To generate C code from this algorithm, we must use only operators and functions that are part of the Embedded MATLAB subset. The equivalent C code requires iterators, such as for loops, to express the matrix operations as a sequence of scalar computations. Most MATLAB expressions containing vectors and matrices are compact, single-line expressions similar to the corresponding mathematical formula. MATLAB is based on compact matrix notation. To translate a polymorphic MATLAB function to C, the programmer must maintain separate function prototype for each possible parameter signature. This kind of flexibility is not supported in C, which assigns a single algorithm to each parameter type. For example, the abs function computes the absolute value of real numbers and norm of complex numbers and can process scalars, vectors, or matrices. Functions in MATLAB can process different types of input parameters and can apply a different algorithm to each type of parameter. While this flexibility makes it easy to develop algorithms as proofs of concept, when it comes time for translation to C, the programmer must assign appropriate data types and sizes to all variables. When writing a MATLAB program, you do not need to define data types and sizes for your variables. MATLAB is a dynamically typed and C is a statically typed language. During translation of an algorithm from MATLAB to C, however, software designers face some important constraints. MATLAB has several advantages for design exploration, such as polymorphism, matrix-based functions, and an interactive programming environment. This article outlines the challenges involved in the manual translation from MATLAB to C, demonstrates how to use the Embedded MATLAB subset for automatic translation, and provides best practices for coding your MATLAB algorithm to improve the generated C code. When your MATLAB algorithm uses the Embedded MATLAB™ language subset, the translation to C becomes unambiguous, enabling you to focus on refining your design rather than producing and verifying hand written C code. A great deal of effort is required to ensure that the MATLAB code and the C code remain equivalent. Manually translating MATLAB to C involves incorporating into the code low-level details such as data-type assignments, memory allocations, and optimizations for computational load and memory. The solution is automatic translation of MATLAB to embeddable C. The challenge is to transition a design from the flexible development environment of MATLAB to the constrained programming style of C. In contrast, programming in C is well suited to optimizing DSPs for performance, memory, and processing power. As a high-level language, MATLAB facilitates design exploration. Embedded software developers have long relied on MATLAB ® for algorithm design and prototyping and on C code for implementation on embedded processors and DSPs.
0 Comments
Leave a Reply. |
Details
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |