How to Cross Compile with LLVM Based Tools Peter Smith, Linaro Introduction and Assumptions
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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. -
Clangjit: Enhancing C++ with Just-In-Time Compilation
ClangJIT: Enhancing C++ with Just-in-Time Compilation Hal Finkel David Poliakoff David F. Richards Lead, Compiler Technology and Lawrence Livermore National Lawrence Livermore National Programming Languages Laboratory Laboratory Leadership Computing Facility Livermore, CA, USA Livermore, CA, USA Argonne National Laboratory [email protected] [email protected] Lemont, IL, USA [email protected] ABSTRACT body of C++ code, but critically, defer the generation and optimiza- The C++ programming language is not only a keystone of the tion of template specializations until runtime using a relatively- high-performance-computing ecosystem but has proven to be a natural extension to the core C++ programming language. successful base for portable parallel-programming frameworks. As A significant design requirement for ClangJIT is that the runtime- is well known, C++ programmers use templates to specialize al- compilation process not explicitly access the file system - only gorithms, thus allowing the compiler to generate highly-efficient loading data from the running binary is permitted - which allows code for specific parameters, data structures, and so on. This capa- for deployment within environments where file-system access is bility has been limited to those specializations that can be identi- either unavailable or prohibitively expensive. In addition, this re- fied when the application is compiled, and in many critical cases, quirement maintains the redistributibility of the binaries using the compiling all potentially-relevant specializations is not practical. JIT-compilation features (i.e., they can run on systems where the ClangJIT provides a well-integrated C++ language extension allow- source code is unavailable). For example, on large HPC deploy- ing template-based specialization to occur during program execu- ments, especially on supercomputers with distributed file systems, tion. -
Riscv-Software-Stack-Tutorial-Hpca2015
Software Tools Bootcamp RISC-V ISA Tutorial — HPCA-21 08 February 2015 Albert Ou UC Berkeley [email protected] Preliminaries To follow along, download these slides at http://riscv.org/tutorial-hpca2015.html 2 Preliminaries . Shell commands are prefixed by a “$” prompt. Due to time constraints, we will not be building everything from source in real-time. - Binaries have been prepared for you in the VM image. - Detailed build steps are documented here for completeness but are not necessary if using the VM. Interactive portions of this tutorial are denoted with: $ echo 'Hello world' . Also as a reminder, these slides are marked with an icon in the upper-right corner: 3 Software Stack . Many possible combinations (and growing) . But here we will focus on the most common workflows for RISC-V software development 4 Agenda 1. riscv-tools infrastructure 2. First Steps 3. Spike + Proxy Kernel 4. QEMU + Linux 5. Advanced Cross-Compiling 6. Yocto/OpenEmbedded 5 riscv-tools — Overview “Meta-repository” with Git submodules for every stable component of the RISC-V software toolchain Submodule Contents riscv-fesvr RISC-V Frontend Server riscv-isa-sim Functional ISA simulator (“Spike”) riscv-qemu Higher-performance ISA simulator riscv-gnu-toolchain binutils, gcc, newlib, glibc, Linux UAPI headers riscv-llvm LLVM, riscv-clang submodule riscv-pk RISC-V Proxy Kernel (riscv-linux) Linux/RISC-V kernel port riscv-tests ISA assembly tests, benchmark suite All listed submodules are hosted under the riscv GitHub organization: https://github.com/riscv 6 riscv-tools — Installation . Build riscv-gnu-toolchain (riscv*-*-elf / newlib target), riscv-fesvr, riscv-isa-sim, and riscv-pk: (pre-installed in VM) $ git clone https://github.com/riscv/riscv-tools $ cd riscv-tools $ git submodule update --init --recursive $ export RISCV=<installation path> $ export PATH=${PATH}:${RISCV}/bin $ ./build.sh . -
Operating Systems and Applications for Embedded Systems >>> Toolchains
