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Selection Sort

This method is a sorting method that will look for smallest or biggest value depend on ascending or descending order then being placed at the forefront place. After that, it will look for the next smallest or biggest value along all elements of array reduced by 1, and so on. For example, there is an array that contains these number :
31224135
If the data above is sorted in ascending by selection method, the result is:

Insertion Sort

Straight insertion is a sorting method which takes a parenthesis data on ordered data and shoves data which is bigger than parenthesis data so parenthesis data can be placed on right place. For example, there is an array that contains these number :
31224135
If the data above is sorted in ascending by straight insertion, the result is:

Introduction to Parallel Programming Using CUDA


CUDA (Compute Unified Device Architecture) is a scheme which is made by NVIDIA that make NVIDIA as a GPU (Graphic Processing Unit) is able to create computations not only for graphic-rendering but also for general-purpose. So, with CUDA, we can utilize quite a lot of processors that is own by NVIDIA for various computations. Now day, GPU likes ATI, also has had many processors on it. Scheme that ATI build is called ATI Stream. Parallel programming becomes so important because need of computer computation ability continues to increase for multitasking and powerful graphic processing. Current methods for performance enhancement are different with earlier methods where enhancement of processor clock is preferred. Clock speed enhancement is restricted by physical capabilities such as power and heat problem. In 2005, various computer industries started to offer computer with some cores on it starting from 2, 3, 4, 6, and so on. At the beginning of development of GPU with many cores, GPU utilization were only done by interface like OpenGL and DirectX which these interfaces are specialized only for graphical processing.
Latest series of NVIDIA have supported CUDA, exactly after 2006. For the list of series that support CUDA can be seen at http://nvidia.com/cuda. As the beginning in study of parallel programming using CUDA, it’s better to use C or C++ as programming language. CUDA C has been first special programming language that is developed by a GPU company to facilitate general-purpose computing on GPU. Some matters that should be prepared when using CUDA C to make an application are these below.