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Additionally, it explores recent compiler innovations and highlights the advantages of these new features to the LabVIEW architecture and to you. Compilation versus Interpretation LabVIEW is a compiled language, which can be surprising because during typical G development, there is no explicit compile step.
Instead, you make a change to your VI and simply press the Run button to execute it. Compilation means that the G code you write is translated into native machine code and is then executed directly by the host computer.
An alternative to this approach is interpretation, where programs are indirectly executed by another software program called the interpreter instead of directly by the computer.
In later versions, the compiler replaced the interpreter to boost VI run-time performance, which is a common differentiator for compilers relative to interpreters. Interpreters tend to be easier to write and maintain at the cost of slower run-time performance, while compilers tend to be more complex to implement but offer faster execution times.
One of the primary benefits of the LabVIEW compiler is that improvements made to the compiler are seen by all VIs without the need for any changes. Back to Top 2. Some of the algorithms introduced here, such as type propagation, clumping, and inplaceness, are described in more detail in the modern LabVIEW compiler discussion.
The LabVIEW language was much simpler in those days, which also lessened the requirements on the compiler then an interpreter. For example, there was no polymorphism and the only numeric type was extended precision floating-point.
Also added in Version 2. The type propagation, inplaceness, and clumping algorithms continue to be important components of the modern LabVIEW compiler and have seen numerous incremental improvements over time.
The GenAPI cross compiles, which is important for real-time development. Real-time developers typically write VIs on a host PC but deploy them to and compile them for a real-time target. Additionally, a limited form of loop-invariant code motion was included.
Prior to the introduction of the GenAPI, registers were hardcoded in the generated code for each node. Limited forms of unreachable code and dead code elimination were also introduced. The DFIR was immediately used to build more advanced forms of loop-invariant code motion, constant folding, dead code elimination, and unreachable code elimination.
LLVM is an open-source compiler infrastructure used widely in industry. With LLVM, new optimizations were added such as instruction scheduling, loop unswitching, instruction combining, conditional propagation, and a more sophisticated register allocator. Back to Top 3.
First, review a high-level overview of the various compile steps and then revisit each part in more detail. The first step in the compilation of a VI is the type propagation algorithm.
This complex step is responsible for resolving implied types for terminals that can adapt to type, as well as detecting syntax errors.
All possible syntax errors in the G programming language are detected during the type propagation algorithm. If the algorithm determines that the VI is valid, then the compilation continues.
After type propagation, the VI is first converted from the model used by the block diagram editor into the DFIR used by the compiler. Once converted to the DFIR, the compiler executes several transforms on the DFIR graph to decompose it, optimize it, and prepare it for code generation.
Many of the compiler optimizations — for example, the inplacer and clumper — are implemented as transforms and run in this step.
A series of LLVM passes is run over the intermediate representation to further optimize and lower it, eventually to machine code.
Type Propagation As previously mentioned the type propagation algorithm resolves types and detects programming errors. In fact, this algorithm has several responsibilities including the following: However, it is the step in the LabVIEW compile chain that most clearly corresponds to the lexical analysis, parsing, or semantic analysis steps in a traditional compiler.
If you add two integers, the result is an integer, but if you add two floating-point numbers, the result is a floating-point number. Similar patterns exist for compound types such as arrays and clusters.
There are other language constructs like shift registers that have more complex typing rules. This add primitive example also illustrates the syntax-checking responsibility of the type propagation algorithm. Suppose you wire an integer and a string to an add primitive — what should happen?
The notion of an IR is common among modern compiler literature and can be applied to any programming language. There are a variety of popular IRs today.
Two common examples are abstract syntax trees AST and three-address code.Free Online Strategic Planner. Free Online Strategic Planner for creating a 3-page strategic plan based on the structure used in this white paper. Use it to organize your thoughts, structure your ideas and compile a short but comprehensive strategic plan for any size and type of organization.
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