LLVM 2.7 Release Notes
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  1. Introduction
  2. Sub-project Status Update
  3. External Projects Using LLVM 2.7
  4. What's New in LLVM 2.7?
  5. Installation Instructions
  6. Portability and Supported Platforms
  7. Known Problems
  8. Additional Information

Written by the LLVM Team

Introduction

This document contains the release notes for the LLVM Compiler Infrastructure, release 2.7. Here we describe the status of LLVM, including major improvements from the previous release and significant known problems. All LLVM releases may be downloaded from the LLVM releases web site.

For more information about LLVM, including information about the latest release, please check out the main LLVM web site. If you have questions or comments, the LLVM Developer's Mailing List is a good place to send them.

Note that if you are reading this file from a Subversion checkout or the main LLVM web page, this document applies to the next release, not the current one. To see the release notes for a specific release, please see the releases page.

Sub-project Status Update

The LLVM 2.7 distribution currently consists of code from the core LLVM repository (which roughly includes the LLVM optimizers, code generators and supporting tools), the Clang repository and the llvm-gcc repository. In addition to this code, the LLVM Project includes other sub-projects that are in development. Here we include updates on these subprojects.

Clang: C/C++/Objective-C Frontend Toolkit

The Clang project is ...

In the LLVM 2.7 time-frame, the Clang team has made many improvements:

Clang Static Analyzer

The Clang Static Analyzer project is an effort to use static source code analysis techniques to automatically find bugs in C and Objective-C programs (and hopefully C++ in the future!). The tool is very good at finding bugs that occur on specific paths through code, such as on error conditions.

In the LLVM 2.7 time-frame, the analyzer core has made several major and minor improvements, including better support for tracking the fields of structures, initial support (not enabled by default yet) for doing interprocedural (cross-function) analysis, and new checks have been added.

VMKit: JVM/CLI Virtual Machine Implementation

The VMKit project is an implementation of a JVM and a CLI Virtual Machine (Microsoft .NET is an implementation of the CLI) using LLVM for static and just-in-time compilation.

With the release of LLVM 2.7, VMKit has shifted to a great framework for writing virtual machines. VMKit now offers precise and efficient garbage collection with multi-threading support, thanks to the MMTk memory management toolkit, as well as just in time and ahead of time compilation with LLVM. The major changes in VMKit 0.27 are:

compiler-rt: Compiler Runtime Library

The new LLVM compiler-rt project is a simple library that provides an implementation of the low-level target-specific hooks required by code generation and other runtime components. For example, when compiling for a 32-bit target, converting a double to a 64-bit unsigned integer is compiled into a runtime call to the "__fixunsdfdi" function. The compiler-rt library provides highly optimized implementations of this and other low-level routines (some are 3x faster than the equivalent libgcc routines).

All of the code in the compiler-rt project is available under the standard LLVM License, a "BSD-style" license. New in LLVM 2.7: compiler_rt now supports ARM targets.

DragonEgg: llvm-gcc ported to gcc-4.5

DragonEgg is a port of llvm-gcc to gcc-4.5. Unlike llvm-gcc, which makes many intrusive changes to the underlying gcc-4.2 code, dragonegg in theory does not require any gcc-4.5 modifications whatsoever (currently one small patch is needed). This is thanks to the new gcc plugin architecture, which makes it possible to modify the behaviour of gcc at runtime by loading a plugin, which is nothing more than a dynamic library which conforms to the gcc plugin interface. DragonEgg is a gcc plugin that causes the LLVM optimizers to be run instead of the gcc optimizers, and the LLVM code generators instead of the gcc code generators, just like llvm-gcc. To use it, you add "-fplugin=path/dragonegg.so" to the gcc-4.5 command line, and gcc-4.5 magically becomes llvm-gcc-4.5!

DragonEgg is still a work in progress. Currently C works very well, while C++, Ada and Fortran work fairly well. All other languages either don't work at all, or only work poorly. For the moment only the x86-32 and x86-64 targets are supported, and only on linux and darwin (darwin needs an additional gcc patch).

DragonEgg is a new project which is seeing its first release with llvm-2.7.

llvm-mc: Machine Code Toolkit

The LLVM Machine Code (aka MC) sub-project of LLVM was created to solve a number of problems in the realm of assembly, disassembly, object file format handling, and a number of other related areas that CPU instruction-set level tools work in. It is a sub-project of LLVM which provides it with a number of advantages over other compilers that do not have tightly integrated assembly-level tools. For a gentle introduction, please see the Intro to the LLVM MC Project Blog Post.

2.7 includes major parts of the work required by the new MC Project. A few targets have been refactored to support it, and work is underway to support a native assembler in LLVM. This work is not complete in LLVM 2.7, but you has made substantially more progress on LLVM mainline.

One minor example of what MC can do is to transcode an AT&T syntax X86 .s file into intel syntax. You can do this with something like:

  llvm-mc foo.s -output-asm-variant=1 -o foo-intel.s
External Open Source Projects Using LLVM 2.7

An exciting aspect of LLVM is that it is used as an enabling technology for a lot of other language and tools projects. This section lists some of the projects that have already been updated to work with LLVM 2.7.

Pure

Pure is an algebraic/functional programming language based on term rewriting. Programs are collections of equations which are used to evaluate expressions in a symbolic fashion. Pure offers dynamic typing, eager and lazy evaluation, lexical closures, a hygienic macro system (also based on term rewriting), built-in list and matrix support (including list and matrix comprehensions) and an easy-to-use C interface. The interpreter uses LLVM as a backend to JIT-compile Pure programs to fast native code.

