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LLVM 3.2 Release Notes

Written by the LLVM Team

These are in-progress notes for the upcoming LLVM 3.2 release. You may prefer the LLVM 3.1 Release Notes.

Introduction

This document contains the release notes for the LLVM Compiler Infrastructure, release 3.2. Here we describe the status of LLVM, including major improvements from the previous release, improvements in various subprojects of LLVM, and some of the current users of the code. 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 3.2 distribution currently consists of code from the core LLVM repository, which roughly includes the LLVM optimizers, code generators and supporting tools, and the Clang 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

Clang is an LLVM front end for the C, C++, and Objective-C languages. Clang aims to provide a better user experience through expressive diagnostics, a high level of conformance to language standards, fast compilation, and low memory use. Like LLVM, Clang provides a modular, library-based architecture that makes it suitable for creating or integrating with other development tools. Clang is considered a production-quality compiler for C, Objective-C, C++ and Objective-C++ on x86 (32- and 64-bit), and for Darwin/ARM targets.

In the LLVM 3.2 time-frame, the Clang team has made many improvements. Highlights include:

  1. More powerful warnings, especially -Wuninitialized
  2. Template type diffing in diagnostic messages
  3. Higher quality and more efficient debug info generation

For more details about the changes to Clang since the 3.1 release, see the Clang release notes.

If Clang rejects your code but another compiler accepts it, please take a look at the language compatibility guide to make sure this is not intentional or a known issue.

DragonEgg: GCC front-ends, LLVM back-end

DragonEgg is a gcc plugin that replaces GCC's optimizers and code generators with LLVM's. It works with gcc-4.5 and gcc-4.6 (and partially with gcc-4.7), can target the x86-32/x86-64 and ARM processor families, and has been successfully used on the Darwin, FreeBSD, KFreeBSD, Linux and OpenBSD platforms. It fully supports Ada, C, C++ and Fortran. It has partial support for Go, Java, Obj-C and Obj-C++.

The 3.2 release has the following notable changes:

  1. Able to load LLVM plugins such as Polly.
  2. Supports thread-local storage models.
  3. Passes knowledge of variable lifetimes to the LLVM optimizers.
  4. No longer requires GCC to be built with LTO support.

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).

The 3.2 release has the following notable changes:

  1. ...

LLDB: Low Level Debugger

LLDB is a ground-up implementation of a command line debugger, as well as a debugger API that can be used from other applications. LLDB makes use of the Clang parser to provide high-fidelity expression parsing (particularly for C++) and uses the LLVM JIT for target support.

The 3.2 release has the following notable changes:

  1. ...

libc++: C++ Standard Library

Like compiler_rt, libc++ is now :ref:`dual licensed <copyright-license-patents>` under the MIT and UIUC license, allowing it to be used more permissively.

Within the LLVM 3.2 time-frame there were the following highlights:

  1. ...

VMKit

The VMKit project is an implementation of a Java Virtual Machine (Java VM or JVM) that uses LLVM for static and just-in-time compilation.

The 3.2 release has the following notable changes:

  1. ...

Polly: Polyhedral Optimizer

Polly is an experimental optimizer for data locality and parallelism. It provides high-level loop optimizations and automatic parallelisation.

Within the LLVM 3.2 time-frame there were the following highlights:

  1. isl, the integer set library used by Polly, was relicensed to the MIT license
  2. isl based code generation
  3. MIT licensed replacement for CLooG (LGPLv2)
  4. Fine grained option handling (separation of core and border computations, control overhead vs. code size)
  5. Support for FORTRAN and dragonegg
  6. OpenMP code generation fixes

External Open Source Projects Using LLVM 3.2

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 3.2.

Crack

Crack aims to provide the ease of development of a scripting language with the performance of a compiled language. The language derives concepts from C++, Java and Python, incorporating object-oriented programming, operator overloading and strong typing.

FAUST

FAUST is a compiled language for real-time audio signal processing. The name FAUST stands for Functional AUdio STream. Its programming model combines two approaches: functional programming and block diagram composition. In addition with the C, C++, Java, JavaScript output formats, the Faust compiler can generate LLVM bitcode, and works with LLVM 2.7-3.1.

Glasgow Haskell Compiler (GHC)

GHC is an open source compiler and programming suite for Haskell, a lazy functional programming language. It includes an optimizing static compiler generating good code for a variety of platforms, together with an interactive system for convenient, quick development.

