Current multicore computers differ in many hardware aspects. Tuning parallel applications is indispensable to achieve best performance on a particular hardware platform. Auto-tuners represent a promising approach to systematically optimize a program’s tuning parameters, such as the number of threads, the size of data partitions, or the number of pipeline stages. However, auto-tuners require sev...

The differential evolution algorithm has been widely applied on unmanned aerial vehicle (UAV) path planning. At present, four random tuning parameters exist for differential evolution algorithm, namely, population size, differential weight, crossover, and generation number. These tuning parameters are required, together with user setting on path and computational cost weightage. However, the op...

For the shortcoming that the PI controller parameters can’t been dynamic tuning in constant voltage control system of doubly-fed wind turbines, a PI controller parameters dynamic tuning strategy based on the ant colony optimization (ACO) algorithm is presented. This strategy makes the two parameters in PI controller as the ant of the ant colony, the controlled absolute error integral function t...

We consider the problem of choosing multiple hyperparameters for support vector machines. We present a novel, general approach using an evolution strategy (ES) to determine the kernel from a parameterized kernel space and to control the regularization. We demonstrate on benchmark datasets that the ES improves the results achieved by grid search and can handle much more kernel parameters. In par...

In this paper, an online adaptation scheme for tuning of PID parameters is presented. This scheme is based upon our previous works on using a data-driven method to obtain a sufficient condition for robust stability and integrating robustness into the Unfalsified Control framework. Here, a modified bumpless transfer approach to facilitate the adaptation of the PID controller parameters is presen...

Adaptive MPI (AMPI) is an advanced MPI runtime environment that offers several features over traditional MPI runtimes, which can lead to a better utilization of the underlying hardware platform and therefore higher performance. These features are overdecomposition through virtualization, and load balancing via rank migration. Choosing which of these features to use, and finding the optimal para...

Database systems have a large number of configuration parameters that control memory distribution, I/O optimization, costing of query plans, parallelism, many aspects of logging, recovery, and other behavior. Regular users and even expert database administrators struggle to tune these parameters for good performance. The wave of research on improving database manageability has largely overlooke...

Two methods of realizing aperiodic stochastic resonance (ASR) by adding noise and tuning system parameters in a bistable system, after a scale transformation, can be compared in a real parameter space. In this space, the resonance point of ASR via adding noise denotes the extremum of a line segment, whereas the method of tuning system parameters presents the extrema of a parameter plane. We dem...

Most of statistical machine translation systems are combinations of various models, and tuning of the scaling factors is an important step. However, this optimisation problem is hard because the objective function has many local minima and the available algorithms cannot achieve a global optimum. Consequently, optimisations starting from different initial settings can converge to fairly differe...

Many minimum distance estimators have the potential to provide parameter estimates which are both robust and efficient and yet, despite these highly desirable theoretical properties, they are rarely used in practice. This is because the performance of these estimators is rarely guaranteed per se but obtained by placing a suitable value on some tuning parameter. Hence there is a risk involved in...