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Just-in-Time Compilation Technique

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Just-In-Time Compilation Technique

1. Introduction

Just-in-time (JIT) compilation is an effective technique for boosting the speed of program interpreters. The idea of JIT compilation is to dynamically translate input programs into native machine code, and then execute only native code. It is an old invention which dates back to 1960. The earliest published JIT compiler is generally attributed to work on LISP (McCarthy, J. 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. After that Smalltalk pioneered new aspects of JIT compilations. For example, translation to machine code was done on demand, and the result was cached for later use. However, the concept is still relevant today as JIT compilation is considered vital for competitive interpreter-based implementations of modern languages, like Java, .NET, C# and ML etc.

JIT compilation is interesting because of the conflicting goals of producing quick code versus quickly producing code. In very simple means JIT compilation is a process of reverse-engineering the semantics of a program, and re-engineering the result back into binary code. The code is split up into blocks, some higher-level meaning is extracted from the current block of code, and native code is generated. It is used to improve the time and space efficiency of programs. A common goal of using JIT techniques is to reach or surpass the performance of static compilation, while maintaining the advantages of bytecode interpretation hence JIT compilation is used to gain the benefits of both static compilation and interpretation.

2. JIT Compilers

2.1. Overview

The just in time compilation is the amalgamation of two ideas found in runtime environments: Bytecode compilation and dynamic compilation. In a bytecode-compiled system, source code is translated to an intermediate representation known as bytecode. Bytecode is not the machine code for any particular computer, and may be portable among computer architectures. The bytecode may then be interpreted by, or run on, a virtual machine. The JIT compiler reads the bytecodes in many sections and compiles them dynamically into machine language so the program can run faster. (fig.1) .This can be done per-file, per-function or even on any arbitrary code fragment; the code can be compiled when it is about to be executed and then cached and reused later without needing to be recompiled and hence it is called just in time compilation.

[pic]

Fig 1. JIT Compilation

2.3. Classification

a) Invocation: A JIT compiler is explicitly invoked if the user must take some action to cause compilation at runtime. An implicitly invoked JIT compiler is transparent to the user.

b) Executability: JIT systems typically involve two languages: a source language to translate from, and a target language to translate to (although these languages can be the same, if the JIT system is only performing optimization on-the-fly). We call a JIT system monoexecutable if it can only execute one of these languages, and polyexecutable if can execute more than one. Polyexecutable JIT systems have the luxury of deciding when compiler invocation is warranted, since either program representation can be used.

c) Concurrency: This property characterizes how the JIT compiler executes, relative to the program itself. If program execution pauses under its own volition to permit compilation, it is not concurrent; the JIT compiler in this case may be invoked via subroutine call, message transmission, or transfer of control to a coroutine. In contrast, a concurrent JIT compiler can operate as the program executes concurrently: in a separate thread or process, even on a different processor.

2.3. Advantages

JIT has the capability to combine the advantages found both in interpretation and static compilation.
a) Improves performance: JIT is able to improve performance through caching results of blocks of code that has been translated – compared to simply re-evaluating every line or operand in the code each time that it occurs.
b) Recompiles the code: JIT is able to collect statistics about how the program is actually running in the environment it is in, and it can rearrange and recompile for optimum performance.
c) Greater portability: JIT systems have greater portability compared to other compilation techniques.
d) Adapting to run-time metrics: A JIT-compiler can not only look at the code and the target system, but also at how the code is used. It can instrument the running code, and make decisions about how to optimize according to.
e) Small Memory Footprint JIT compilation takes advantage of the possibility that some code may never be used. The JIT Compiler compiles methods only as needed.

