit (GPU) and a parallel CPU. By overcoming current hardware limitations, we present an environment where general GPU computation of √3-Subdivision can be practical

GPGPU-Enabled Physics Based Deformed Model Simulation

Computer simulation techniques are widely adopted nowadays in many areas like manufacturing, engineering, graphics, animation, virtual reality and so on. However, the standard finite element based simulation is notorious for its expensive computation. To address this challenge, I present a GPU-based parallel implementation for simulating large elastic deformation. Classic modal analysis provides a set of orthonormal bases vectors, which span a spectral space encoding the dynamics of the elastic body. As each basis vector is orthogonal to each other, the computation is completely decoupled and can be well-fit into the modern GPGPU platform. We further explore the latest feature of NVIDIA CUDA so that the result of GPU computation can be directly used for upcoming rendering/visualization and a significant amount of overheads for transmitting data from client GPU and host CPU via the PCI-Express bus are avoided. Real-time simulation is made possible with this technique for many cases that otherwise is not possible