In this article we present a compile-time algorithm, implemented using C++ template metaprogramming techniques, that minimizes the use of temporary storage when evaluating expressions. We present the basic building blocks of our algorithm---transformations that act locally on nodes of the expression parse tree---and demonstrate that the application of these local transformations generates a (nonunique) expression that requires a minimum number of temporary storage objects to evaluate. We discuss a C++ implementation of our algorithm using expression templates, and give results demonstrating the effectiveness of our approach.

Preparations for exascale computing have led to the realization that computing environments will be significantly different from those that provide petascale capabilities. This change is driven by energy constraints, which has compelled hardware architects to design systems that will require a significant re-thinking of how application algorithms are selected and implemented. The "codesign" principle may offer a common basis for application and system developers as well as architects to work synergistically towards achieving exascale computing. This paper aims to introduce to the embedded system design community the unique challenges and opportunities as well as exciting developments in exascale HPC system codesign. Given the success of adopting codesign practices in the embedded system design area, this effort should be mutually beneficial to both communities.

Abstract Due to the intricate nature of the equation governing light transport in participating media, accurately and efficiently simulating radiative energy transfer remains very challenging in spite of its broad range of applications. As an alternative to traditional numerical estimation methods such as ray‐marching and volume‐slicing, a few analytical approaches to solving single scattering have been proposed but current techniques are limited to the assumption of isotropy, rely on simplifying approximations and/or require substantial numerical precomputation and storage. In this paper, we present the very first closed‐form solution to the air‐light integral in homogeneous media for general 1‐D anisotropic phase functions and punctual light sources. By addressing an open problem in the overall light transport literature, this novel theoretical result enables the analytical computation of exact solutions to complex scattering phenomena while achieving semi‐interactive performance on graphics hardware for several common scattering modes.

The NVIDIA® OptiX™ ray tracing engine is a programmable system designed for NVIDIA GPUs and other highly parallel architectures. The OptiX engine builds on the key observation that most ray tracing algorithms can be implemented using a small set of programmable operations. Consequently, the core of OptiX is a domain-specific just-in-time compiler that generates custom ray tracing kernels by combining user-supplied programs for ray generation, material shading, object intersection, and scene traversal. This enables the implementation of a highly diverse set of ray tracing-based algorithms and applications, including interactive rendering, offline rendering, collision detection systems, artificial intelligence queries, and scientific simulations such as sound propagation. OptiX achieves high performance through a compact object model and application of several ray tracing-specific compiler optimizations. For ease of use it exposes a single-ray programming model with full support for recursion and a dynamic dispatch mechanism similar to virtual function calls.

This paper presents a system deployed on parallel clusters to manage a collection of parallel simulations that make up a computational study. It explores how such a system can extend traditional parallel job scheduling and resource allocation techniques to incorporate knowledge specific to the study.

Abstract Despite their numerous applications, efficiently rendering participating media remains a challenging task due to the intricacy of the radiative transport equation. As they provide a generic means of solving a wide variety of problems, numerical methods are most often used to solve the air‐light integral even under simplifying assumptions. In this paper, we present a novel analytical approach to single scattering from isotropic point light sources in homogeneous media. We derive the first closed‐form solution to the air‐light integral in isotropic media and extend this formulation to anisotropic phase functions. The technique relies neither on pre‐computation nor on storage, and we provide a practical implementation allowing for an explicit control on the accuracy of the solutions. Finally, we demonstrate its quantitative and qualitative benefits over both previous numerical and analytical approaches.

Abstract Ray tracing has long been a method of choice for off‐line rendering, but traditionally was too slow for interactive use. With faster hardware and algorithmic improvements this has recently changed, and real‐time ray tracing is finally within reach. However, real‐time capability also opens up new problems that do not exist in an off‐line environment. In particular real‐time ray tracing offers the opportunity to interactively ray trace moving/animated scene content. This presents a challenge to the data structures that have been developed for ray tracing over the past few decades. Spatial data structures crucial for fast ray tracing must be rebuilt or updated as the scene changes, and this can become a bottleneck for the speed of ray tracing. This bottleneck has recently received much attention by researchers and that has resulted in a multitude of different algorithms, data structures and strategies for handling animated scenes. The effectiveness of techniques for ray tracing dynamic scenes vary dramatically depending on details such as scene complexity, model structure, type of motion and the coherency of the rays. Consequently, there is so far no approach that is best in all cases, and determining the best technique for a particular problem can be a challenge. In this State of the Art Report (STAR), we aim to survey the different approaches to ray tracing animated scenes, discussing their strengths and weaknesses, and their relationship to other approaches. The overall goal is to help the reader choose the best approach depending on the situation, and to expose promising areas where there is potential for algorithmic improvements.

