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  2. Trampoline (computing) - Wikipedia

    en.wikipedia.org/wiki/Trampoline_(computing)

    This avoids having to use "fat" function pointers for nested functions which carry both the code address and the static link. [8] [9] [10] This, however, conflicts with the desire to make the stack non-executable for security reasons. In the esoteric programming language Befunge, a trampoline is an instruction to skip the next cell in the ...

  3. Jump threading - Wikipedia

    en.wikipedia.org/wiki/Jump_threading

    In computing, jump threading is a compiler optimization of one jump directly to a second jump. If the second condition is a subset or inverse of the first, it can be eliminated, or threaded through the first jump. [1] This is easily done in a single pass through the program, following acyclic chained jumps until the compiler arrives at a fixed ...

  4. Branch table - Wikipedia

    en.wikipedia.org/wiki/Branch_table

    Examples of, and arguments for, Jump Tables via Function Pointer Arrays in C/C++ [3] Example code generated by 'Switch/Case' branch table in C, versus IF/ELSE. [4] Example code generated for array indexing if structure size is divisible by powers of 2 or otherwise.

  5. Jikes - Wikipedia

    en.wikipedia.org/wiki/Jikes

    Jikes is an open-source Java compiler written in C++.It is no longer being updated. The original version was developed by David L. "Dave" Shields and Philippe Charles at IBM but was quickly transformed into an open-source project contributed to by an active [citation needed] community of developers.

  6. Indirect branch - Wikipedia

    en.wikipedia.org/wiki/Indirect_branch

    An indirect branch (also known as a computed jump, indirect jump and register-indirect jump) is a type of program control instruction present in some machine language instruction sets. Rather than specifying the address of the next instruction to execute , as in a direct branch , the argument specifies where the address is located.

  7. Automatic parallelization - Wikipedia

    en.wikipedia.org/wiki/Automatic_parallelization

    Automatic parallelization by compilers or tools is very difficult due to the following reasons: [6] dependence analysis is hard for code that uses indirect addressing, pointers, recursion, or indirect function calls because it is difficult to detect such dependencies at compile time; loops have an unknown number of iterations;

  8. Escape analysis - Wikipedia

    en.wikipedia.org/wiki/Escape_analysis

    The popularity of the Java programming language has made escape analysis a target of interest. Java's combination of heap-only object allocation, built-in threading, the Sun HotSpot dynamic compiler, and OpenJ9 's just-in-time compiler (JIT) creates a candidate platform for escape analysis related optimizations (see Escape analysis in Java ).

  9. Loop unrolling - Wikipedia

    en.wikipedia.org/wiki/Loop_unrolling

    On the other hand, this manual loop unrolling expands the source code size from 3 lines to 7, that have to be produced, checked, and debugged, and the compiler may have to allocate more registers to store variables in the expanded loop iteration [dubious – discuss]. In addition, the loop control variables and number of operations inside the ...