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This document describes the work for the master’s thesis in Electrical Engineering carried out at Electrolux Laundry Systems. In this project the computers that control the laundry system have been compared in order to verify the performance of the whole system. Three real environment systems are analysed and two of these systems have been set up in the laboratory in order to solve the problem considered. The results show that the tested devices perform better than the device PC1, which is not fulfilling the expectations in the real environment system. Some conclusions and future work are presented.

The goal of this study was to determine if performance-based tests should be routinely administered to students in computer application courses. The purpose was to determine the most appropriate mode of testing for individuals taking a computer applications course. The study is divided into areas of assessment, personality traits, and computer attitudes.

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.