Bringing Clang and LLVM to Visual C++ Users
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The LLVM Instruction Set and Compilation Strategy
The LLVM Instruction Set and Compilation Strategy Chris Lattner Vikram Adve University of Illinois at Urbana-Champaign lattner,vadve ¡ @cs.uiuc.edu Abstract This document introduces the LLVM compiler infrastructure and instruction set, a simple approach that enables sophisticated code transformations at link time, runtime, and in the field. It is a pragmatic approach to compilation, interfering with programmers and tools as little as possible, while still retaining extensive high-level information from source-level compilers for later stages of an application’s lifetime. We describe the LLVM instruction set, the design of the LLVM system, and some of its key components. 1 Introduction Modern programming languages and software practices aim to support more reliable, flexible, and powerful software applications, increase programmer productivity, and provide higher level semantic information to the compiler. Un- fortunately, traditional approaches to compilation either fail to extract sufficient performance from the program (by not using interprocedural analysis or profile information) or interfere with the build process substantially (by requiring build scripts to be modified for either profiling or interprocedural optimization). Furthermore, they do not support optimization either at runtime or after an application has been installed at an end-user’s site, when the most relevant information about actual usage patterns would be available. The LLVM Compilation Strategy is designed to enable effective multi-stage optimization (at compile-time, link-time, runtime, and offline) and more effective profile-driven optimization, and to do so without changes to the traditional build process or programmer intervention. LLVM (Low Level Virtual Machine) is a compilation strategy that uses a low-level virtual instruction set with rich type information as a common code representation for all phases of compilation. -
What Is LLVM? and a Status Update
What is LLVM? And a Status Update. Approved for public release Hal Finkel Leadership Computing Facility Argonne National Laboratory Clang, LLVM, etc. ✔ LLVM is a liberally-licensed(*) infrastructure for creating compilers, other toolchain components, and JIT compilation engines. ✔ Clang is a modern C++ frontend for LLVM ✔ LLVM and Clang will play significant roles in exascale computing systems! (*) Now under the Apache 2 license with the LLVM Exception LLVM/Clang is both a research platform and a production-quality compiler. 2 A role in exascale? Current/Future HPC vendors are already involved (plus many others)... Apple + Google Intel (Many millions invested annually) + many others (Qualcomm, Sony, Microsoft, Facebook, Ericcson, etc.) ARM LLVM IBM Cray NVIDIA (and PGI) Academia, Labs, etc. AMD 3 What is LLVM: LLVM is a multi-architecture infrastructure for constructing compilers and other toolchain components. LLVM is not a “low-level virtual machine”! LLVM IR Architecture-independent simplification Architecture-aware optimization (e.g. vectorization) Assembly printing, binary generation, or JIT execution Backends (Type legalization, instruction selection, register allocation, etc.) 4 What is Clang: LLVM IR Clang is a C++ frontend for LLVM... Code generation Parsing and C++ Source semantic analysis (C++14, C11, etc.) Static analysis ● For basic compilation, Clang works just like gcc – using clang instead of gcc, or clang++ instead of g++, in your makefile will likely “just work.” ● Clang has a scalable LTO, check out: https://clang.llvm.org/docs/ThinLTO.html 5 The core LLVM compiler-infrastructure components are one of the subprojects in the LLVM project. These components are also referred to as “LLVM.” 6 What About Flang? ● Started as a collaboration between DOE and NVIDIA/PGI. -
CUDA Flux: a Lightweight Instruction Profiler for CUDA Applications
CUDA Flux: A Lightweight Instruction Profiler for CUDA Applications Lorenz Braun Holger Froning¨ Institute of Computer Engineering Institute of Computer Engineering Heidelberg University Heidelberg University Heidelberg, Germany Heidelberg, Germany [email protected] [email protected] Abstract—GPUs are powerful, massively parallel processors, hardware, it lacks verbosity when it comes to analyzing the which require a vast amount of thread parallelism to keep their different types of instructions executed. This problem is aggra- thousands of execution units busy, and to tolerate latency when vated by the recently frequent introduction of new instructions, accessing its high-throughput memory system. Understanding the behavior of massively threaded GPU programs can be for instance floating point operations with reduced precision difficult, even though recent GPUs provide an abundance of or special function operations including Tensor Cores for ma- hardware performance counters, which collect statistics about chine learning. Similarly, information on the use of vectorized certain events. Profiling tools that assist the user in such analysis operations is often lost. Characterizing workloads on PTX for their GPUs, like NVIDIA’s nvprof and cupti, are state-of- level is desirable as PTX allows us to determine the exact types the-art. However, instrumentation based on reading hardware performance counters can be slow, in particular when the number of the instructions a kernel executes. On the contrary, nvprof of metrics is large. Furthermore, the results can be inaccurate as metrics are based on a lower-level representation called SASS. instructions are grouped to match the available set of hardware Still, even if there was an exact mapping, some information on counters. -
