In this study, a new gas turbine monitoring system being able to carry out appropriate run process is set up for a gas turbine with 250 kW power rating and its accessories. The system with the mechanical and electrical connections of the required sub-parts is transformed to a kind of the test stand. Performance test result calculation method is described. In addition that, performance evaluation software being able to apply with the completion of the preliminary performance tests is developed for this gas turbine. This system has infrastructure for the gas turbine sub-components performance and aerothermodynamics research. This system is also designed for aviation training facility as a training material for the gas turbine start and run demonstration. This system provides the preliminary gas turbine performance research requirements in the laboratory environment.

Performance monitoring counters are implemented in most recent microprocessors. In this thesis, we describe various performance measurement experiments for a program and a system that we conducted on a Linux operating system using the Pentium performance counters. We carried out our performance measurements on a Pentium II microprocessor. The Pentium II performance counters can be configured to count events such as cache misses, TLB misses, instructions executed etc. We used a low intrusive overhead technique to access these performance counters. We used these performance counters to measure the cache miss overheads due to context switches in Linux system. Our methodology involves sampling the hardware counters every 50ps. The sampling was set up using signals related to interval timers. We describe an analytical cache performance model under multiprogrammed condition from the literature and validate it using the performance monitoring counters. We next explores the long term performance of a system under different workload conditions. Various performance monitoring events - data cache h, data TLB misses, data cache reads or writes, branches etc. - are monitored over a 24 hour period. This is useful in identifying activities which cause loss of system performance. We used timer interrupts for sampling the performance counters. We develop a profiling methodology to give a perspective of performance of the different functions of a program, not only on the basis of execution-time but also on the data cache misses. Available tools like prof on Unix can be used to pinpoint the regions of performance loss of programs, but they mainly rely on an execution-time profiles. This does not give insight into problems in cache performance for that program. So we develop this methodology to get the performance of each function of the program not only on the basis of its execution time but also on the basis of its cache behavior.