FPGA ARCHITECTURE FOR 2D DISCRETE FOURIER TRANSFORM BASED ON 2D DECOMPOSITION FOR LARGE-SIZED DATA

ABSTRACT Applications based on Discrete Fourier Transforms (DFT) are extensively used in various areas of signal and digital image processing. Of particular interest is the two-dimensional (2D) DFT which is more computation-and bandwidth-intensive than the one-dimensional (ID) DFT. Traditionally, a 2D DFT is computed using Row-Column (RC) decomposition, where ID DFTs are computed along the rows followed by ID DFTs along the columns. Both application specific and reconfigurable hardware have been used for high-performance implementations of 2D DFT. However, architectures based on RC decomposition are not efficient for large input size data due to memory bandwidth constraints. In this paper, we propose an efficient architecture to implement the 2D DFT for largesized input data based on a novel 2D decomposition algorithm. This architecture achieves very high throughput by exploiting the inherent parallelism due to the algorithm decomposition and by utilizing the row-wise burst access pattern of the external memory. A high throughput memory interface has been designed to enable maximum utilization of the memory bandwidth. In addition, an automatic system generator is provided for mapping this architecture onto a reconfigurable platform of Xilinx Virtex5 devices. For a 2K x 2K input size, the proposed architecture is 1.96x times faster than RC decomposition based implementation under the same memory constraints, and also outperforms other existing implementations

Panax ginseng abuse exhibits a pro-inflammatory effect by activating the NF-κB pathway

P. ginseng (Panax ginseng C. A. Meyer) is a well-known traditional medicine that has been used for thousands of years to treat diseases. However, “ginseng abuse syndrome” (GAS) often occurs due to an inappropriate use such as high-dose or long-term usage of ginseng; information about what causes GAS and how GAS occurs is still lacking. In this study, the critical components that potentially caused GAS were screened through a step-by-step separation strategy, the pro-inflammatory effects of different extracts on messenger RNA (mRNA) or protein expression levels were evaluated in RAW 264.7 macrophages through quantitative real-time polymerase chain reaction (qRT-PCR) or Western blot, respectively. It was found that high-molecular water-soluble substances (HWSS) significantly increased the expression of cytokines (cyclooxygenase-2 (COX-2), inducible nitric oxide synthase (iNOS), and interleukin 6 (IL-6)) and cyclooxygenase 2 (COX-2) protein; gel filtration chromatography fraction 1 (GFC-F1) further purified from HWSS showed prominent pro-inflammatory effects by increasing the transcription of cytokines (COX-2, iNOS, tumor necrosis factor alpha (TNF-α), and interleukin 1β (IL-1β)) as well as the expression of COX-2 and iNOS protein. Moreover, GFC-F1 activated nuclear factor-kappa B (NF-кB) (p65 and inhibitor of nuclear factor-kappa B alpha (IκB-α)) and the p38/MAPK (mitogen-activated protein kinase) signaling pathways. On the other hand, the inhibitor of the NF-κB pathway (pyrrolidine dithiocarbamate (PDTC)) reduced GFC-F1-induced nitric oxide (NO) production, while the inhibitors of the MAPK pathways did not. Taken together, GFC-F1 is the potential composition that caused GAS through the production of inflammatory cytokines by activating the NF-кB pathway

A special-purpose compiler for look-up table and code generation for function evaluation

Abstract—Elementary functions are extensively used in com-puter graphics, signal and image processing, and communication systems. This paper presents a special-purpose compiler that automatically generates customized look-up tables and imple-mentations for elementary functions under user given constraints. The generated implementations include a C/C++ code that can be used directly by applications running on multicores, as well as a MATLAB-like code that can be translated directly to a hardware module on FPGA platforms. The experimental results show that our solutions for function evaluation bring significant performance improvements to applications on multicores as well as significant resource savings to designs on FPGAs. I