Implementing Continuation Based Language in LLVM and Clang
Implementing Continuation based language in LLVM and Clang Kaito TOKUMORI Shinji KONO University of the Ryukyus University of the Ryukyus Email: [email protected] Email: [email protected] Abstract—The programming paradigm which use data seg- 1 __code f(Allocate allocate){ 2 allocate.size = 0; ments and code segments are proposed. This paradigm uses 3 goto g(allocate); Continuation based C (CbC), which a slight modified C language. 4 } 5 Code segments are units of calculation and Data segments are 6 // data segment definition sets of typed data. We use these segments as units of computation 7 // (generated automatically) 8 union Data { and meta computation. In this paper we show the implementation 9 struct Allocate { of CbC on LLVM and Clang 3.7. 10 long size; 11 } allocate; 12 }; I. A PRACTICAL CONTINUATION BASED LANGUAGE TABLE I The proposed units of programming are named code seg- CBCEXAMPLE ments and data segments. Code segments are units of calcu- lation which have no state. Data segments are sets of typed data. Code segments are connected to data segments by a meta data segment called a context. After the execution of a code have input data segments and output data segments. Data segment and its context, the next code segment (continuation) segments have two kind of dependency with code segments. is executed. First, Code segments access the contents of data segments Continuation based C (CbC) [1], hereafter referred to as using field names. So data segments should have the named CbC, is a slight modified C which supports code segments. -
Majnemer-Fuzzingclang.Pdf
Fuzzing Clang to find ABI Bugs David Majnemer What’s in an ABI? • The size, alignment, etc. of types • Layout of records, RTTI, virtual tables, etc. • The decoration of types, functions, etc. • To generalize: anything that you need N > 1 compilers to agree upon C++: A complicated language union U { int a; int b; }; ! int U::*x = &U::a; int U::*y = &U::b; ! Does ‘x’ equal ‘y’ ? We’ve got a standard How hard could it be? “[T]wo pointers to members compare equal if they would refer to the same member of the same most derived object or the same subobject if indirection with a hypothetical object of the associated class type were performed, otherwise they compare unequal.” No ABI correctly implements this. Why does any of this matter? • Data passed across ABI boundaries may be interpreted by another compiler • Unpredictable things may happen if two compilers disagree about how to interpret this data • Subtle bugs can be some of the worst bugs Finding bugs isn’t easy • ABI implementation techniques may collide with each other in unpredictable ways • One compiler permutes field order in structs if the alignment is 16 AND it has an empty virtual base AND it has at least one bitfield member AND … • Some ABIs are not documented • Even if they are, you can’t always trust the documentation What happens if we aren’t proactive • Let users find our bugs for us • This can be demoralizing for users, eroding their trust • Altruistic; we must hope that the user will file the bug • At best, the user’s time has been spent on something they probably didn’t want to do Let computers find the bugs 1. -
ILE C/C++ Language Reference, SC09-7852
IBM IBM i Websphere Development Studio ILE C/C++ Language Reference 7.1 SC09-7852-02 IBM IBM i Websphere Development Studio ILE C/C++ Language Reference 7.1 SC09-7852-02 Note! Before using this information and the product it supports, be sure to read the general information under “Notices” on page 355. This edition applies to IBM i 7.1, (program 5770-WDS), ILE C/C++ compilers, and to all subsequent releases and modifications until otherwise indicated in new editions. This version does not run on all reduced instruction set computer (RISC) models nor does it run on CISC models. © Copyright IBM Corporation 1998, 2010. US Government Users Restricted Rights – Use, duplication or disclosure restricted by GSA ADP Schedule Contract with IBM Corp. Contents About ILE C/C++ Language Reference Digraph characters ........... 27 (SC09-7852-01) ........... ix Trigraph sequences ........... 28 Who should read this book ......... ix Comments............... 28 Highlighting Conventions .......... x How to Read the Syntax Diagrams ....... x Chapter 3. Data objects and Prerequisite and related information ...... xii declarations ............ 31 How to send your comments ........ xii Overview of data objects and declarations .... 31 Overview of data objects ......... 31 What's new for IBM i 7.1 ....... xv Incomplete types .......... 32 Compatible and composite types ..... 32 Chapter 1. Scope and linkage ..... 1 Overview of data declarations and definitions .. 33 Tentative definitions ......... 34 Scope ................. 1 Storage class specifiers........... 35 Block/local scope ............ 2 The auto storage class specifier ....... 35 Function scope ............ 2 Storage duration of automatic variables ... 35 Function prototype scope ......... 3 Linkage of automatic variables ...... 36 File/global scope ........... -
