One VM to Rule Them All
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The document discusses creating a high-performance virtual machine (VM) architecture that can easily implement VMs for new languages. It introduces Truffle, a language implementation framework, and Graal, a compilation infrastructure. With Truffle and Graal, language implementers can write interpreters for their languages and reusable services will provide a high-performance VM without requiring extensive work in compiler optimization. The guest language interpreter is partially evaluated and optimized based on profiling information during execution.
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Chapter 1
Introduction
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between compiler design and computer-science theory and an outline of the
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Simply stated, a compiler is a program that can read a program in one language - the source language - and translate it into an equivalent program in
another language - the target language; see Fig. 1.1. An important role of the
compiler is to report any errors in the source program that it detects during
the translation proc....
If the target program is an executable machine-language program, it can
then be called by the user to process inputs and produce outputs; see Fig. 1.2.
Target Program output tFigure 1.2: Running the target program
An interpreter is another common kind of language processor. Instead of
producing a target program as a translation, an interpreter appears to directly
execute the operations specified in the source program on inputs supplied by
the user, as shown in Fig. 1.3.
source program 1 Interpreter t- output input
Figure 1.3: An interpreter
The machine-language target program produced by a compiler is usually
much faster than an interpreter at mapping inputs to outputs . An interpreter,
however, can usually give better error diagnostics than a compiler, because it
executes the source program statement by statement.
Example 1.1 : Java language processors combine compilation and interpretation, as shown in Fig. 1.4. A Java source program may first be compiled into
an intermediate form called bytecodes. The bytecodes are tinto machine language
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1. The document discusses the different phases of a compiler, including lexical analysis, syntax analysis, semantic analysis, code optimization, and code generation.
2. It provides examples and explanations of each phase, describing how the compiler processes source code through each step to produce executable machine code.
3. The phases involve breaking source code into tokens, checking syntax and semantics, generating intermediate code, optimizing for efficiency, and finally mapping to target machine language instructions.
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The document discusses three computer language translators: compilers, interpreters, and assemblers. [1] A compiler translates high-level code into machine code for faster execution, while an interpreter executes code line-by-line which is slower but allows for quicker testing. [2] An assembler directly translates assembly language instructions into machine code through a 1:1 mapping of mnemonics to instructions. [3] Compilers produce standalone executable programs while interpreters are useful for learning and debugging through a read-check-execute loop.
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A compiler is a computer program that translates a program written in a source language into an equivalent program in a target language. The compilation process involves scanning the source code, parsing it, performing semantic analysis, generating intermediate code, optimizing the code, and finally generating the target code. Key data structures used in compilers include symbol tables to store information about identifiers, literal tables to store constants, and parse trees to represent the syntactic structure of the program.
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Presentation about Compiler - Computer Programming - University of Zakho ... College of Engineering - Petroleum Department
Transpilers(Source-to-Source Compilers)
A transpiler is a type of compiler that takes source code from one programming language and outputs source code in another programming language, while a compiler converts source code directly into machine code. Transpilers allow code to be translated between languages at similar levels of abstraction, such as C++ to C, while compilers translate to a lower level like C to assembly code. Transpilers are useful for porting codebases to new languages, translating between language versions, or implementing domain-specific languages. Popular transpilers include Babel, TypeScript, and Emscripten.
ProgrammingIntroduction.ppt
This document provides an introduction to programming languages. It discusses the different generations of programming languages from machine language to high-level languages like C++ and Java. It also covers the differences between interpreters and compilers and the basic steps involved in implementing a programming language which are scanning, parsing, and code generation.
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4_5802928814682016556.pptx
The document summarizes key concepts about compiler design. It defines a compiler as a program that translates source code written in one language into an equivalent executable program in another language. Compilers are classified based on the number of passes, such as single-pass and multi-pass compilers. The document also discusses the analysis-synthesis model of compilation, which involves analyzing the source program to create an intermediate representation, then synthesizing target code from that representation. Major phases of a compiler include lexical analysis, parsing, semantic analysis, code generation, and optimization.
CD - CH1 - Introduction to compiler design.pptx
The document summarizes key concepts about compiler design. It defines a compiler as a program that translates source code written in one language into an equivalent executable program in another language. Compilers are classified based on the number of passes they use, such as single-pass and multi-pass compilers. The analysis-synthesis model is described as the two-part process of compilation involving analysis of the source program and synthesis of the translated code. The phases of a compiler include lexical analysis, parsing, semantic analysis, code generation and optimization.
