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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 ...
JIT code generally offers far better performance than interpreters. In addition, it can in some cases offer better performance than static compilation, as many optimizations are only feasible at run-time: [17] [18] The compilation can be optimized to the targeted CPU and the operating system model where the application runs.
Java bytecode is used at runtime either interpreted by a JVM or compiled to machine code via just-in-time (JIT) compilation and run as a native application. As Java bytecode is designed for a cross-platform compatibility and security, a Java bytecode application tends to run consistently across various hardware and software configurations. [3]
Very long instruction word (VLIW) refers to instruction set architectures that are designed to exploit instruction-level parallelism (ILP). A VLIW processor allows programs to explicitly specify instructions to execute in parallel, whereas conventional central processing units (CPUs) mostly allow programs to specify instructions to execute in sequence only.
For the "interrupt acknowledge" method, the external device gives the CPU an interrupt handler number. The interrupt acknowledge method is used by the Intel Pentium and many older microprocessors. [8] When the CPU is affected by an interrupt, it looks up the interrupt handler in the interrupt vector table, and transfers control to it.
In software design, the Java Native Interface (JNI) is a foreign function interface programming framework that enables Java code running in a Java virtual machine (JVM) to call and be called by [1] native applications (programs specific to a hardware and operating system platform) and libraries written in other languages such as C, C++ and assembly.
Optimizing compilers are responsible for generating code that, when executed, will cause the hardware to use caches and registers efficiently. Many programmers assume one level of memory. This works fine until the application hits a performance wall. Then the memory hierarchy will be assessed during code refactoring.
A macro processor, such as the C preprocessor, which replaces patterns in source code according to relatively simple rules, is a simple form of source-code generator. Source-to-source code generation tools also exist. [11] [12] Large language models such as ChatGPT are capable of generating a program's source code from a description of the ...