Abstarct: Data processing refers to the analysis and interpretation of data, as well as the ability to manipulate and make changes to achieve the desired output. With the abundance of information in today's world, increasing processing speed is essential. FPGAs are one type of hardware that can meet this need. Among the techniques used in FPGAs for this purpose are pipelining and parallelization. It seems that the techniques proposed for increasing speed in FPGAs are very practical and applicable to most digital circuits. This claim can be proven by examining recent articles, such as the use of these methods in most digital converters, filters, image and video processing algorithm implementations. In this thesis, after reviewing various methods for increasing speed in FPGAs, we focus specifically on analyzing two methods: pipelining and parallelization. Finally, we attempt to implement these two methods as well as a combination of the two, known as pipeline parallelization, on a digital circuit (filter) using FPGA chips. To evaluate the performance of these methods, we implement filters with different orders both with and without these speed-increasing techniques, and observe the efficiency of these methods in increasing the speed of digital systems. For example, after implementing the pipelining technique on a third-order filter, its speed increases from 67 MHz to 167 MHz, and after implementing parallelization, its speed increases to 174 MHz. Finally, after implementing the combined technique, its speed reaches 203 MHz. The results demonstrate the optimal performance of these techniques when used in digital systems.