<p>Autoliv has developed the Night Vision system, which is a safety system for use incars to improve the driver’s situational awareness during night conditions. It is areal-time system that is able to detect pedestrians in the traffic environment andissue warnings when there is a risk of collision. The timing behaviour of programsrunning on real-time systems is vital information when developing and optimisingboth hardware and software. As a part of further developing their Night Visionsystem, Autoliv wanted to examine detailed timing behaviour of a specific part ofthe Night Vision algorithm, namely the Tracking module, which tracks detectedpedestrians. Parallel to this, they also wanted a reliable method to obtain timingdata that would work for other parts of that system as well, or even other applications.</p><p>A preliminary study was conducted in order to determine the most suitable methodof obtaining the timing data desired. This resulted in a measurement-based approachusing software profiling, in which the Tracking module was measured usingvarious input data. The measurements were performed on simulated hardwareusing both a cycle accurate simulator and measurement tools from the systemCPU manufacturer, as well as tools implemented specifically to handle input andoutput data.</p><p>The measurements resulted in large amounts of data used to compile performancestatistics. Using different scenarios in the input data, we were able to obtain timingcharacteristics for several typical situations the system may encounter duringoperation. By manipulating the input data we were also able to observe generalbehaviour and achieve artificially high execution times, which serves as indicationson how the system responds to irregular and unexpected input data.</p><p>The method used for collecting timing information was well suited for this particularproject. It provided the possibility to analyse behavior in a better waythan other, more theoretical, approaches would have. The method is also easilyadaptable to other parts of the Night Vision system, or other systems, with onlyminor adjustments to measurement environment and tools.</p>

Autoliv has developed the Night Vision system, which is a safety system for use incars to improve the driver’s situational awareness during night conditions. It is areal-time system that is able to detect pedestrians in the traffic environment andissue warnings when there is a risk of collision. The timing behaviour of programsrunning on real-time systems is vital information when developing and optimisingboth hardware and software. As a part of further developing their Night Visionsystem, Autoliv wanted to examine detailed timing behaviour of a specific part ofthe Night Vision algorithm, namely the Tracking module, which tracks detectedpedestrians. Parallel to this, they also wanted a reliable method to obtain timingdata that would work for other parts of that system as well, or even other applications. A preliminary study was conducted in order to determine the most suitable methodof obtaining the timing data desired. This resulted in a measurement-based approachusing software profiling, in which the Tracking module was measured usingvarious input data. The measurements were performed on simulated hardwareusing both a cycle accurate simulator and measurement tools from the systemCPU manufacturer, as well as tools implemented specifically to handle input andoutput data. The measurements resulted in large amounts of data used to compile performancestatistics. Using different scenarios in the input data, we were able to obtain timingcharacteristics for several typical situations the system may encounter duringoperation. By manipulating the input data we were also able to observe generalbehaviour and achieve artificially high execution times, which serves as indicationson how the system responds to irregular and unexpected input data. The method used for collecting timing information was well suited for this particularproject. It provided the possibility to analyse behavior in a better waythan other, more theoretical, approaches would have. The method is also easilyadaptable to other parts of the Night Vision system, or other systems, with onlyminor adjustments to measurement environment and tools.

This thesis describes possible applications of Prony's method in timing analysis of digital circuits. Such applications include predicting the future shape of the waveform in DTA(Dynamic Timing Analysis) and delay look-up table in STA(Static Timing Analysis). Given some equally spaced output values, the traditional Prony's method can be used to extract poles and residues of a linear system, i.e. to characterize a waveform using an exponential function. In this thesis, not only values but also equally spaced derivatives are tested. Still using same idea of the traditional Prony's method, poles and residues can also be extracted with those values and derivatives. The resultant poles and residues will be used to predict the output waveform in DTA analysis. The benefits brought by the using of derivatives include less simulation steps and less CPU time consuming than the regular constant step simulation. As a matter of fact, the Prony's method can precisely approximate a complicated waveform. Such property can be applied for STA analysis. The Prony's approximation can be used to precisely record an output waveform, which is used as an entry of the look-up table of STA. Since the accuracy of STA analysis relies on the accuracy of the input and output waveform in the look-up table, the accuracy of the Prony's approach is promising.

This thesis describes possible applications of Prony's method in timing analysis of digital circuits. Such applications include predicting the future shape of the waveform in DTA(Dynamic Timing Analysis) and delay look-up table in STA(Static Timing Analysis). Given some equally spaced output values, the traditional Prony's method can be used to extract poles and residues of a linear system, i.e. to characterize a waveform using an exponential function. In this thesis, not only values but also equally spaced derivatives are tested. Still using same idea of the traditional Prony's method, poles and residues can also be extracted with those values and derivatives. The resultant poles and residues will be used to predict the output waveform in DTA analysis. The benefits brought by the using of derivatives include less simulation steps and less CPU time consuming than the regular constant step simulation. As a matter of fact, the Prony's method can precisely approximate a complicated waveform. Such property can be applied for STA analysis. The Prony's approximation can be used to precisely record an output waveform, which is used as an entry of the look-up table of STA. Since the accuracy of STA analysis relies on the accuracy of the input and output waveform in the look-up table, the accuracy of the Prony's approach is promising.

This thesis describes possible applications of Prony's method in timing analysis of digital circuits. Such applications include predicting the future shape of the waveform in DTA(Dynamic Timing Analysis) and delay look-up table in STA(Static Timing Analysis). Given some equally spaced output values, the traditional Prony's method can be used to extract poles and residues of a linear system, i.e. to characterize a waveform using an exponential function. In this thesis, not only values but also equally spaced derivatives are tested. Still using same idea of the traditional Prony's method, poles and residues can also be extracted with those values and derivatives. The resultant poles and residues will be used to predict the output waveform in DTA analysis. The benefits brought by the using of derivatives include less simulation steps and less CPU time consuming than the regular constant step simulation. As a matter of fact, the Prony's method can precisely approximate a complicated waveform. Such property can be applied for STA analysis. The Prony's approximation can be used to precisely record an output waveform, which is used as an entry of the look-up table of STA. Since the accuracy of STA analysis relies on the accuracy of the input and output waveform in the look-up table, the accuracy of the Prony's approach is promising.

This thesis describes possible applications of Prony's method in timing analysis of digital circuits. Such applications include predicting the future shape of the waveform in DTA(Dynamic Timing Analysis) and delay look-up table in STA(Static Timing Analysis). Given some equally spaced output values, the traditional Prony's method can be used to extract poles and residues of a linear system, i.e. to characterize a waveform using an exponential function. In this thesis, not only values but also equally spaced derivatives are tested. Still using same idea of the traditional Prony's method, poles and residues can also be extracted with those values and derivatives. The resultant poles and residues will be used to predict the output waveform in DTA analysis. The benefits brought by the using of derivatives include less simulation steps and less CPU time consuming than the regular constant step simulation. As a matter of fact, the Prony's method can precisely approximate a complicated waveform. Such property can be applied for STA analysis. The Prony's approximation can be used to precisely record an output waveform, which is used as an entry of the look-up table of STA. Since the accuracy of STA analysis relies on the accuracy of the input and output waveform in the look-up table, the accuracy of the Prony's approach is promising.