Cd ch1 - introduction
The document discusses the phases of a compiler. It describes the phases as:
1) Lexical analysis which converts source code into tokens.
2) Syntax analysis which checks the syntax is correct and builds a parse tree.
3) Semantic analysis which checks for semantic errors using symbol tables.
4) Intermediate code generation which converts the parse tree into an intermediate representation.
5) Optimization of the intermediate code.
6) Code generation which converts the optimized intermediate code into assembly code and then machine code.
Lect 1. introduction to programming languages
A programming language is a set of rules that allows humans to communicate instructions to computers. There are many programming languages because they have evolved over time as better ways to design them have been developed. Programming languages can be categorized based on their generation or programming paradigm such as imperative, object-oriented, logic-based, and functional. Characteristics like writability, readability, reliability and maintainability are important qualities for programming languages.
Passes of Compiler.pptx
A presentation of Compiler Design on the topic Passes. It include one pass, two pass and multi-pass. It also include comparison between single pass and multi-pass compiler and use cases of both the compiler.
Passes of compilers
There are two types of compiler passes: multi-pass compilers perform multiple traversals of the source code to perform different stages of compilation like scanning, parsing, semantic analysis, etc. One-pass compilers only traverse the source code once, performing all compilation stages on each line before moving to the next.
Bootstrapping is the process of using a compiler written in a language to compile itself, allowing the creation of a self-hosting compiler for that language. It involves first creating a simple bootstrap compiler for a language subset, then using that to compile a full compiler for the language which can then compile future versions.
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One VM to Rule Them All
- 1. One VM to Rule Them All Tianxiang Xiong
- 2. Background ● A small number of languages have high-perf VMs ○ E.g. Java, C# ● Many languages have low-perf VMs ○ Ruby, Python, R, MATLAB, PHP… ● High-perf VMs are currently: ○ Highly complex ○ Biased towards a single language or family of languages
- 3. Big Idea ● Create architecture for easily implementing high-perf VMs for new languages 1. Language implementer writes interpreter 2. *A miracle occurs* 3. High-performance VM
- 4. Truffle and Graal ● Truffle--language implementation framework ● Graal--compilation infrastructure ● VMs for many guest languages implemented in a managed host language ○ Only guest-specific parts are written by language implementer ○ Reusable host services are provided by framework ● Guest language (usually) dynamically typed
- 6. AST and Optimization ● Guest language implements AST interpreter ● Node rewriting--during interpretation, a node can replace itself w/ another, based on profiling feedback: ○ Dynamic type info ○ Execution freqs ○ Rate of node rewrites ● When compiler is evoked, it uses profiling info to partially evaluate the AST interpreter
- 7. AST and Deoptimization ● Parts of interpreter responsible for node rewriting are omitted from compilation ○ Branches that perform rewriting cause deoptimization ● Deoptimization--when type specialization fails, optimized code is discarded and execution reverts to interpreter ● More info is gathered during interpretation, followed by another round of partial evaluation, and so on
- 9. Node Rewriting Conditions ● Guest language developer is responsible for fulfilling conditions of node rewriting: ○ Completeness--node provides rewrites for all cases it does not handle ○ Finiteness--After finite # of node rewrites, must end up in state that handles full language semantics ○ Locality--a node can only rewrite itself and its subtree
- 10. Branch probabilities and loop freqs ● Guest lang interpreter author is also (optionally) responsible for providing: ○ Branch probabilities ○ Loop frequencies ● Interpreter can do profiling for optimizing compiler ○ If not, values are derived from host system during partial evaluation
- 11. Related Work ● PyPy ○ Big idea: write interpreter in high-level (less dynamic) lang, then generate custom VM, tracing dynamic compiler form interpreter ○ Python interpreter, VM written in RPython -> translated to C ● Self-optimizing interpreters ○ Compilers can perform optimizations beyond reach of interpreters ● Compile to IR (e.g. LLVM), e.g. Rubinius
- 12. TruffleClojure ● TruffleClojure ○ Master’s thesis, not ready for use ● Features: ○ Implements TCO (by avoiding Java bytecode) ○ Perf improvements via type specialization (e.g. of contains?)