This paper presents a system supporting reuse of simulation results in multi-experiment computational studies involving independent simulations and explores the benefits of such reuse. Using a SCIRun-based defibrillator device simulation code (DefibSim) and the SimX system for computational studies, this paper demonstrates how aggressive reuse between and within computational studies can enable interactive rates for such studies on a moderate-sized 128-node processor cluster; a brute-force approach to the problem would require two thousand nodes or more on a massively parallel machine for similar performance. Key to realizing these performance improvements is exploiting optimization opportunities that present themselves at the level of the overall workflow of the study as opposed to focusing on individual simulations. Such global optimization approaches are likely to become increasingly important with the shift towards interactive and universal parallel computing.

Abstract We present the Memory Trace Visualizer (MTV), a tool that provides interactive visualization and analysis of the sequence of memory operations performed by a program as it runs. As improvements in processor performance continue to outpace improvements in memory performance, tools to understand memory access patterns are increasingly important for optimizing data intensive programs such as those found in scientific computing. Using visual representations of abstract data structures, a simulated cache, and animating memory operations, MTV can expose memory performance bottlenecks and guide programmers toward memory system optimization opportunities. Visualization of detailed memory operations provides a powerful and intuitive way to expose patterns and discover bottlenecks, and is an important addition to existing statistical performance measurements.

Abstract This paper presents a novel method that effectively combines both control variates and importance sampling in a sequential Monte Carlo context. The radiance estimates computed during the rendering process are cached in a 5D adaptive hierarchical structure that defines dynamic predicate functions for both variance reduction techniques and guarantees well‐behaved PDFs, yielding continually increasing efficiencies thanks to a marginal computational overhead. While remaining unbiased, the technique is effective within a single pass as both estimation and caching are done online, exploiting the coherency in illumination while being independent of the actual scene representation. The method is relatively easy to implement and to tune via a single parameter, and we demonstrate its practical benefits with important gains in convergence rate and competitive results with state of the art techniques.

No abstract available.

We present an approach to visualizing particle-based simulation data using interactive ray tracing and describe an algorithmic enhancement that exploits the properties of these data sets to provide highly interactive performance and reduced storage requirements. This algorithm for fast packet-based ray tracing of multilevel grids enables the interactive visualization of large time-varying data sets with millions of particles and incorporates advanced features like soft shadows. We compare the performance of our approach with two recent particle visualization systems: one based on an optimized single ray grid traversal algorithm and the other on programmable graphics hardware. This comparison demonstrates that the new algorithm offers an attractive alternative for interactive particle visualization.

The Material Point Method is used for complex simulation of solid materials represented using many individual particles. Visualizing such data using existing polygonal or volumetric methods does not accurately encapsulate both the particle and macroscopic properties of the data. In this case study we present various methods used to visualize the particle data as spheres and explain and evaluate two methods of augmenting the visualization using silhouette edges and advanced illumination such as ambient occlusion.We also present informal feedback received from the application scientists who use these methods in their workflow.

Abstract The Common Component Architecture (CCA) is a component model for high‐performance computing, developed by a grass‐roots effort of computational scientists. Although the CCA is usable with CORBA‐like distributed‐object components, its main purpose is to set forth a component model for high‐performance, parallel computing. Traditional component models are not well suited for performance and massive parallelism. We outline the design pattern for the CCA component model, discuss our strategy for language interoperability, describe the development tools we provide, and walk through an illustrative example using these tools. Performance and scalability, which are distinguishing features of CCA components, affect choices throughout design and implementation. Copyright © 2005 John Wiley & Sons, Ltd.

