Performance tuning of a smartphone-based overtaking assistant

ITS solutions suffer from the slow pace of adoption by manufacturers despite the interest shown by both consumers and industry. Our goal is to develop ITS applications using already available technologies to make them affordable, quick to deploy, and easy to adopt. In this paper we introduce EYES, an overtaking assistance solution that provides drivers with a real-time video feed from the vehicle located just in front. Our application thus provides a better view of the road ahead, and of any vehicles travelling in the opposite direction, being especially useful when the front view of the driver is blocked by large vehicles. We evaluated our application using the MJPEG video encoding format, and have determined the most effective resolution and JPEG quality choice for our case. Experimental results from the tests performed with the application in both indoor and outdoor scenarios, allow us to be optimistic about the effectiveness and applicability of smartphones in providing overtaking assistance based on video streaming in vehicular networks

Performance Tuning of Database Systems Using a Context-aware Approach

Database system performance problems have a cascading effect into all aspects of an enterprise application. Database vendors and application developers provide guidelines, best practices and even initial database settings for good performance. But database performance tuning is not a one-off task. Database administrators have to keep a constant eye on the database performance as the tuning work carried out earlier could be invalidated due to multitude of reasons. Before engaging in a performance tuning endeavor, a database administrator must prioritize which tuning tasks to carry out first. This prioritization is done based on which tuning action would yield highest performance benefit. However, this prediction may not always be accurate. Experiment-based performance tuning methodologies have been introduced as an alternative to prediction-based performance tuning approaches. Experimenting on a representative system similar to the production one allows a database administrator to accurately gauge the performance gain for a particular tuning task. In this paper we propose a novel approach to experiment-based performance tuning with the use of a context-aware application model. Using a proof-of-concept implementation we show how it could be used to automate the detection of performance changes, experiment creation and evaluate the performance tuning outcomes for mixed workload types through database configuration parameter changes

A Study on the Influence of Caching: Sequences of Dense Linear Algebra Kernels

It is universally known that caching is critical to attain high- performance implementations: In many situations, data locality (in space and time) plays a bigger role than optimizing the (number of) arithmetic floating point operations. In this paper, we show evidence that at least for linear algebra algorithms, caching is also a crucial factor for accurate performance modeling and performance prediction.Comment: Submitted to the Ninth International Workshop on Automatic Performance Tuning (iWAPT2014

Performance Debugging and Tuning using an Instruction-Set Simulator

Instruction-set simulators allow programmers a detailed level of insight into, and control over, the execution of a program, including parallel programs and operating systems. In principle, instruction set simulation can model any target computer and gather any statistic. Furthermore, such simulators are usually portable, independent of compiler tools, and deterministic-allowing bugs to be recreated or measurements repeated. Though often viewed as being too slow for use as a general programming tool, in the last several years their performance has improved considerably. We describe SIMICS, an instruction set simulator of SPARC-based multiprocessors developed at SICS, in its rôle as a general programming tool. We discuss some of the benefits of using a tool such as SIMICS to support various tasks in software engineering, including debugging, testing, analysis, and performance tuning. We present in some detail two test cases, where we've used SimICS to support analysis and performance tuning of two applications, Penny and EQNTOTT. This work resulted in improved parallelism in, and understanding of, Penny, as well as a performance improvement for EQNTOTT of over a magnitude. We also present some early work on analyzing SPARC/Linux, demonstrating the ability of tools like SimICS to analyze operating systems

Basic database performance tuning - developer's perspective

This lecture discusses selected database performance issues from the developer's point of view: connection overhead, bind variables and SQL injection, making most of the optimizer with up-to-date statistics, reading execution plans. Prior knowledge of SQL is expected