Cactus: Issues for Sustainable Simulation Software

The Cactus Framework is an open-source, modular, portable programming environment for the collaborative development and deployment of scientific applications using high-performance computing. Its roots reach back to 1996 at the National Center for Supercomputer Applications and the Albert Einstein Institute in Germany, where its development jumpstarted. Since then, the Cactus framework has witnessed major changes in hardware infrastructure as well as its own community. This paper describes its endurance through these past changes and, drawing upon lessons from its past, also discusses futureComment: submitted to the Workshop on Sustainable Software for Science: Practice and Experiences 201

A Massive Data Parallel Computational Framework for Petascale/Exascale Hybrid Computer Systems

Heterogeneous systems are becoming more common on High Performance Computing (HPC) systems. Even using tools like CUDA and OpenCL it is a non-trivial task to obtain optimal performance on the GPU. Approaches to simplifying this task include Merge (a library based framework for heterogeneous multi-core systems), Zippy (a framework for parallel execution of codes on multiple GPUs), BSGP (a new programming language for general purpose computation on the GPU) and CUDA-lite (an enhancement to CUDA that transforms code based on annotations). In addition, efforts are underway to improve compiler tools for automatic parallelization and optimization of affine loop nests for GPUs and for automatic translation of OpenMP parallelized codes to CUDA. In this paper we present an alternative approach: a new computational framework for the development of massively data parallel scientific codes applications suitable for use on such petascale/exascale hybrid systems built upon the highly scalable Cactus framework. As the first non-trivial demonstration of its usefulness, we successfully developed a new 3D CFD code that achieves improved performance.Comment: Parallel Computing 2011 (ParCo2011), 30 August -- 2 September 2011, Ghent, Belgiu

Research and Education in Computational Science and Engineering

Over the past two decades the field of computational science and engineering (CSE) has penetrated both basic and applied research in academia, industry, and laboratories to advance discovery, optimize systems, support decision-makers, and educate the scientific and engineering workforce. Informed by centuries of theory and experiment, CSE performs computational experiments to answer questions that neither theory nor experiment alone is equipped to answer. CSE provides scientists and engineers of all persuasions with algorithmic inventions and software systems that transcend disciplines and scales. Carried on a wave of digital technology, CSE brings the power of parallelism to bear on troves of data. Mathematics-based advanced computing has become a prevalent means of discovery and innovation in essentially all areas of science, engineering, technology, and society; and the CSE community is at the core of this transformation. However, a combination of disruptive developments---including the architectural complexity of extreme-scale computing, the data revolution that engulfs the planet, and the specialization required to follow the applications to new frontiers---is redefining the scope and reach of the CSE endeavor. This report describes the rapid expansion of CSE and the challenges to sustaining its bold advances. The report also presents strategies and directions for CSE research and education for the next decade.Comment: Major revision, to appear in SIAM Revie

Investigation of High Pressure Fluid Circuit Gas Flow Dynamics in a Hermetic Compressor Using CFD to Improve Qualitative Flow Understanding

While many approaches have been investigated to identify areas for hermetic compressor efficiency improvements over the past few decades, there remains no conclusive method to gain a holistic view of the system domain to help identify potential target areas to guide product research direction. Hence, modern tools, methods, and problem perspectives are needed to develop new insight into mature problem-sets on a system level to satisfy increasingly stringent efficiency mandates. Reasonably mature simulation tools currently exist that enable scientists and engineers to gain a new perspective into system domains. One such tool is Computational Fluid Dynamics (CFD). The results of the following investigation will show how CFD, coupled with the knowledge of its inherent strengths and weaknesses, can be leveraged to allow scientists and engineers to view mature problem-sets from a qualitative perspective to yield different results by using the high-pressure fluid circuit of a hermetic compression system as a simulation test-bed

CAVE 3D: Software Extensions for Scientific Visualization of Large-scale Models

AbstractNumerical analysis of large-scale and multidisciplinary problems on high-performance computer systems is one of the main computational challenges of the 21st century. The amount of data processed in complex systems analyses approaches peta- and exascale. The technical possibility for real-time visualization, post-processing and analysis of large-scale models is extremely important for carrying out comprehensive numerical studies. Powerful visualization is going to play an important role in the future of large-scale models. In this paper, we describe several software extensions aimed to improve visualization performance for large-scale models and developed by our team for 3D virtual environment systems such as CAVEs and Powerwalls. These extensions include an algorithm for real-time generation of isosurfaces on large meshes and a visualization system designed for massively parallel computing environment. Besides, we describe an augmented reality system developed by the part of our team in Stuttgart