We present a new approach to interactive ray tracing of moderate-sized animated scenes based on traversing frustum-bounded packets of coherent rays through uniform grids. By incrementally computing the overlap of the frustum with a slice of grid cells, we accelerate grid traversal by more than a factor of 10, and achieve ray tracing performance competitive with the fastest known packet-based kd-tree ray tracers. The ability to efficiently rebuild the grid on every frame enables this performance even for fully dynamic scenes that typically challenge interactive ray tracing systems.

In many applications, volumetric data sets are examined by displaying isosurfaces, surfaces where the data, or some function of the data, takes on a given value. Interactive applications typically use local lighting models to render such surfaces. This work introduces a method to precompute or lazily compute global illumination to improve interactive isosurface renderings. The precomputed illumination resides in a separate volume and includes direct light, shadows, and interreflections. Using this volume, interactive globally illuminated renderings of isosurfaces become feasible while still allowing dynamic manipulation of lighting, viewpoint and isovalue.

We present an overview of the SCIRun2 parallel component framework. SCIRun2 is based on the common component architecture (CCA) as stated by R. Armstrong et al. (1999) and the SCI Institutes' SCIRun by C. Johnson and S. Parker (1999). SCIRun2 supports distributed computing through distributed objects. Parallel components are managed transparently over an M/spl times/N method invocation and data redistribution subsystem. A meta component model based on CCA is used to accommodate multiple component models such as CCA, CORBA and Dataflow. A group of monitoring components built on top of the TAU toolkit as stated in Advanced Computing Laboratory (1999) evaluate the performance of the other components.

The scientific visualization community faces a crisis: there exist many individual tools that can be used to perform visualization, but there is little, if any, hope of being able to use tools from different sources as part of a single application. As a result, our community is fractured, and can be characterized as "islands of capability." The purpose of this panel is to probe the issues that prevent such interoperability, and engage in frank discussion about how our community can rectify these maladies. The issues to be discussed include but are not limited to: (1)lack of "standards" for data storage and modelling of N-dimensional scientific data, similar to those used for raster image files; (2)lack of "standard" interfaces for common visualization tools; (3)the visualization needs of the computational science research community, who are the primary consumers of technology from the visualization community; (4)lack of organization within our community to push for definition and adoption of such "standards;" (5)lack of organization within our community to serve as a "broker" and "promoter" for tools that might conform to even the weakest of standards. The panelist lineup represents a diverse cross-section of expertise and opinions about the panel topic. The panelists themselves are in disagreement about the severity of the problem, and potential solutions. The topic of this panel is highly germane to future growth of visualization as a science, and promises to be highly engaging for panelists and audience members alike.

Abstract In this paper we discuss three scientific computing problem solving environments: SCIRun, BioPSE, and Uintah. We begin with an overview of the systems, describe their underlying software architectures, discuss implementation issues, and give examples of their use in computational science and engineering applications. We conclude by discussing future research and development plans for the three problem solving environments. Copyright © 2002 John Wiley & Sons, Ltd.

Describes Uintah, a component-based visual problem-solving environment (PSE) that is designed to specifically address the unique problems of massively parallel computation on tera-scale computing platforms. Uintah supports the entire life-cycle of scientific applications by allowing scientific programmers to quickly and easily develop new techniques, debug new implementations and apply known algorithms to solve novel problems. Uintah is built on three principles: (1) as much as possible, the complexities of parallel execution should be handled for the scientist, (2) the software should be reusable at the component level, and (3) scientists should be able to dynamically steer and visualize their simulation results as the simulation executes. To provide this functionality, Uintah builds upon the best features of the SCIRun (Scientific Computing and Imaging Run-time) PSE and the DoE (Department of Energy) Common Component Architecture (CCA).

