AP/Linux - initial implementation

The AP1000+ is a distributed-memory parallel computer based on SuperSPARC processors, which incorporates message-passing hardware which can be accessed safely from user mode. We are in the process of porting the Linux kernel to this machine and extending it to support execution of parallel programs. This report outlines the motivation and background of this effort, and describes the current status and future directions for the work. The reader may also refer to our WWW page at http://cap.anu.edu.au/cap/projects/linux for up to date information on the progress of the port

The impact of iodine supplementation and bread fortification on urinary iodine concentrations in a mildly iodine deficient population of pregnant women in South Australia

Mild iodine deficiency during pregnancy can have significant effects on fetal development and future cognitive function. The purpose of this study was to characterise the iodine status of South Australian women during pregnancy and relate it to the use of iodine-containing multivitamins. The impact of fortification of bread with iodized salt was also assessed. Women (n = 196) were recruited prospectively at the beginning of pregnancy and urine collected at 12, 18, 30, 36 weeks gestation and 6 months postpartum. The use of a multivitamin supplement was recorded at each visit. Spot urinary iodine concentrations (UIC) were assessed. Median UICs were within the mildly deficient range in women not taking supplements (<90 μg/L). Among the women taking iodine-containing multivitamins UICs were within WHO recommendations (150–249 μg/L) for sufficiency and showed an increasing trend through gestation. The fortification of bread with iodized salt increased the median UIC from 68 μg/L to 84 μg/L (p = .011) which was still in the deficient range. Pregnant women in this region of Australia were unlikely to reach recommended iodine levels without an iodine supplement, even after the mandatory iodine supplementation of bread was instituted in October 2009.Vicki L Clifton, Nicolette A Hodyl, Paul A Fogarty, David J Torpy, Rachel Roberts, Ted Nettelbeck, Gary Ma and Basil Hetze

A Fast Parallel Marching-Cubes Implementation on the Fujitsu AP1000

Parallel computers hold the promise of enabling interactive visualization of very large data sets. Fulfilling this promise depends on the development of parallel algorithms and implementations which can efficiently utilize the power of a parallel computer. Fortunately, many visualization algorithms involve performing independent computations on a large collection of data items, making them particularly suitable for parallelization. This report describes a high-performance implementation of the Marching Cubes isosurface algorithm on the Fujitsu AP1000, based on a fast serial Marching Cubes implementation. On a 128-processor AP1000, our implementation can generate an isosurface for a volume of reasonable size (e.g. 2.6 million data points) in typically less than 0.5 seconds (depending on the number of polygons generated). The Fujitsu AP1000 is an experimental large-scale MIMD (multiple-instruction, multiple data) parallel computer, composed of between 64 and 1024 processing cells connect..

A fast parallel marching-cubes implementation on the Fujitsu AP1000

Parallel computers hold the promise of enabling interactive visualization of very large data sets. Fulfilling this promise depends on the development of parallel algorithms and implementations which can efficiently utilize the power of a parallel computer. Fortunately, many visualization algorithms involve performing independent computations on a large collection of data items, making them particularly suitable for parallelization. This report describes a high-performance implementation of the Marching Cubes isosurface algorithm on the Fujitsu AP1000, based on a fast serial Marching Cubes implementation. On a 128-processor AP1000, our implementation can generate an isosurface for a volume of reasonable size (e.g. 2.6 million data points) in typically less than 0.5 seconds (depending on the number of polygons generated). The Fujitsu AP1000 is an experimental large-scale MIMD (multiple-instruction, multiple data) parallel computer, composed of between 64 and 1024 processing cells connected by three high bandwidth, low latency communications networks. Each processing cell is a SPARC processor with 16MB of memory. The cell processors do not share memory. Our experience indicates that the Marching Cubes algorithm parallelizes well; in fact the speedup we obtain is actually greater than the number of processors (presumably due to cache effects). However, it is necessary to perform any further processing of the generated surface (such as rendering, or evaluation of connected volumes) in parallel if massive slowdowns are to be avoided

Parallel Volume Rendering and Data Coherence on the Fujitsu AP1000

Many scientific and engineering disciplines, through physical measurements or computational simulations, generate large scale three-dimensional data sets. Both the physical size and the computational resources needed to render these data sets present a challenge to current rendering architectures and techniques. The Fujitsu AP1000 has the memory capacity and the processing speed to render large three-dimensional data sets at interactive or near-interactive speeds. A parallel version of a volume renderer has been implemented using a ray-casting technique on this architecture. The two key issues in implementing this technique on a distributed memory, MIMD machine such as the AP1000 are the work and data distribution. To perform the data distribution, a distributed virtual memory for volume data is used. The importance of utilizing the data coherence that is inherent in volume data is demonstrated through the analysis of several case studies. 1 Introduction Many scientific and engineerin..

Data Shader Language and Interface Specification

The process of visualizing a scientific data set benefits from an extensive knowledge of the domain in which the data set is created. Because an in-depth knowledge of all scientific domains is not available to the creator of a visualization system, a flexible and extensible system is essential in providing a productive tool to the scientist. One approach to providing this flexibility is through a shading language that enables users to write programmable data shaders that determine how scientific data sets are rendered. This paper describes the implementation of such a shading system. The system consists of two parts, a shader library and a shader compiler. The shader library does not provide a shading model directly, but instead provides a means of loading and binding externally created shaders to a rendering engine which uses the library. The shader compiler is used to compile a shader description, written in the shading language, into a form that the shader library can load. The shad..

Data shader language and interface specification

The process of visualizing a scientific data set benefits from an extensive knowledge of the domain in which the data set is created. Because an in-depth knowledge of all scientific domains is not available to the creator of a visualization system, a exible and extensible system is essential in providing a productive tool to the scientist. One approach to providing this exibility is through a shading language that enables users to write programmable data shaders that determine how scientific data sets are rendered. This paper describes the implementation of such a shading system. The system consists of two parts, a shader library and a shader compiler. The shader library does not provide a shading model directly, but instead provides a means of loading and binding externally created shaders to a rendering engine which uses the library. The shader compiler is used to compile a shader description, written in the shading language, into a form that the shader library can load. The shader library has been used in both a ray-tracing geometric renderer and a ray-casting volume renderer

The Faculties

The process of visualizing a scientific data set benefits from an extensive knowledge of the domain in which the data set is created. Because an in-depth knowledge of all scientific domains is not available to the creator of a visualization system, a flexible and extensible system is essential in providing a productive tool to the scientist. One approach to providing this flexibility is through a shading language that enables users to write programmable data shaders that determine how scientific data sets are rendered. This paper describes the implementation of such a shading system. The system consists of two parts, a shader library and a shader compiler. The shader library does not provide a shading model directly, but instead provides a means of loading and binding externally created shaders to a rendering engine which uses the library. The shader compiler is used to compile a shader description, written in the shading language, into a form that the shader library can load. The shad..

The rsync algorithm

This report presents an algorithm for updating a file on one machine to be identical to a file on another machine. We assume that the two machines are connected by a low-bandwidth high-latency bi-directional communications link. The algorithm identifies parts of the source file which are identical to some part of the destination file, and only sends those parts which cannot be matched in this way. Effectively, the algorithm computes a set of differences without having both files on the same machine. The algorithm works best when the files are similar, but will also function correctly and reasonably efficiently when the files are quite different