GHC 7.0 and onwards include an LLVM code generator, supporting LLVM 2.8 and later.

Julia

Julia is a high-level, high-performance dynamic language for technical computing. It provides a sophisticated compiler, distributed parallel execution, numerical accuracy, and an extensive mathematical function library. The compiler uses type inference to generate fast code without any type declarations, and uses LLVM's optimization passes and JIT compiler. The Julia Language is designed around multiple dispatch, giving programs a large degree of flexibility. It is ready for use on many kinds of problems.

LLVM D Compiler

LLVM D Compiler (LDC) is a compiler for the D programming Language. It is based on the DMD frontend and uses LLVM as backend.

Open Shading Language

Open Shading Language (OSL) is a small but rich language for programmable shading in advanced global illumination renderers and other applications, ideal for describing materials, lights, displacement, and pattern generation. It uses LLVM to JIT complex shader networks to x86 code at runtime.

OSL was developed by Sony Pictures Imageworks for use in its in-house renderer used for feature film animation and visual effects, and is distributed as open source software with the "New BSD" license.

Portable OpenCL (pocl)

In addition to producing an easily portable open source OpenCL implementation, another major goal of pocl is improving performance portability of OpenCL programs with compiler optimizations, reducing the need for target-dependent manual optimizations. An important part of pocl is a set of LLVM passes used to statically parallelize multiple work-items with the kernel compiler, even in the presence of work-group barriers. This enables static parallelization of the fine-grained static concurrency in the work groups in multiple ways (SIMD, VLIW, superscalar, ...).

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. The interpreter uses LLVM as a backend to JIT-compile Pure programs to fast native code. 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 interface to C and other programming languages (including the ability to load LLVM bitcode modules, and inline C, C++, Fortran and Faust code in Pure programs if the corresponding LLVM-enabled compilers are installed).

Pure version 0.54 has been tested and is known to work with LLVM 3.1 (and continues to work with older LLVM releases >= 2.5).

TTA-based Co-design 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/Verilog and parallel program binaries. Processor customization points include the register files, function units, supported operations, and the interconnection network.

TCE uses 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.

What's New in LLVM 3.2?

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.

Major New Features

Features that need text if they're finished for 3.2:
ARM EHABI combiner-aa? strong phi elim loop dependence analysis CorrelatedValuePropagation Integrated assembler on by default for arm/thumb?
Near dead:
Analysis/RegionInfo.h + Dom Frontiers SparseBitVector: used in LiveVar. llvm/lib/Archive - replace with lib object?

LLVM 3.2 includes several major changes and big features:

  1. New NVPTX back-end (replacing existing PTX back-end) based on NVIDIA sources
  2. ...

LLVM IR and Core Improvements

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

  1. Thread local variables may have a specified TLS model. See the :ref:`Language Reference Manual <globalvars>`.
  2. ...

Optimizer Improvements

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

Loop Vectorizer - We've added a loop vectorizer and we are now able to vectorize small loops. The loop vectorizer is disabled by default and can be enabled using the -mllvm -vectorize-loops flag. The SIMD vector width can be specified using the flag -mllvm -force-vector-width=4. The default value is 0 which means auto-select.

We can now vectorize this function:

unsigned sum_arrays(int *A, int *B, int start, int end) {
  unsigned sum = 0;
  for (int i = start; i < end; ++i)
    sum += A[i] + B[i] + i;
  return sum;
}

We vectorize under the following loops:

  1. The inner most loops must have a single basic block.
  2. The number of iterations are known before the loop starts to execute.
  3. The loop counter needs to be incremented by one.
  4. The loop trip count can be a variable.
  5. Loops do not need to start at zero.
  6. The induction variable can be used inside the loop.
  7. Loop reductions are supported.
  8. Arrays with affine access pattern do not need to be marked as 'noalias' and are checked at runtime.
  9. ...

SROA - We've re-written SROA to be significantly more powerful and generate code which is much more friendly to the rest of the optimization pipeline. Previously this pass had scaling problems that required it to only operate on relatively small aggregates, and at times it would mistakenly replace a large aggregate with a single very large integer in order to make it a scalar SSA value. The result was a large number of i1024 and i2048 values representing any small stack buffer. These in turn slowed down many subsequent optimization paths.