Describes work in progress to develop a standard for interoperability among high-performance scientific components. This research stems from the growing recognition that the scientific community needs to better manage the complexity of multidisciplinary simulations and better address scalable performance issues on parallel and distributed architectures. The driving force for this is the need for fast connections among components that perform numerically intensive work and for parallel collective interactions among components that use multiple processes or threads. This paper focuses on the areas we believe are most crucial in this context, namely an interface definition language that supports scientific abstractions for specifying component interfaces and a port connection model for specifying component interactions.

this paper, we present interactive volume visualization schemes that use ray tracing as their basic computation method

Presents a brute-force ray-tracing system for interactive volume visualization. The system runs on a conventional (distributed) shared-memory multiprocessor machine. For each pixel, we trace a ray through a volume to compute the color for that pixel. Although this method has a high intrinsic computational cost, its simplicity and scalability make it ideal for large data sets on current high-end parallel systems. To gain efficiency, several optimizations are used, including a volume bricking scheme and a shallow data hierarchy. These optimizations are used in three separate visualization algorithms: isosurfacing of rectilinear data, isosurfacing of unstructured data, and maximum-intensity projection on rectilinear data. The system runs interactively (i.e. at several frames per second) on an SGI Reality Monster. The graphics capabilities of the Reality Monster are used only for display of the final color image.

Building systems that alter program behavior during execution based on user-specified criteria (computational steering systems) has been a recent research topic, particularly among the high performance computing community. To enable a computational steering system with powerful visualization capabilities to run on distributed memory architectures, a distributed infrastructure (or runtime system) must first be built. This infrastructure would permit harnessing a variety of machines to collaborate on an interactive simulation. Building such an infrastructure requires strategies for coordinating execution across machines (concurrency control mechanisms), mechanisms for fast data transfer between machines, and mechanisms for user manipulation of remote execution. We are creating a distributed infrastructure for the SCIRun computational steering system. SCIRun, a scientific problem solving environment (PSE), provides the ability to interactively guide or steer a running computation. Initially designed for a shared memory multiprocessor, SCIRun is a tightly integrated, multi-threaded framework for composing scientific applications from existing or new components. High performance computing is needed to maintain interactivity for scientists and engineers running simulations. Extending such a performance-sensitive application toolkit to enable pieces of the computation to run on different machine architectures all within the same computation would prove very useful. Not only could many different machines execute this framework, but also several machines could be configured to work synergistically on computations.

We show that it is feasible to perform interactive isosurfacing of very large rectilinear datasets with brute-force ray tracing on a conventional (distributed) shared-memory multiprocessor machine. Rather than generate geometry representing the isosurface and render with a z-buffer, for each pixel we trace a ray through a volume and do an analytic isosurface intersection computation. Although this method has a high intrinsic computational cost, its simplicity and scalability make it ideal for large datasets on current high-end systems. Incorporating simple optimizations, such as volume bricking and a shallow hierarchy, enables interactive rendering (i.e. 10 frames per second) of the 1 GByte full resolution Visible Woman dataset on an SGI Reality Monster. The graphics capabilities of the Reality Monster are used only for display of the final color image.

We present the design, implementation and application of SCIRun, a scientific programming environment that allows the interactive construction, debugging and steering of large scale scientific computations. Using this "computational workbench," a scientist can design and modify simulations interactively via a dataflow programming model. SCIRun enables scientists to design and modify models and automatically change parameters and boundary conditions as well as the mesh discretization level needed for an accurate numerical solution. As opposed to the typical "off-line" simulation mode - in which the scientist manually sets input parameters, computes results, visualizes the results via a separate visualization package, then starts again at the beginning - SCIRun "closes the loop" and allows interactive steering of the design and computation phases of the simulation. To make the dataflow programming paradigm applicable to large scientific problems, we have identified ways to avoid the excessive memory use inherent in standard dataflow implementations, and have implemented fine-grained dataflow in order to further promote computational efficiency. In this paper, we describe applications of the SCIRun system to several problems in computational medicine. In addition, an we have included an interactive demo program in the form of an application of SCIRun system to a small electrostatic field problem.

We describe a computational steering model which allows users to interactively change boundary conditions, model geometry, and computational parameters via a graphical user interface. To replace the typical simulation mode-in which the researcher manually sets input parameters, computes results, stores data off to disk, visualizes the results via a separate visualization package, then starts again at the beginning-we have designed software to "close the loop" and allow the visualization to help guide (steer) the design and computation phases of the simulation. We have applied the computational steering model to problems in medicine, specifically to applications in bioelectric field phenomena and biomedical device design.>