Basic Combinational Blocks using Vivado HLS

Vivado HLS is designed for high level language synthesis of digital systems. Any system can be modelled using lower-level languages like Verilog HDL, VHDL. But these HDL languages are considered as machine level languages like assembly language in case of microprocessors. High level languages like C, C++ or even python also can be used to […]

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General Verilog Codes for Sequential Blocks

In our previous post, we discussed about general codes for some of the most important combinational blocks. In this post, we will discuss general Verilog codes for some of the most important sequential blocks. General Verilog Codes for Sequential Blocks are important to avoid different codes for different design parameters. General Verilog codes make our

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General Verilog Codes for Combinational Blocks

In our previous blog, we discussed different combinational circuits but General Verilog codes are essential in writing bigger complex codes for a system. They make it easy for the coders to generalize the overall code. The generalized overall code can then be easily tuned for the design parameters. For example, if a designer writes a

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Solving Linear Equations using QR Decomposition

QR decomposition is another powerful technique to solve linear equations. In QR decomposition, the co-efficient matrix need not to be a symmetric matrix. In special cases where the input signal is compressible or sparse, QR decomposition can directly operate on matrix if less than . This way an underdetermined linear system is solved. Matrix is

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Solving Linear Equations with Modified Cholesky Decomposition

In our previous tutorial, we have discussed about Cholesky decomposition which is a very important matrix factorization to solve a linear equation. But this technique has some drawbacks which are also discussed in the same tutorial. In this tutorial, we will discuss about modified Cholesky Decomposition which is an alternative version of Cholesky decomposition. This

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Solving Linear Equations using Cholesky Decomposition

Cholesky decomposition is a very important matrix factorization technique which is used to solve a linear equation. This technique originally derives from very popular LU decomposition and very suitable for higher order matrices. In Cholesky decomposition, the co-efficient matrix has to be a symmetric positive definite matrix. But in general, the co-efficient matrix can be

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