Code Transformation and Analysis Using Clang and LLVM Static and Dynamic Analysis
Code transformation and analysis using Clang and LLVM Static and Dynamic Analysis Hal Finkel1 and G´abor Horv´ath2 Computer Science Summer School 2017 1 Argonne National Laboratory 2 Ericsson and E¨otv¨osLor´adUniversity Table of contents 1. Introduction 2. Static Analysis with Clang 3. Instrumentation and More 1 Introduction Space of Techniques During this set of lectures we'll cover a space of techniques for the analysis and transformation of code using LLVM. Each of these techniques have overlapping areas of applicability: Static Analysis LLVM Instrumentation Source Transformation 2 Space of Techniques When to use source-to-source transformation: • When you need to use the instrumented code with multiple compilers. • When you intend for the instrumentation to become a permanent part of the code base. You'll end up being concerned with the textual formatting of the instrumentation if humans also need to maintain or enhance this same code. 3 Space of Techniques When to use Clang's static analysis: • When the analysis can be performed on an AST representation. • When you'd like to maintain a strong connection to the original source code. • When false negatives are acceptable (i.e. it is okay if you miss problems). https://clang-analyzer.llvm.org/ 4 Space of Techniques When to use IR instrumentation: • When the necessary conditions can be (or can only be) detected at runtime (often in conjunction with a specialized runtime library). • When you require stronger coverage guarantees than static analysis. • When you'd like to reduce the cost of the instrumentation by running optimizations before the instrumentation is inserted, after the instrumentation is inserted, or both. -
Application Binary Interface for the ARM Architecture
ABI for the ARM Architecture (Base Standard) Application Binary Interface for the ARM® Architecture The Base Standard Document number: ARM IHI 0036B, current through ABI release 2.10 Date of Issue: 10th October 2008, reissued 24th November 2015 Abstract This document describes the structure of the Application Binary Interface (ABI) for the ARM architecture, and links to the documents that define the base standard for the ABI for the ARM Architecture. The base standard governs inter-operation between independently generated binary files and sets standards common to ARM- based execution environments. Keywords ABI for the ARM architecture, ABI base standard, embedded ABI How to find the latest release of this specification or report a defect in it Please check the ARM Information Center (http://infocenter.arm.com/) for a later release if your copy is more than one year old (navigate to the ARM Software development tools section, ABI for the ARM Architecture subsection). Please report defects in this specification to arm dot eabi at arm dot com. Licence THE TERMS OF YOUR ROYALTY FREE LIMITED LICENCE TO USE THIS ABI SPECIFICATION ARE GIVEN IN SECTION 1.4, Your licence to use this specification (ARM contract reference LEC-ELA-00081 V2.0). PLEASE READ THEM CAREFULLY. BY DOWNLOADING OR OTHERWISE USING THIS SPECIFICATION, YOU AGREE TO BE BOUND BY ALL OF ITS TERMS. IF YOU DO NOT AGREE TO THIS, DO NOT DOWNLOAD OR USE THIS SPECIFICATION. THIS ABI SPECIFICATION IS PROVIDED “AS IS” WITH NO WARRANTIES (SEE SECTION 1.4 FOR DETAILS). Proprietary notice ARM, Thumb, RealView, ARM7TDMI and ARM9TDMI are registered trademarks of ARM Limited. -
Application Binary Interface Compatability Through A
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by The University of Utah: J. Willard Marriott Digital Library APPLICATION BINARY INTERFACE COMPATIBILITY THROUGH A CUSTOMIZABLE LANGUAGE by Kevin Jay Atkinson A dissertation submitted to the faculty of The University of Utah in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Computer Science School of Computing The University of Utah December 2011 Copyright c Kevin Jay Atkinson 2011 All Rights Reserved The University of Utah Graduate School STATEMENT OF DISSERTATION APPROVAL The dissertation of Kevin Jay Atkinson has been approved by the following supervisory committee members: Matthew Flatt , Chair 11/3/2011 Date Approved Gary Lindstrom , Member 11/17/2011 Date Approved Eric Eide , Member 11/3/2011 Date Approved Robert Kessler , Member 11/3/2011 Date Approved Olin Shivers , Member 11/29/2011 Date Approved and by Al Davis , Chair of the Department of School of Computing and by Charles A. Wight, Dean of The Graduate School. ABSTRACT ZL is a C++-compatible language in which high-level constructs, such as classes, are defined using macros over a C-like core language. This approach is similar in spirit to Scheme and makes many parts of the language easily customizable. For example, since the class construct can be defined using macros, a programmer can have complete control over the memory layout of objects. Using this capability, a programmer can mitigate certain problems in software evolution such as fragile ABIs (Application Binary Interfaces) due to software changes and incompatible ABIs due to compiler changes. -
Sham: a DSL for Fast Dsls
