EnglishFloating- to fixed-point MATLAB algorithm conversion for FPGAs
By Tom Hill, Xilinx
June 04, 2007 -- dspdesignline.com
In a recent survey conducted by AccelChip Inc. (recently acquired by Xilinx), 53% of the respondents identified floating- to fixed-point conversion as the most difficult aspect of implementing an algorithm on an FPGA (Figure 1).
Figure 1. AccelChip DSP design challenges survey.
June 04, 2007 -- dspdesignline.com
In a recent survey conducted by AccelChip Inc. (recently acquired by Xilinx), 53% of the respondents identified floating- to fixed-point conversion as the most difficult aspect of implementing an algorithm on an FPGA (Figure 1).
Figure 1. AccelChip DSP design challenges survey.
Although MATLAB is a powerful algorithm development tool, many of its benefits are reduced during the fixed-point conversion process. For example, new mathematical errors are introduced into the algorithm because of the reduced precision of the fixed-point arithmetic. You must rewrite code to replace high-level functions and operators with low-level models that reflect the actual hardware macro-architecture. And simulation run times can be as much as 50 times longer. For these reasons, MATLAB, the overwhelming choice for algorithm development, is often abandoned in favor of C/C++ for fixed-point modeling.
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