Constantinos Ierotheou

The parawise expert assistant – widening accessibility to efficient and scalable tool generated OpenMP code

Despite the apparent simplicity of the OpenMP directive shared memory programming model and the sophisticated dependence analysis and code generation capabilities of the ParaWise/CAPO tools, experience shows that a level of expertise is required to produce efficient parallel code. In a real world application the investigation of a single loop in a generated parallel code can soon become an in-depth inspection of numerous dependencies in many routines. The additional understanding of dependencies is also needed to effectively interpret the information provided and supply the required feedback. The ParaWise Expert Assistant has been developed to automate this investigation and present questions to the user about, and in the context of, their application code. In this paper, we demonstrate that knowledge of dependence information and OpenMP are no longer essential to produce efficient parallel code with the Expert Assistant. It is hoped that this will enable a far wider audience to use the tools and subsequently, exploit the benefits of large parallel systems.

Parallel bandwidth characteristics calculations for thin avalanche photodiodes on a SGI Origin 2000 supercomputer

An important factor for high‐speed optical communication is the availability of ultrafast and low‐noise photodetectors. Among the semiconductor photodetectors that are commonly used in todays long‐haul and metro‐area fiber‐optic systems, avalanche photodiodes (APDs) are often preferred over p‐i‐n photodiodes due to their internal gain, which significantly improves the receiver sensitivity and alleviates the need for optical pre‐amplification. Unfortunately, the random nature of the very process of carrier impact ionization, which generates the gain, is inherently noisy and results in fluctuations not only in the gain but also in the time response. Recently, a theory characterizing the autocorrelation function of APDs has been developed by us which incorporates the dead‐space effect, an effect that is very significant in thin, high‐performance APDs. The research extends the time‐domain analysis of the dead‐space multiplication model to compute the autocorrelation function of the APD impulse response. However, the computation requires a large amount of memory space and is very time consuming. In this research, we describe our experiences in parallelizing the code in MPI and OpenMP using CAPTools. Several array partitioning schemes and scheduling policies are implemented and tested. Our results show that the code is scalable up to 64 processors on a SGI Origin 2000 machine and has small average errors. Copyright

Nested parallelization of the flow solver TFS using the ParaWise parallelization environment

The Navier-Stokes Solver TFS developed by the Institute of Aerodynamics of the RWTH Aachen University is currently used in a multidisciplinary project to simulate the air flow through the human nose. In order to reduce the runtime of the expensive computations the Para Wise/CAPO automatic parallelization environment has been used to assist in the nested OpenMP parallelization of the TFS multiblock code targeted at Sun Microsystems shared memory parallel systems. Further manual tuning improved the scalability of the OpenMP approach.