Sham: A DSL for Fast DSLs Rajan Waliaa, Chung-chieh Shana, and Sam Tobin-Hochstadta a Indiana University, Bloomington, United States Abstract Domain-specific languages (DSLs) are touted as both easy to embed in programs and easy to optimize. Yet these goals are often in tension. Embedded or internal DSLs fit naturally with a host language, while inheriting the host’s performance characteristics. External DSLs can use external optimizers and languages but sit apart from the host. We present Sham, a toolkit designed to enable internal DSLs with high performance. Sham provides a domain-specific language (embedded in Racket) for implementing other high-performance DSLs, with transparent compilation to assembly code at runtime. Sham is well suited as both a compilation target for other embedded DSLs and for transparently replacing DSL support code with faster versions. Sham provides seamless inter-operation with its host language without requiring any additional effort from its users. Sham also provides a framework for defining language syntax which implements Sham’s own language interface as well. We validate Sham’s design on a series of case studies, ranging from Krishnamurthi’s classic automata DSL to a sound synthesis DSL and a probabilistic programming language. All of these are existing DSLs where we replaced the backend using Sham, resulting in major performance gains. We present an example-driven description of how Sham can smoothly enhance an existing DSL into a high-performance one. When compared to existing approaches for implementing high-performance DSLs, Sham’s design aims for both simplicity and programmer control. This makes it easier to port our techniques to other languages and frameworks, or borrow Sham’s innovations “à la carte” without adopting the whole approach. -
Introduction to LLVM (Low Level Virtual Machine)
Introduction to LLVM (Low Level Virtual Machine) Fons Rademakers CERN What is the LLVM Project? • Collection of compiler technology components ■ Not a traditional “Virtual Machine” ■ Language independent optimizer and code generator ■ LLVM-GCC front-end ■ Clang front-end ■ Just-In-Time compiler • Open source project with many contributors ■ Industry, research groups, individuals ■ See http://llvm.org/Users.html • Everything is Open Source, and BSD Licensed! (except GCC) • For more see: http://llvm.org/ 2 LLVM as an Open-Source Project • Abridged project history ■ Dec. 2000: Started as a research project at University of Illinois ■ Oct. 2003: Open Source LLVM 1.0 release ■ June 2005: Apple hires project lead Chris Lattner ■ June 2008: LLVM GCC 4.2 ships in Apple Xcode 3.1 ■ Feb. 2009: LLVM 2.5 3 Why New Compilers? • Existing Open Source C Compilers have Stagnated! • How? ■ Based on decades old code generation technology ■ No modern techniques like cross-file optimization and JIT codegen ■ Aging code bases: difficult to learn, hard to change substantially ■ Can’t be reused in other applications ■ Keep getting slower with every release 4 LLVM Vision and Approach • Build a set of modular compiler components: ■ Reduces the time & cost to construct a particular compiler ■ Components are shared across different compilers ■ Allows choice of the right component for the job ■ Focus on compile and execution times ■ All components written in C++, ported to many platforms 5 First Product - LLVM-GCC 4.2 • C, C++, Objective C, Objective C++, Ada and Fortran • Same GCC command line options • Supports almost all GCC language features and extensions • Supports many targets, including X86, X86-64, PowerPC, etc. -
Polymorphisation: Improving Rust Compilation Times Through
Polymorphisation: Improving Rust compilation times through intelligent monomorphisation David Wood (2198230W) April 15, 2020 MSci Software Engineering with Work Placement (40 Credits) ABSTRACT In addition, Rust's compilation model is different from Rust is a new systems programming language, designed to other programming languages. In C++, the compilation unit is a single file, whereas Rust's compilation unit is a provide memory safety while maintaining high performance. 1 One of the major priorities for the Rust compiler team is crate . While compilation times of entire C++ and entire to improve compilation times, which is regularly requested Rust projects are generally comparable, modification of a by users of the language. Rust's high compilation times are single C++ file requires far less recompilation than modifi- a result of many expensive compile-time analyses, a com- cation of a single Rust file. In recent years, implementation pilation model with large compilation units (thus requiring of incremental compilation into rustc has improved recom- incremental compilation techniques), use of LLVM to gen- pilation times after small modifications to code. erate machine code, and the language's monomorphisation Rust generates machine code using LLVM, a collection of strategy. This paper presents a code size optimisation, im- modular and reusable compiler and toolchain technologies. plemented in rustc, to reduce compilation times by intelli- At LLVM's core is a language-independent optimiser, and gently reducing monomorphisation through \polymorphisa- code-generation support for multiple processors. Languages tion" - identifying where functions could remain polymor- including Rust, Swift, Julia and C/C++ have compilers us- phic and producing fewer monomorphisations.