The new SROA pass uses a different algorithm that allows it to only promote to scalars the pieces of the aggregate actively in use. Because of this it doesn't require any thresholds. It also always deduces the scalar values from the uses of the aggregate rather than the specific LLVM type of the aggregate. These features combine to both optimize more code with the pass but to improve the compile time of many functions dramatically.

  1. Branch weight metadata is preseved through more of the optimizer.
  2. ...

MC Level Improvements

The LLVM Machine Code (aka MC) subsystem 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. For more information, please see the Intro to the LLVM MC Project Blog Post.

  1. ...

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:

  1. ...

Stack Coloring - We have implemented a new optimization pass to merge stack objects which are used in disjoin areas of the code. This optimization reduces the required stack space significantly, in cases where it is clear to the optimizer that the stack slot is not shared. We use the lifetime markers to tell the codegen that a certain alloca is used within a region.

We now merge consecutive loads and stores.

X86-32 and X86-64 Target Improvements

New features and major changes in the X86 target include:

  1. ...

ARM Target Improvements

New features of the ARM target include:

  1. ...

MIPS Target Improvements

New features and major changes in the MIPS target include:

  1. ...

PowerPC Target Improvements

Many fixes and changes across LLVM (and Clang) for better compliance with the 64-bit PowerPC ELF Application Binary Interface, interoperability with GCC, and overall 64-bit PowerPC support. Some highlights include:

  1. MCJIT support added.
  2. PPC64 relocation support and (small code model) TOC handling added.
  3. Parameter passing and return value fixes (alignment issues, padding, varargs support, proper register usage, odd-sized structure support, float support, extension of return values for i32 return values).
  4. Fixes in spill and reload code for vector registers.
  5. C++ exception handling enabled.
  6. Changes to remediate double-rounding compatibility issues with respect to GCC behavior.
  7. Refactoring to disentangle ppc64-elf-linux ABI from Darwin ppc64 ABI support.
  8. Assorted new test cases and test case fixes (endian and word size issues).
  9. Fixes for big-endian codegen bugs, instruction encodings, and instruction constraints.
  10. Implemented -integrated-as support.
  11. Additional support for Altivec compare operations.
  12. IBM long double support.

There have also been code generation improvements for both 32- and 64-bit code. Instruction scheduling support for the Freescale e500mc and e5500 cores has been added.

PTX/NVPTX Target Improvements

The PTX back-end has been replaced by the NVPTX back-end, which is based on the LLVM back-end used by NVIDIA in their CUDA (nvcc) and OpenCL compiler. Some highlights include:

  1. Compatibility with PTX 3.1 and SM 3.5.
  2. Support for NVVM intrinsics as defined in the NVIDIA Compiler SDK.
  3. Full compatibility with old PTX back-end, with much greater coverage of LLVM SIR.

Please submit any back-end bugs to the LLVM Bugzilla site.

Major Changes and Removed Features

If you're already an LLVM user or developer with out-of-tree changes based on LLVM 3.2, this section lists some "gotchas" that you may run into upgrading from the previous release.

  1. The CellSPU port has been removed. It can still be found in older versions.
  2. ...

Internal API Changes

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

We've added a new interface for allowing IR-level passes to access target-specific information. A new IR-level pass, called TargetTransformInfo provides a number of low-level interfaces. LSR and LowerInvoke already use the new interface.

The TargetData structure has been renamed to DataLayout and moved to VMCore to remove a dependency on Target.

  1. ...

Tools Changes

In addition, some tools have changed in this release. Some of the changes are:

  1. ...

Python Bindings

Officially supported Python bindings have been added! Feature support is far from complete. The current bindings support interfaces to:

  1. ...

Known Problems

LLVM is generally a production quality compiler, and is used by a broad range of applications and shipping in many products. That said, not every subsystem is as mature as the aggregate, particularly the more obscure1 targets. If you run into a problem, please check the LLVM bug database and submit a bug if there isn't already one or ask on the LLVMdev list.

Known problem areas include:

  1. The MSP430 and XCore backends are experimental.
  2. The integrated assembler, disassembler, and JIT is not supported by several targets. If an integrated assembler is not supported, then a system assembler is required. For more details, see the :ref:`target-feature-matrix`.

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/docs/ directory in the LLVM tree.

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