>>> Operating Systems And Applications For Embedded Systems >>> Toolchains Name: Mariusz Naumowicz Date: 31 sierpnia 2018 [~]$ _ [1/19] >>> Plan 1. Toolchain Toolchain Main component of GNU toolchain C library Finding a toolchain 2. crosstool-NG crosstool-NG Installing Anatomy of a toolchain Information about cross-compiler Configruation Most interesting features Sysroot Other tools POSIX functions AP [~]$ _ [2/19] >>> Toolchain A toolchain is the set of tools that compiles source code into executables that can run on your target device, and includes a compiler, a linker, and run-time libraries. [1. Toolchain]$ _ [3/19] >>> Main component of GNU toolchain * Binutils: A set of binary utilities including the assembler, and the linker, ld. It is available at http://www.gnu.org/software/binutils/. * GNU Compiler Collection (GCC): These are the compilers for C and other languages which, depending on the version of GCC, include C++, Objective-C, Objective-C++, Java, Fortran, Ada, and Go. They all use a common back-end which produces assembler code which is fed to the GNU assembler. It is available at http://gcc.gnu.org/. * C library: A standardized API based on the POSIX specification which is the principle interface to the operating system kernel from applications. There are several C libraries to consider, see the following section. [1. Toolchain]$ _ [4/19] >>> C library * glibc: Available at http://www.gnu.org/software/libc. It is the standard GNU C library. It is big and, until recently, not very configurable, but it is the most complete implementation of the POSIX API. * eglibc: Available at http://www.eglibc.org/home. -
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. -
A DSL for Resource Checking Using Finite State Automaton-Driven Symbolic Execution Code
Open Comput. Sci. 2021; 11:107–115 Research Article Endre Fülöp and Norbert Pataki* A DSL for Resource Checking Using Finite State Automaton-Driven Symbolic Execution https://doi.org/10.1515/comp-2020-0120 code. Compilers validate the syntactic elements, referred Received Mar 31, 2020; accepted May 28, 2020 variables, called functions to name a few. However, many problems may remain undiscovered. Abstract: Static analysis is an essential way to find code Static analysis is a widely-used method which is by smells and bugs. It checks the source code without exe- definition the act of uncovering properties and reasoning cution and no test cases are required, therefore its cost is about software without observing its runtime behaviour, lower than testing. Moreover, static analysis can help in restricting the scope of tools to those which operate on the software engineering comprehensively, since static anal- source representation, the code written in a single or mul- ysis can be used for the validation of code conventions, tiple programming languages. While most static analysis for measuring software complexity and for executing code methods are designed to detect anomalies (called bugs) in refactorings as well. Symbolic execution is a static analy- software code, the methods they employ are varied [1]. One sis method where the variables (e.g. input data) are inter- major difference is the level of abstraction at which the preted with symbolic values. code is represented [2]. Because static analysis is closely Clang Static Analyzer is a powerful symbolic execution related to the compilation of the code, the formats used engine based on the Clang compiler infrastructure that to represent the different abstractions are not unique to can be used with C, C++ and Objective-C. -
SMT-Based Refutation of Spurious Bug Reports in the Clang Static Analyzer
SMT-Based Refutation of Spurious Bug Reports in the Clang Static Analyzer Mikhail R. Gadelha∗, Enrico Steffinlongo∗, Lucas C. Cordeiroy, Bernd Fischerz, and Denis A. Nicole∗ ∗University of Southampton, UK. yUniversity of Manchester, UK. zStellenbosch University, South Africa. Abstract—We describe and evaluate a bug refutation extension bit in a is one, and (a & 1) ˆ 1 inverts the last bit in a. for the Clang Static Analyzer (CSA) that addresses the limi- The analyzer, however, produces the following (spurious) bug tations of the existing built-in constraint solver. In particular, report when analyzing the program: we complement CSA’s existing heuristics that remove spurious bug reports. We encode the path constraints produced by CSA as Satisfiability Modulo Theories (SMT) problems, use SMT main.c:4:12: warning: Dereference of null solvers to precisely check them for satisfiability, and remove pointer (loaded from variable ’z’) bug reports whose associated path constraints are unsatisfi- return *z; able. Our refutation extension refutes spurious bug reports in ˆ˜ 8 out of 12 widely used open-source applications; on aver- age, it refutes ca. 7% of all bug reports, and never refutes 1 warning generated. any true bug report. It incurs only negligible performance overheads, and on average adds 1.2% to the runtime of the The null pointer dereference reported here means that CSA full Clang/LLVM toolchain. A demonstration is available at claims to nevertheless have found a path where the dereference https://www.youtube.com/watch?v=ylW5iRYNsGA. of z is reachable. Such spurious bug reports are in practice common; in our I. -
Linux Journal | February 2016 | Issue
