Progressive and approximate techniques are proposed here for ray-tracing systems used to predict radio propagation. In a progressive prediction system, intermediate prediction results are fed back to users continuously. As more raypaths are processed, the accuracy of prediction results improves progressively. We consider how to construct a progressive system that satisfies the requirements of continuous observability and controllability as well as faithfulness and fairness. Adding a workload estimator to such a progressive prediction system allows termination of the computation when a desired accuracy (mean and standard deviation of the error) is achieved without knowing the final result that would be obtained if the prediction system runs to completion. The sample generator is at the core of the progressive prediction system and serves to cluster and prioritize raypaths according to their expected contributions to prediction results. Two types of progressive approaches, source-group-raypath-permute and raypath-interleave, are proposed. The workload estimator determines the number of raypaths to be processed to achieve the specified requirement on prediction accuracy. Two approximate models are described that adjust the workload dynamically during the prediction process. Our experiments show that the proposed progressive and approximate methods provide flexible mechanisms to trade prediction accuracy for prediction time in a relatively fine granularity.

/pdf/progressive-and-approximate-techniques-in-ray-tracing-based-53i1oe35hz.pdf

Progressive and approximate techniques in ray-tracing-based radio wave propagation prediction models

http://cgi.di.uoa.gr/~ad/Publications/JPDC04-ChenDelisBertoni.pdf

Radio-wave propagation prediction using ray-tracing techniques on a network of workstations (NOW)

In this paper, a global optimization technique is applied to solve the optimal transmitter placement problem for indoor wireless systems. An efficient pattern, search algorithm--DIRECT (DIviding RECTangles) of Jones, Perttunen, and Stuckman (1993)--has been connected to a parallel 3D radio propagation ray tracing modeler running on a 200-node Beowulf cluster of Linux workstations. Surrogate functions for a parallel WCDMA (wideband code division multiple access) simulator were used to estimate the system performance for the global optimization algorithm. Power coverage and BER (bit error rate) are considered as two different criteria for optimizing locations of a specified number of transmitters across the feasible region of the design space. This paper briefly describes the underlying radio propagation and WCDMA simulations and focuses on the design issues of the optimization loop.

/pdf/s-sup-4-w-globally-optimized-design-of-wireless-22kimx9rba.pdf

S/sup 4/W: globally optimized design of wireless communication systems

This paper presents the design and performance of a new parallel graphics renderer for 3D images. This renderer is based on an adaptive supersampling approach that works for time/space-efficient execution on two classes of parallel computers. Our rendering scheme takes subpixel supersamples only along polygon edges. This leads to a significant reduction in rendering time and in buffer memory requirements. Furthermore, we offer a balanced rasterization of all transformed polygons. Experimental results prove these advantages on both a shared-memory SGI multiprocessor server and a Unix cluster of Sun workstations. We reveal performance effects of the new rendering scheme on subpixel resolution, polygon number, scene complexity, and memory requirements. The balanced parallel renderer demonstrates scalable performance with respect to increase in graphic complexity and in machine size. Our parallel renderer outperforms Crow's scheme in benchmark experiments performed. The improvements are made in three fronts: (1) reduction in rendering time, (2) higher efficiency with balanced workload,: and (3) adaptive to available buffer memory size. The balanced renderer can be more cost-effectively embedded within many 3D graphics algorithms, such as those for edge smoothing and 3D visualization. Our parallel renderer is MPI-coded, offering high portability and cross-platform performance. These advantages can greatly improve the QoS in 3D imaging and in real-time interactive graphics.

Adaptive parallel rendering on multiprocessors and workstation clusters

Grid computing, a form of distributed computing, has become a hot topic recently. Currently, there are many ways in which Grids are being used in order to enhance existing IT infrastructure to better utilize distributed resources and data. Grid technology is considered to be a very powerful solution to the problem of sharing heterogeneous resources including compute resources, data stores, and different kinds of services provided by various entities. In this paper, we look at applications that make, or could make, good use of a distributed computing environment, such as a Grid. We provide some background on a selected application, the POV-Ray ray tracer, and investigate how it can benefit from running on a Grid. We use the Gridbus Resource Broker for scheduling application tasks on a Global Grid.

Multimedia on global grids: a case study in distributed ray tracing

A case study is presented which is aimed at investigating the performance of several parallel versions of the POV-Ray ray-tracing package implemented on a workstation cluster using the MPI message-passing library. Based on a manager/worker scheme, variants of workload partitioning and message scheduling strategies, in conjunction with different task granularities, are evaluated with respect to their runtime behaviour. The results indicate that dynamic, adaptive strategies are required to cope with both the unbalanced workload characteristics of the parallel ray-tracing application and the different computational capabilities of the machines in a workstation cluster environment.

Parallel raytracing: a case study on partitioning and scheduling on workstation clusters

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Parallel raytracing: a case study on partitioning and scheduling on workstation clusters