Age, Biography and Wiki
Who is it? | Actor, Producer, Cinematographer |
Birth Day | August 19, 1931 |
Birth Place | Monterey, California, United States |
Age | 92 YEARS OLD |
Birth Sign | Virgo |
Net worth
Just N. Time, a versatile talent in the entertainment industry, is believed to have a net worth ranging from $100,000 to $1 million by 2024. This multi-faceted individual has made a name for themselves as an actor, producer, and cinematographer in the United States. Whether captivating audiences with their performances on-screen, behind the camera, or bringing captivating stories to life as a producer, Just N. Time has undoubtedly made a significant impact on the industry. With their diverse skill set and undeniable talent, it is no surprise that their net worth is expected to grow substantially in the coming years.
Biography/Timeline
The earliest published JIT compiler is generally attributed to work on LISP by John McCarthy in 1960. In his seminal paper Recursive functions of symbolic expressions and their computation by machine, Part I, he mentions functions that are translated during runtime, thereby sparing the need to save the compiler output to punch cards (although this would be more accurately known as a "Compile and go system"). Another early Example was by Ken Thompson, who in 1968 gave one of the first applications of regular expressions, here for pattern matching in the text Editor QED. For speed, Thompson implemented regular expression matching by JITing to IBM 7094 code on the Compatible Time-Sharing System. An influential technique for deriving compiled code from interpretation was pioneered by Mitchell in 1970, which he implemented for the experimental language LC².
Smalltalk (c. 1983) pioneered new aspects of JIT compilations. For Example, translation to machine code was done on demand, and the result was cached for later use. When memory became scarce, the system would delete some of this code and regenerate it when it was needed again. Sun's Self language improved these techniques extensively and was at one point the fastest Smalltalk system in the world; achieving up to half the speed of optimized C but with a fully object-oriented language.
Self was abandoned by Sun, but the research went into the Java language. The term "Just-in-time compilation" was borrowed from the Manufacturing term "Just in time" and popularized by Java, with James Gosling using the term from 1993. Currently JITing is used by most implementations of the Java Virtual Machine, as HotSpot builds on, and extensively uses, this research base.
Native Image Generator (Ngen) by Microsoft is another approach at reducing the initial delay. Ngen pre-compiles (or "pre-JITs") bytecode in a Common Intermediate Language image into machine native code. As a result, no runtime compilation is needed. .NET framework 2.0 shipped with Visual Studio 2005 runs Ngen on all of the Microsoft library DLLs right after the installation. Pre-jitting provides a way to improve the startup time. However, the quality of code it generates might not be as good as the one that is JITed, for the same reasons why code compiled statically, without profile-guided optimization, cannot be as good as JIT compiled code in the extreme case: the lack of profiling data to drive, for instance, inline caching.
JIT spraying is a class of computer security exploits that use JIT compilation for heap spraying – the resulting memory is then executable, which allows an exploit if execution can be moved into the heap.
The correct tradeoff can vary due to circumstances. For Example, Sun's Java Virtual Machine has two major modes—client and server. In client mode, minimal compilation and optimization is performed, to reduce startup time. In server mode, extensive compilation and optimization is performed, to maximize performance once the application is running by sacrificing startup time. Other Java just-in-time compilers have used a runtime measurement of the number of times a method has executed combined with the bytecode size of a method as a heuristic to decide when to compile. Still another uses the number of times executed combined with the detection of loops. In general, it is much harder to accurately predict which methods to optimize in short-running applications than in long-running ones.