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MathWorks—Makers of MATLAB and Simulink.
http://www.mathworks.com/

has been cited by the following article:

  • TITLE: Open Source Synthesis and Verification Tool for Fixed-to-Floating and Floating-to-Fixed Points Conversions

    AUTHORS: Semih Aslan, Ekram Mohammad, Azim Hassan Salamy

    KEYWORDS: FPGA, VLSI, RTL, Iverilog, GTKWave, OCTAVE, HLS, C#, Open Source

    JOURNAL NAME: Circuits and Systems, Vol.7 No.11, September 23, 2016

    ABSTRACT: An open source high level synthesis fixed-to-floating and floating-to-fixed conversion tool is presented for embedded design, communication systems, and signal processing applications. Many systems use a fixed point number system. Fixed point numbers often need to be converted to floating point numbers for higher accuracy, dynamic range, fixed-length transmission limitations or end user requirements. A similar conversion system is needed to convert floating point numbers to fixed point numbers due to the advantages that fixed point numbers offer when compared with floating point number systems, such as compact hardware, reduced verification time and design effort. The latest embedded and SoC designs use both number systems together to improve accuracy or reduce required hardware in the same design. The proposed open source design and verification tool converts fixed point numbers to floating point numbers, and floating point numbers to fixed point numbers using the IEEE-754 floating point number standard. This open source design tool generates HDL code and its test bench that can be implemented in FPGA and VLSI systems. The design can be compiled and simulated using open source Iverilog/GTKWave and verified using Octave. A high level synthesis tool and GUI are designed using C#. The proposed design tool can increase productivity by reducing the design and verification time, as well as reduce the development cost due to the open source nature of the design tool. The proposed design tool can be used as a standalone block generator or implemented into current designs to improve range, accuracy, and reduce the development cost. The generated design has been implemented on Xilinx FPGAs.