The Locus Algorithm III: A Grid Computing system to generate catalogues of optimised pointings for Differential Photometry

This paper discusses the hardware and software components of the Grid Computing system used to implement the Locus Algorithm to identify optimum pointings for differential photometry of 61,662,376 stars and 23,799 quasars. The scale of the data, together with initial operational assessments demanded a High Performance Computing (HPC) system to complete the data analysis. Grid computing was chosen as the HPC solution as the optimum choice available within this project. The physical and logical structure of the National Grid computing Infrastructure informed the approach that was taken. That approach was one of layered separation of the different project components to enable maximum flexibility and extensibility

The Locus Algorithm IV: Performance metrics of a grid computing system used to create catalogues of optimised pointings

This paper discusses the requirements for and performance metrics of the the Grid Computing system used to implement the Locus Algorithm to identify optimum pointings for differential photometry of 61,662,376 stars and 23,779 quasars. Initial operational tests indicated a need for a software system to analyse the data and a High Performance Computing system to run that software in a scalable manner. Practical assessments of the performance of the software in a serial computing environment were used to provide a benchmark against which the performance metrics of the HPC solution could be compared, as well as to indicate any bottlenecks in performance. These performance metrics indicated a distinct split in the performance dictated more by differences in the input data than by differences in the design of the systems used. This indicates a need for experimental analysis of system performance, and suggests that algorithmic complexity analyses may lead to incorrect or naive conclusions, especially in systems with high data I/O overhead such as grid computing. Further, it implies that systems which reduce or eliminate this bottleneck such as in-memory processing could lead to a substantial increase in performance

BioNessie - a grid enabled biochemical networks simulation environment

The simulation of biochemical networks provides insight and understanding about the underlying biochemical processes and pathways used by cells and organisms. BioNessie is a biochemical network simulator which has been developed at the University of Glasgow. This paper describes the simulator and focuses in particular on how it has been extended to benefit from a wide variety of high performance compute resources across the UK through Grid technologies to support larger scale simulations

'BioNessie(G) - a grid enabled biochemical networks simulation environment

The simulation of biochemical networks provides insight and understanding about the underlying biochemical processes and pathways used by cells and organisms. BioNessie is a biochemical network simulator which has been developed at the University of Glasgow. This paper describes the simulator and focuses in particular on how it has been extended to benefit from a wide variety of high performance compute resources across the UK through Grid technologies to support larger scale simulations

A ducted wind turbine simulation model for building simulation

Power production is shifting away from centralized generation plants to production of heat and power at the point of demand. A technology that may play a part in this shift is the ducted wind turbine (DWT). The emergence of small building integrated micro turbines opens up the possibility of utilizing the differential pressures occurring around buildings for local power production. This paper describes work to develop and test a simple mathematical model of a ducted wind turbine and its integration within a building simulation tool. A case study in which the simulation model will be used to analyse of the likely power output from a building incorporating ducted wind turbines within the façade is also presented

Performance of VIDEBAS in an operational environment

VIDEBAS is a relational database management system in which a database consists of two parts, namely a “real-only” and an “update” part. The first part remains unmodified until the next reorganization and exploits redundancy to achieve fast access to data. A prototype of VIDEBAS has been built. In this paper a performance comparison between this relational system and a DBTG-system (UDS) is made. The used external memory and the number of page accesses to retrieve and update tuples is estimated. Although it is commonly assumed that in an operational environment relational systems are slower than network systems the opposite appears. On the other hand UDS needs less external memory