embblk.latency.systolicQRMatrixSolverBlockTiming

Compute throughput and latency of Systolic Matrix Solve Using QR Decomposition block

Since R2024a

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Syntax

[throughput,latency] = embblk.latency.systolicQRMatrixSolverBlockTiming(A,B)

Description

[throughput,latency] = embblk.latency.systolicQRMatrixSolverBlockTiming(A,B) returns the throughput and latency of the Systolic Matrix Solve Using QR Decomposition block. This computation depends on the data type, complexity, and dimension of the input matrices A,B.

example

Examples

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Define input matrices A and B. Compute the latency and throughput of the Systolic Matrix Solve Using QR Decomposition block for these inputs.

A = fi(complex(randn(4,4),randn(4,4)),1,17,10);
B = fi(complex(randn(4,1),randn(4,1)),1,17,10);
[throughput,latency] = embblk.latency.systolicQRMatrixSolverBlockTiming(A,B)
throughput =

    20


latency =

   190

Input Arguments

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Input matrices A and B to the Systolic Matrix Solve Using QR Decomposition block, specified as matrices.

Data Types: single | double | fi
Complex Number Support: Yes

Output Arguments

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Throughput of the Systolic Matrix Solve Using QR Decomposition block, returned as a scalar. Throughput is defined as the number of clock cycles between adjacent ready signals.

Latency of the Systolic Matrix Solve Using QR Decomposition block, returned as a scalar. Latency is defined as the number of clock cycles between the input and the corresponding output.

Version History

Introduced in R2024a

See Also