Efficiency Comparison of DFT/IDFT Algorithms by Evaluating Diverse Hardware : Implementations,Parallelization Prospectsand Possible Improvements

In this paper we investigate various algorithms for performing Fast Fourier Transformation (FFT)/Inverse Fast Fourier Transformation (IFFT), and proper techniquesfor maximizing the FFT/IFFT execution speed, such as pipelining or parallel processing, and use of memory structures with pre-computed values (look up tables -LUT) or other dedicated hardware components (usually multipliers). Furthermore, we discuss the optimal hardware architectures that best apply to various FFT/IFFT algorithms, along with their abilities to exploit parallel processing with minimal data dependences of the FFT/IFFT calculations. An interesting approach that is also considered in this paper is the application of the integrated processing-in-memory Intelligent RAM (IRAM) chip to high speed FFT/IFFT computing. The results of the assessment study emphasize that the execution speed of the FFT/IFFT algorithms is tightly connected to the capabilities of the FFT/IFFT hardware to support the provided parallelism of the given algorithm. Therefore, we suggest that the basic Discrete Fourier Transform (DFT)/Inverse Discrete Fourier Transform (IDFT) can also provide high performances, by utilizing a specialized FFT/IFFT hardware architecture that can exploit the provided parallelism of the DFT/IDF operations. The proposed improvements include simplified multiplications over symbols given in polar coordinate system, using sinе and cosine look up tables,and an approach for performing parallel addition of N input symbols.

Possible Approaches to Commercializing Applied University Research: a Russian Case Study

This paper discusses the environment around universities in Russia and possible approaches to analyzing and choosing the method for applied research results commercialization as well as selecting promising applied research areas in that environment. Conceptual foundations for decision making during the commercialization and roadmap/action plan creation processes are outlined. These can be useful to both universities for planning their activities aswell as for organizations that plan to cooperate with universities or that are interested in university generated research. This being said, obtained models and used evaluation parameters may be unique and may depend upon the particular project, university, region, and personal preferences of decision makers. Thus, consideration of these parameters and characteristics only has merit when making decisions in the dynamics of change of these parameters. For this purpose statistical information is needed that characterizes the competencies of the research organization (university) inquestion, needs of partner organizations, governmental and societal requirements, and science and technology prospects. After determining the promising research areas it’s time to look at particular projects, which in turn are also characterized by various parameters dependent upon their objectives. Considering the values of these parameters in their dynamics allows control of project parameters in the course of its execution. This in turn allows prediction of negative situations and alleviation of such by setting the target values of parameters and using best practices and standardization of management processes to achieve those values.