GSoC/GCI Archive
GSoC/GCI Archive
Google Summer of Code 2015

LLVM Compiler Infrastructure

License: University of Illinois/NCSA Open Source License

Web Page: http://llvm.org/OpenProjects.html

Mailing List: http://lists.cs.uiuc.edu/mailman/listinfo/llvmdev

The LLVM Project is a collection of modular and reusable compiler and toolchain technologies. Despite its name, LLVM has little to do with traditional virtual machines, though it does provide helpful libraries that can be used to build them.

LLVM began as a research project at the University of Illinois, with the goal of providing a modern, SSA-based compilation strategy capable of supporting both static and dynamic compilation of arbitrary programming languages. Since then, LLVM has grown to be an umbrella project consisting of a number of different subprojects, many of which are being used in production by a wide variety of commercial and open sourceprojects as well as being widely used in academic research. Code in the LLVM project is licensed under the "UIUC" BSD-Style license.

The primary sub-projects of LLVM are:

  1. The LLVM Core libraries provide a modern source- and target-independent optimizer, along with code generation support for many popular CPUs (as well as some less common ones!) These libraries are built around a well specified code representation known as the LLVM intermediate representation ("LLVM IR"). The LLVM Core libraries are well documented, and it is particularly easy to invent your own language (or port an existing compiler) to use LLVM as an optimizer and code generator.

  2. Clang is an "LLVM native" C/C++/Objective-C compiler, which aims to deliver amazingly fast compiles (e.g. about 3x faster than GCCwhen compiling Objective-C code in a debug configuration), extremely useful error and warning messages and to provide a platform for building great source level tools. The Clang Static Analyzer is a tool that automatically finds bugs in your code, and is a great example of the sort of tool that can be built using the Clang frontend as a library to parse C/C++ code.

  3. dragonegg integrates the LLVM optimizers and code generator with the GCC 4.5 parsers. This allows LLVM to compile Ada, Fortran, and other languages supported by the GCC compiler frontends, and access to C features not supported by Clang (such as OpenMP).

  4. The LLDB project builds on libraries provided by LLVM and Clang to provide a great native debugger. It uses the Clang ASTs and expression parser, LLVM JIT, LLVM disassembler, etc so that it provides an experience that "just works". It is also blazing fast and much more memory efficient than GDB at loading symbols.

  5. The libc++ and libc++ ABI projects provide a standard conformant and high-performance implementation of the C++ Standard Library, including full support for C++'0x.

  6. The compiler-rt project provides highly tuned implementations of the low-level code generator support routines like "__fixunsdfdi" and other calls generated when a target doesn't have a short sequence of native instructions to implement a core IR operation.

  7. The vmkit project is an implementation of the Java and .NET Virtual Machines that is built on LLVM technologies.

  8. The polly project implements a suite of cache-locality optimizations as well as auto-parallelism and vectorization using a polyhedral model.

  9. The libclc project aims to implement the OpenCL standard library.

  10. The klee project implements a "symbolic virtual machine" which uses a theorem prover to try to evaluate all dynamic paths through a program in an effort to find bugs and to prove properties of functions. A major feature of klee is that it can produce a testcase in the event that it detects a bug.

  11. The SAFECode project is a memory safety compiler for C/C++ programs. It instruments code with run-time checks to detect memory safety errors (e.g., buffer overflows) at run-time. It can be used to protect software from security attacks and can also be used as a memory safety error debugging tool like Valgrind.

In addition to official subprojects of LLVM, there are a broad variety of other projects that use components of LLVM for various tasks. Through these external projects you can use LLVM to compile Ruby, Python, Haskell, Java, D, PHP, Pure, Lua, and a number of other languages. A major strength of LLVM is its versatility, flexibility, and reusability, which is why it is being used for such a wide variety of different tasks: everything from doing light-weight JIT compiles of embedded languages like Lua to compiling Fortran code for massive super computers.

As much as everything else, LLVM has a broad and friendly community of people who are interested in building great low-level tools. If you are interested in getting involved, a good first place is to skim the LLVM Blog and to sign up for the LLVM Developer mailing list. For information on how to send in a patch, get commit access, and copyright and license topics, please see the LLVM Developer Policy.

Projects

  • Application for the The LLVM's "Copy-paste detection" project The application was written in markdown format and can be found on the Gist, the link is attached below. It is advised to read it on the Gist as it has better Markdown support than this application form.
  • Compile-Time Optimizations in Polly Improving the compile-time of polyhedral compilation tools and Polly has been an issue for some time. However, recently, lot of progress has been made. The aim of this project is to improve the compile-time of Polly by a large-factor. Some of the prominent changes I plan to make are: changes to the representations in the Integer Set Library (ISL) that Polly uses, and to modify the position of Polly in LLVM pass pipeline and it’s interactions with other passes.
  • Detecting Redundant Operations with LLVM An operation is classified as redundant if it is either 1) unneeded thus can be simply omitted without changing the program's output; or 2) repeated, which means the result of it is the same as a former run. The prevalent existence of these redundancies is a main cause of performance bugs. I intend to detect them by 1) identifying the redundant operations on instruction granularity with LLVM; and then 2) aggregating them into high-level blocks that worth fixing.