As massively parallel, distributed memory systems replace traditional vector supercomputers, effective application program optimization and system resource management become more than research curiosities --- they are crucial to achieving substantial fractions of peak performance for scientific application codes. By recording dynamic activity, either at the application or system software level, one can identify and remove performance bottlenecks. Pablo is a performance analysis environment designed to provide performance data capture, analysis, and presentation across a wide variety of scalable parallel systems. The Pablo environment includes software performance instrumentation, graphical performance data reduction and analysis, and support for mapping performance data to both graphics and sound. Current research directions include complete performance data immersion via head-mounted displays and the integration of Pablo with data parallel Fortran compilers based on the emerging High ...

In computer graphics, rendering is the process by which an abstract description of a scene is converted to an image. When the scene is complex, or when high-quality images or high frame rates are required, the rendering process becomes computationally demanding. To provide the necessary levels of performance, parallel computing techniques must be brought to bear. Although parallelism has been exploited in computer graphics since the early days of the field, its initial use was primarily in specialized applications. The VLSI revolution of the late 1970Õs and the advent of scalable parallel computers during the late 1980Õs changed this situation. Today, parallel hardware is routinely used in graphics workstations, and numerous software-based rendering systems have been developed for general-purpose parallel architectures. This article provides a broad introduction to the subject of parallel rendering, encompassing both hardware and software systems. The focus is on the underlying concepts and the issues which arise in the design of parallel rendering algorithms and systems. We examine the different types of parallelism and how they can be applied in rendering applications. Concepts from parallel computing, such as data decomposition, task granularity, scalability, and load balancing, are considered in relation to the rendering

Performance is a critical issue in current massively parallel processors. However, delivery of adequate performance is not automatic and performance evaluation tools are required in order to help the programmer to understand the behaviour of a parallel program. In recent years, a wide variety of tools have been developed for this purpose including tools for monitoring and evaluating performance and visualization tools. However, these tools do not provide an abstract representation of performance. Massively parallel processors can generate a huge amount of performance data and sophisticated methods for representing and displaying this data (e.g. visual and aural) are required. Current performance views are not scalable in general and do not represent an abstraction of the pe...

The Parallel Virtual Machine (PVM) tool has been used for a distributed implementation of Greg Ward’s Radiance code. In order to generate exactly the same primary rays with both the sequential and the parallel codes, the quincunx sampling technique used in Radiance for the reduction of the number of primary rays by interpolation, must be left untouched in the parallel implementation. The octree of local ambient values used in Radiance for the indirect illumination has been shared among all the processors. Both static and dynamic image partitioning techniques which replicate the octree of the complete scene in all the processors and have load-balancing, have been developed for one frame rendering. Speedups larger than 7.5 have been achieved in a network of 8 workstations. For animation sequences, a new dynamic partitioning distribution technique with superlinear speedups has also been developed.