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 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.

Depth gradients of benthic standing stock and diversity on the continental margin at a high-latitude ice-free site (off Spitsbergen 79 degrees N)

High-latitude seas are mostly covered by multi-year ice, which impacts processes of primary production and sedimentation of organic matter. Because of the warming effect of West Spitsbergen Current (WSC), the waters off West Spitsbergen have only winter ice cover. That is uncommon for such a high latitude and enables to separate effects of multiyear-ice cover from the latitudinal patterns. Macrofauna was sampled off Kongsfjord (79°N) along the depth gradient from 300 to 3000 m. The density, biomass and diversity at shallow sites situated in a canyon were very variable. Biomass was negatively correlated with depth (R=-0.86R=-0.86, p<0.001), and ranged from 61 g ww m−2 (212 m) to 1 g ww m−2 (2025 m). The biomasses were much higher than in the multiyear-ice covered High Arctic at similar depths, while resembling those from temperate and tropical localities. Species richness (expressed by number of species per sample and species–area accumulation curves) decreased with depth. There was no clear depth-related pattern in diversity measures: Hurbert rarefaction, Shannon–Wiener or Pielou. The classic increase of species richness and diversity with depth was not observed. Species richness and diversity of deep-sea macrofauna were much lower in our study than in comparable studies of temperate North Atlantic localities. That is related to geographic isolation of Greenland–Icelandic–Norwegian (GIN) seas from the Atlantic pool of species.