| Abstract: | 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 today's 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 © 2004 John Wiley & Sons, Ltd. |