Pure versions 0.43 and later have been tested and are known to work with LLVM 2.7 (and continue to work with older LLVM releases >= 2.5).

Roadsend PHP

Roadsend PHP (rphp) is an open source implementation of the PHP programming language that uses LLVM for its optimizer, JIT and static compiler. This is a reimplementation of an earlier project that is now based on LLVM.

Unladen Swallow

Unladen Swallow is a branch of Python intended to be fully compatible and significantly faster. It uses LLVM's optimization passes and JIT compiler.

TTA-based Codesign Environment (TCE)

TCE is a toolset for designing application-specific processors (ASP) based on the Transport triggered architecture (TTA). The toolset provides a complete co-design flow from C/C++ programs down to synthesizable VHDL and parallel program binaries. Processor customization points include the register files, function units, supported operations, and the interconnection network.

TCE uses llvm-gcc/Clang and LLVM for C/C++ language support, target independent optimizations and also for parts of code generation. It generates new LLVM-based code generators "on the fly" for the designed TTA processors and loads them in to the compiler backend as runtime libraries to avoid per-target recompilation of larger parts of the compiler chain.

SAFECode Compiler

SAFECode is a memory safe C compiler built using LLVM. It takes standard, unannotated C code, analyzes the code to ensure that memory accesses and array indexing operations are safe, and instruments the code with run-time checks when safety cannot be proven statically.

IcedTea Java Virtual Machine Implementation

IcedTea provides a harness to build OpenJDK using only free software build tools and to provide replacements for the not-yet free parts of OpenJDK. One of the extensions that IcedTea provides is a new JIT compiler named Shark which uses LLVM to provide native code generation without introducing processor-dependent code.

Icedtea6 1.8 and later have been tested and are known to work with LLVM 2.7 (and continue to work with older LLVM releases >= 2.6 as well).

LLVM-Lua

LLVM-Lua uses LLVM to add JIT and static compiling support to the Lua VM. Lua bytecode is analyzed to remove type checks, then LLVM is used to compile the bytecode down to machine code.

LLVM-Lua 1.2.0 have been tested and is known to work with LLVM 2.7.

What's New in LLVM 2.7?

This release includes a huge number of bug fixes, performance tweaks and minor improvements. Some of the major improvements and new features are listed in this section.

LLVM Community Changes

In addition to changes to the code, between LLVM 2.6 and 2.7, a number of organization changes have happened:

Major New Features

LLVM 2.7 includes several major new capabilities:

LLVM IR and Core Improvements

LLVM IR has several new features for better support of new targets and that expose new optimization opportunities:

Optimizer Improvements

In addition to a large array of minor performance tweaks and bug fixes, this release includes a few major enhancements and additions to the optimizers:

Interpreter and JIT Improvements
Target Independent Code Generator Improvements

We have put a significant amount of work into the code generator infrastructure, which allows us to implement more aggressive algorithms and make it run faster:

X86-32 and X86-64 Target Improvements

New features of the X86 target include:

ARM Target Improvements

New features of the ARM target include:

New Useful APIs

This release includes a number of new APIs that are used internally, which may also be useful for external clients.

Other Improvements and New Features

Other miscellaneous features include:

Major Changes and Removed Features

If you're already an LLVM user or developer with out-of-tree changes based on LLVM 2.6, this section lists some "gotchas" that you may run into upgrading from the previous release.

In addition, many APIs have changed in this release. Some of the major LLVM API changes are:

Portability and Supported Platforms

LLVM is known to work on the following platforms:

The core LLVM infrastructure uses GNU autoconf to adapt itself to the machine and operating system on which it is built. However, minor porting may be required to get LLVM to work on new platforms. We welcome your portability patches and reports of successful builds or error messages.

Known Problems

This section contains significant known problems with the LLVM system, listed by component. If you run into a problem, please check the LLVM bug database and submit a bug if there isn't already one.

Experimental features included with this release

The following components of this LLVM release are either untested, known to be broken or unreliable, or are in early development. These components should not be relied on, and bugs should not be filed against them, but they may be useful to some people. In particular, if you would like to work on one of these components, please contact us on the LLVMdev list.

Known problems with the X86 back-end
Known problems with the PowerPC back-end
Known problems with the ARM back-end
Known problems with the SPARC back-end
Known problems with the MIPS back-end
Known problems with the Alpha back-end
Known problems with the C back-end
Known problems with the llvm-gcc C and C++ front-end

The only major language feature of GCC not supported by llvm-gcc is the __builtin_apply family of builtins. However, some extensions are only supported on some targets. For example, trampolines are only supported on some targets (these are used when you take the address of a nested function).

Known problems with the llvm-gcc Fortran front-end
Known problems with the llvm-gcc Ada front-end
The llvm-gcc 4.2 Ada compiler works fairly well; however, this is not a mature technology, and problems should be expected.
Additional Information

A wide variety of additional information is available on the LLVM web page, in particular in the documentation section. The web page also contains versions of the API documentation which is up-to-date with the Subversion version of the source code. You can access versions of these documents specific to this release by going into the "llvm/doc/" directory in the LLVM tree.

If you have any questions or comments about LLVM, please feel free to contact us via the mailing lists.


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