Chlamydia-related bacteria in respiratory samples in Finland.

Chlamydia-related bacteria, new members of the order Chlamydiales, are suggested to be associated with respiratory disease. We used real-time PCR to investigate the prevalence of Parachlamydia acanthamoebae, Protochlamydia spp., Rhabdochlamydia spp., Simkania negevensis and Waddlia chondrophila in samples taken from patients with suspected respiratory tract infections. Of the 531 samples analyzed, the subset of 136 samples contained 16 (11.8%) samples positive for Rhabdochlamydia spp. DNA. P. acanthamoebae, Protochlamydia spp., S. negevensis and W. chondrophila DNA were not detected among the respiratory samples investigated. These results suggest an association of Rhabdochlamydia spp. with respiratory disease.

Memory-based scheduling of scientific computing clusters

This study looks at how increased memory utilisation affects throughput and energy consumption in scientific computing, especially in high-energy physics. Our aim is to minimise energy consumed by a set of jobs without increasing the processing time. The earlier tests indicated that, especially in data analysis, throughput can increase over 100% and energy consumption decrease 50% by processing multiple jobs in parallel per CPU core. Since jobs are heterogeneous, it is not possible to find an optimum value for the number of parallel jobs. A better solution is based on memory utilisation, but finding an optimum memory threshold is not straightforward. Therefore, a fuzzy logic-based algorithm was developed that can dynamically adapt the memory threshold based on the overall load. In this way, it is possible to keep memory consumption stable with different workloads while achieving significantly higher throughput and energy-efficiency than using a traditional fixed number of jobs or fixed memory threshold approaches.