3. JIT COMPILATION TECHNIQUES
A JIT compilation technique often focuses around implementation of particular programming languages. There are many programming languages in which just in time compilation can be implemented. Also several modern runtime environments, such as Microsoft's .NET Framework and most implementations of Java, rely on JIT compilation for high-speed code execution. Here I have discussed the just in time compilation on Microsoft's .NET Framework in detailed. 3.1. .NET Framework
In the .NET Framework, all the Microsoft .NET languages use a common language runtime, which helps to any language that is Microsoft .NET compatible on computer. The main advantage of the .NET Framework is the interoperability between different languages. As all the Microsoft .NET languages share the same common runtime language, they all work well together. When we compile a Microsoft.NET language, the complier generates code written in the Microsoft Intermediate Language (MSIL). MSIL is a set of instructions that can quickly be translated into native code. A Microsoft.NET application can be run only after the MSIL code is translated into native machine code.

3.2.Working
MSIL(MS Intermediate Language) can be executed only when it is converted by .net Framework Just in time (JIT) compiler to native code, which is CPU specific code that run on some computer architecture as the JIT compiler.(Fig 2) JIT compilation takes into account the fact that some code might never get called during execution .Rather than using time and memory to convert all the MSIL to native code, it converts the MSIL as it is needed during execution and stored in resulting native code so it is accessible for subsequent calls. The loader creates and attaches a stub to each of a type's methods when the type is loaded. On the initial call to the method, the stub passes control to the JIT compiler, which converts the MSIL for that method into native code and modifies the stub to direct execution to the location of the native code. Subsequent calls of the JIT-compiled method proceed directly to the native code that was previously generated, reducing the time it takes to JIT-compile and run the code.

[pic]
Fig 2. JIT compilation in .NET framework

The runtime supplies another mode of compilation called install-time code generation. The install-time code generation mode converts MSIL to native code just as the regular JIT compiler does, but it converts larger units of code at a time, storing the resulting native code for use when the assembly is subsequently loaded and executed. As part of compiling MSIL to native code, code must pass a verification process unless an administrator has established a security policy that allows code to bypass verification. Verification examines MSIL and metadata to find out whether the code can be determined to be type safe, which means that it is known to access only the memory locations it is authorized to access.

3.3. Types
In Microsoft .NET there are three types of JIT (Just-In-Time):

[pic]

Fig.3 Types of JIT compiler in .NET framework
a) Pre-JIT COMPILER: Pre-JIT compiles complete source code into native code in a single compilation cycle. This is done at the time of deployment of the application.
b) Econo-JIT COMPILER: Econo-JIT compiles only those methods that are called at runtime. However, these compiled methods are removed when they are not required.
c) Normal-JIT COMPILER: Normal-JIT compiles only those methods that are called at runtime. These methods are compiled the first time they are called, and then they are stored in cache. When the same methods are called again, the compiled code from cache is used for execution.

4. Challenges of JIT Compilation
a) Compiler Verification: A JIT compiler needs to correctly map its input programs down to concrete machine code. In this case the target must be real machine code ,not assembly code or intermediate code which most other verified compilers seem to output.
b) Non-static Code: Conventional static compilers can treat generated code purely as data, since execution of generated code is not done during compilation. However, JIT compilers switch between executions of static code and dynamically generated code; hence some data needs to be treated as code.
c) Self-modifying Code: The dynamically generated code might also cause self-modification: the generated code can, in incremental JIT compilers, invoke the code generator which may alter the code that called it. Code that can modify itself poses verification challenges that only few have tackled
5. Conclusion
JIT compilation is an old technique. It has received much attention in recent years. Just-in-time, compilation has advantage of improving the runtime performance of computer programs with smaller memory footprints. In this paper by giving brief details of JIT compilation, I have tried to explain the concept more broadly.

References:

1. Aycock, J. (June 2003). "A brief history of just-in-time". ACM Computing Surveys 35 (2): 97–113. doi:10.1145/857076.857077 2. Compiling MSIL to Native Code Available at:http://msdn.microsoft.com/en-us/library/ht8ecch6%28v=vs.71%29.aspx 3. McCarthy, J. (April 1960). "Recursive functions of symbolic expressions and their computation by machine, Part I". Communications of the ACM 3 (4): 184–195.

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