FFT IP Core: User Guide

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ID 683374
Date 11/06/2017
Public
Document Table of Contents
Document Table of Contents x
1. About This IP Core 2. FFT IP Core Getting Started 3. FFT IP Core Functional Description 4. Block Floating Point Scaling 5. Document Revision History A. FFT IP Core User Guide Document Archive
1. About This IP Core x
1.1. Intel® DSP IP Core Features 1.2. FFT IP Core Features 1.3. General Description 1.4. DSP IP Core Device Family Support 1.5. DSP IP Core Verification 1.6. FFT IP Core Release Information 1.7. Performance and Resource Utilization
1.3. General Description x
1.3.1. Fixed Transform Size FFT 1.3.2. Variable Streaming FFT
2. FFT IP Core Getting Started x
2.1. Installing and Licensing Intel® FPGA IP Cores 2.2. IP Catalog and Parameter Editor 2.3. Generating IP Cores ( Intel® Quartus® Prime Pro Edition) 2.4. Generating IP Cores ( Intel® Quartus® Prime Standard Edition) 2.5. Simulating Intel® FPGA IP Cores 2.6. DSP Builder for Intel® FPGAs Design Flow
2.1. Installing and Licensing Intel® FPGA IP Cores x
2.1.1. Intel® FPGA IP Evaluation Mode 2.1.2. FFT IP Core Intel® FPGA IP Evaluation Mode Timeout Behavior
2.3. Generating IP Cores ( Intel® Quartus® Prime Pro Edition) x
2.3.1. IP Core Generation Output ( Intel® Quartus® Prime Pro Edition)
2.4. Generating IP Cores ( Intel® Quartus® Prime Standard Edition) x
2.4.1. IP Core Generation Output ( Intel® Quartus® Prime Standard Edition)
2.5. Simulating Intel® FPGA IP Cores x
2.5.1. Simulating the Fixed-Transform FFT IP Core in the MATLAB Software 2.5.2. Simulating the Variable Streaming FFT IP Core in the MATLAB Software
3. FFT IP Core Functional Description x
3.1. Fixed Transform FFTs 3.2. Variable Streaming FFTs 3.3. FFT Processor Engines 3.4. I/O Data Flow 3.5. FFT IP Core Parameters 3.6. FFT IP Core Interfaces and Signals
3.2. Variable Streaming FFTs x
3.2.1. Fixed-Point Variable Streaming FFTs 3.2.2. Floating-Point Variable Streaming FFTs
3.3. FFT Processor Engines x
3.3.1. Quad-Output FFT Engine 3.3.2. Single-Output FFT Engine
3.4. I/O Data Flow x
3.4.1. Streaming FFT 3.4.2. Variable Streaming 3.4.3. Buffered Burst 3.4.4. Burst
3.4.1. Streaming FFT x
3.4.1.1. Using the Streaming FFT 3.4.1.2. Changing the Direction on a Block-by-Block Basis 3.4.1.3. Enabling the Streaming FFT
3.4.2. Variable Streaming x
3.4.2.1. Changing Block Size 3.4.2.2. Changing Direction 3.4.2.3. I/O Order 3.4.2.4. Enabling the Variable Streaming FFT 3.4.2.5. Dynamically Changing the FFT Size 3.4.2.6. I/O Order
3.4.3. Buffered Burst x
3.4.3.1. Enabling the Buffered Burst FFT
3.6. FFT IP Core Interfaces and Signals x
3.6.1. Avalon-ST Interfaces in DSP IP Cores 3.6.2. FFT IP Core Avalon-ST Signals
3.6.2. FFT IP Core Avalon-ST Signals x
3.6.2.1. Component Specific Signals
4. Block Floating Point Scaling x
4.1. Possible Exponent Values 4.2. Implementing Scaling 4.3. Unity Gain in an IFFT+FFT Pair
4.2. Implementing Scaling x
4.2.1. Example of Scaling
1. About This IP Core
2. FFT IP Core Getting Started
3. FFT IP Core Functional Description
4. Block Floating Point Scaling
5. Document Revision History
A. FFT IP Core User Guide Document Archive

2.5.2. Simulating the Variable Streaming FFT IP Core in the MATLAB Software

The FFT IP Core produces a bit-accurate MATLAB model <variation name>_model.m, which you can use to model the behavior of your custom FFT variation in the MATLAB software.

The model takes a complex vector as input and it outputs the transform-domain complex vector. The lengths and direction of the transforms (FFT/IFFT) (specified as one entry per block) are also passed as an input to the model. You must ensure that the length of the input vector is at least as large as the sum of the transform sizes for the model to function correctly. The wizard also creates the MATLAB testbench file <variation name>_tb.m. This file creates the stimuli for the MATLAB model by reading the input complex random data from the generated files.

  1. Run the MATLAB software.
  2. In the MATLAB command window, change to the working directory for your project.
  3. Simulate the design:
    1. Type help <variation name>_model at the command prompt to view the input and output vectors that are required to run the MATLAB model as a standalone M-function. Create your input vector and make a function call to <variation name>_model. For example: 
      nps=[256,2048];
	inverse = [0,1]; % 0 => FFT 1=> IFFT
	x = (2^12)*rand(1,sum(nps)) + j*(2^12)*rand(1,sum(nps));
	[y] = <variation name>_model(x,nps,inverse);
    2. Alternaitvely, run the provided testbench by typing the name of the testbench, <variation name>_tb at the command prompt.
      Note: If you select digit-reversed output order, you can reorder the data with the following MATLAB code: 
      y = y(digit_reverse(0:(FFTSIZE-1), log2(FFTSIZE)) + 1);

      where digit_reverse is: 

      			function y = digit_reverse(x, n_bits)
			if mod(n_bits,2)
				z = dec2bin(x, n_bits);
				for i=1:2:n_bits-1
					p(:,i) = z(:,n_bits-i);
					p(:,i+1) = z(:,n_bits-i+1);
				end
				p(:,n_bits) = z(:,1);
				y=bin2dec(p);
			else
				y=digitrevorder(x,4);
			end
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