Implement Hardware-Efficient Real Partial-Systolic QR Decomposition

Open Script

This example shows how to implement a hardware-efficient QR decomposition using the Real Partial-Systolic QR Decomposition block.

Economy Size QR Decomposition

The Real Partial-Systolic QR Decomposition block performs the first step of solving the least-squares matrix equation AX = B which transforms A in-place to R and B in-place to C = Q'B, then solves the transformed system RX = C, where QR is the orthogonal-triangular decomposition of A.

To compute the stand-alone QR decomposition, this example sets B to be the identity matrix so that the output of the Real Partial-Systolic QR Decomposition block is the upper-triangular R and C = Q'.

Define Matrix Dimensions

Specify the number of rows in matrices A and B, the number of columns in matrix A, and the number of columns in matrix B. This example sets B to be the identity matrix the same size as the number of rows of A.

m = 10; % Number of rows in matrices A and B
n = 3;  % Number of columns in matrix A
p = m;  % Number of columns in matrix B

Generate Matrices A and B

Use the helper function realUniformRandomArray to generate a random matrix A such that the elements of A are between -1 and +1, and A is full rank. Matrix B is the identity matrix.

rng('default')
A = fixed.example.realUniformRandomArray(-1,1,m,n);
B = eye(m);

Select Fixed-Point Data Types

Use the helper function qrFixedpointTypes to select fixed-point data types for matrices A and B that guarantee no overflow will occur in the transformation of A in-place to R and B in-place to C = Q'B.

max_abs_A = 1;  % Upper bound on max(abs(A(:))
max_abs_B = 1;  % Upper bound on max(abs(B(:))
precisionBits = 24;  % Number of bits of precision
T = fixed.qrFixedpointTypes(m,max_abs_A,max_abs_B,precisionBits);
A = cast(A,'like',T.A);
B = cast(B,'like',T.B);

Open the Model

model = 'RealPartialSystolicQRModel';
open_system(model);

The Data Handler subsystem in this model takes real matrices A and B as inputs. The ready port triggers the Data Handler. After sending a true validIn signal, there may be some delay before ready is set to false. When the Data Handler detects the leading edge of the ready signal, the block sets validIn to true and sends the next row of A and B. This protocol allows data to be sent whenever a leading edge of the ready signal is detected, ensuring that all data is processed.

Set Variables in the Model Workspace

Use the helper function setModelWorkspace to add the variables defined above to the model workspace. These variables correspond to the block parameters for the Real Partial-Systolic QR Decomposition block.

numSamples = 1; % Number of sample matrices
fixed.example.setModelWorkspace(model,'A',A,'B',B,'m',m,'n',n,'p',p,...
    'numSamples',numSamples);

Simulate the Model

out = sim(model);

Construct the Solution from the Output Data

The Real Partial-Systolic QR Decomposition block outputs matrices R and C at each time step. When valid result matrices are output, the block sets validOut to true.

R = out.R;
C = out.C;

Extract the Economy-Size Q

The block computes C = Q'B. In this example, B is the identity matrix, so Q = C' is the economy-size orthogonal factor of the QR decomposition.

Q = C';

Verify that Q is Orthogonal and R is Upper-Triangular

Q is orothogonal, so Q'Q is the identity matrix within roundoff.

I = Q'*Q

I = 

    1.0000   -0.0000   -0.0000
   -0.0000    1.0000   -0.0000
   -0.0000   -0.0000    1.0000

          DataTypeMode: Fixed-point: binary point scaling
            Signedness: Signed
            WordLength: 62
        FractionLength: 48

R is an upper-triangular matrix.

R = 

    2.2180    0.8559   -0.5607
         0    2.0578   -0.4017
         0         0    1.7117

          DataTypeMode: Fixed-point: binary point scaling
            Signedness: Signed
            WordLength: 29
        FractionLength: 24

isequal(R,triu(R))

ans =

  logical

   1

Verify the Accuracy of the Output

To evaluate the accuracy of the Real Partial-Systolic QR Decomposition block, compute the relative error.

relative_error = norm(double(Q*R - A))/norm(double(A))

relative_error =

   1.5886e-06

Suppress mlint warnings.

%#ok<*NOPTS>