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When code generation occurs at runtime, as in just-in-time compilation (JIT), it is important that the entire process be efficient with respect to space and time. For example, when regular expressions are interpreted and used to generate code at runtime, a non-deterministic finite-state machine is often generated instead of a deterministic one, because usually the former can be created more ...
Most compilers have at least the following compiler phases (which therefore occur at compile-time): syntax analysis, semantic analysis, and code generation.During optimization phases, constant expressions in the source code can also be evaluated at compile-time using compile-time execution, which reduces the constant expressions to a single value.
A compiler is likely to perform some or all of the following operations, often called phases: preprocessing, lexical analysis, parsing, semantic analysis (syntax-directed translation), conversion of input programs to an intermediate representation, code optimization and machine specific code generation.
A tracing JIT compiler goes through various phases at runtime. First, profiling information for loops is collected. After a hot loop has been identified, a special tracing phase is entered, which records all executed operations of that loop. This sequence of operations is called a trace.
The solution to this problem is a pair of bypass multiplexers. These multiplexers sit at the end of the decode stage, and their flopped outputs are the inputs to the ALU. Each multiplexer selects between: A register file read port (i.e. the output of the decode stage, as in the naive pipeline): red arrow
The problem of compiling a self-compiling compiler has been called the chicken-or-egg problem in compiler design, and bootstrapping is a solution to this problem. [ 1 ] [ 2 ] Bootstrapping is a fairly common practice when creating a programming language .
System cost or reliability may be more important than the code speed. For example, compilers for embedded software usually offer options that reduce code size at the expense of speed. The code's timing may need to be predictable, rather than as fast as possible, so code caching might be disabled, along with compiler optimizations that require it.
Conversely, loop fusion (or loop jamming) is a compiler optimization and loop transformation which replaces multiple loops with a single one. [3] [2] Loop fusion does not always improve run-time speed. On some architectures, two loops may actually perform better than one loop because, for example, there is increased data locality within