™ A LOOK AT KDE’s KStars Astronomy Program Since 1994: The Original Magazine of the Linux Community FEBRUARY 2016 | ISSUE 262 | www.linuxjournal.com + Programming Working with Command How-Tos Arguments in Your Program a Shell Scripts BeagleBone Interview: Katerina Black Barone-Adesi on to Help Brew Beer Developing the Snabb Switch Network Write a Toolkit Short Script to Solve a WATCH: ISSUE Math Puzzle OVERVIEW V LJ262-February2016.indd 1 1/21/16 5:26 PM NEW! Agile Improve Product Business Development Processes with an Enterprise Practical books Author: Ted Schmidt Job Scheduler for the most technical Sponsor: IBM Author: Mike Diehl Sponsor: people on the planet. Skybot Finding Your DIY Way: Mapping Commerce Site Your Network Author: to Improve Reuven M. Lerner Manageability GEEK GUIDES Sponsor: GeoTrust Author: Bill Childers Sponsor: InterMapper Combating Get in the Infrastructure Fast Lane Sprawl with NVMe Author: Author: Bill Childers Mike Diehl Sponsor: Sponsor: Puppet Labs Silicon Mechanics & Intel Download books for free with a Take Control Linux in simple one-time registration. of Growing the Time Redis NoSQL of Malware http://geekguide.linuxjournal.com Server Clusters Author: Author: Federico Kereki Reuven M. Lerner Sponsor: Sponsor: IBM Bit9 + Carbon Black LJ262-February2016.indd 2 1/21/16 5:26 PM NEW! Agile Improve Product Business Development Processes with an Enterprise Practical books Author: Ted Schmidt Job Scheduler for the most technical Sponsor: IBM Author: Mike Diehl Sponsor: people on the planet. Skybot Finding Your DIY Way: Mapping Commerce Site Your Network Author: to Improve Reuven M. Lerner Manageability GEEK GUIDES Sponsor: GeoTrust Author: Bill Childers Sponsor: InterMapper Combating Get in the Infrastructure Fast Lane Sprawl with NVMe Author: Author: Bill Childers Mike Diehl Sponsor: Sponsor: Puppet Labs Silicon Mechanics & Intel Download books for free with a Take Control Linux in simple one-time registration. -
Pwny Documentation Release 0.9.0
pwny Documentation Release 0.9.0 Author Nov 19, 2017 Contents 1 pwny package 3 2 pwnypack package 5 2.1 asm – (Dis)assembler..........................................5 2.2 bytecode – Python bytecode manipulation..............................7 2.3 codec – Data transformation...................................... 11 2.4 elf – ELF file parsing.......................................... 16 2.5 flow – Communication......................................... 36 2.6 fmtstring – Format strings...................................... 41 2.7 marshal – Python marshal loader................................... 42 2.8 oracle – Padding oracle attacks.................................... 43 2.9 packing – Data (un)packing...................................... 44 2.10 php – PHP related functions....................................... 46 2.11 pickle – Pickle tools.......................................... 47 2.12 py_internals – Python internals.................................. 49 2.13 rop – ROP gadgets........................................... 50 2.14 shellcode – Shellcode generator................................... 50 2.15 target – Target definition....................................... 79 2.16 util – Utility functions......................................... 80 3 Indices and tables 83 Python Module Index 85 i ii pwny Documentation, Release 0.9.0 pwnypack is the official CTF toolkit of Certified Edible Dinosaurs. It aims to provide a set of command line utilities and a python library that are useful when playing hacking CTFs. The core functionality of pwnypack -
Protecting Million-User Ios Apps with Obfuscation: Motivations, Pitfalls, and Experience
Protecting Million-User iOS Apps with Obfuscation: Motivations, Pitfalls, and Experience Pei Wang∗ Dinghao Wu Zhaofeng Chen Tao Wei [email protected] [email protected] [email protected] [email protected] The Pennsylvania State The Pennsylvania State Baidu X-Lab Baidu X-Lab University University ABSTRACT ACM Reference Format: In recent years, mobile apps have become the infrastructure of many Pei Wang, Dinghao Wu, Zhaofeng Chen, and Tao Wei. 2018. Protecting popular Internet services. It is now fairly common that a mobile app Million-User iOS Apps with Obfuscation: Motivations, Pitfalls, and Experi- ence. In ICSE-SEIP ’18: 40th International Conference on Software Engineering: serves a large number of users across the globe. Different from web- Software Engineering in Practice Track, May 27–June 3, 2018, Gothenburg, based services whose important program logic is mostly placed on Sweden. ACM, New York, NY, USA, 10 pages. https://doi.org/10.1145/3183519. remote servers, many mobile apps require complicated client-side 3183524 code to perform tasks that are critical to the businesses. The code of mobile apps can be easily accessed by any party after the software is installed on a rooted or jailbroken device. By examining the code, skilled reverse engineers can learn various knowledge about the 1 INTRODUCTION design and implementation of an app. Real-world cases have shown During the last decade, mobile devices and apps have become the that the disclosed critical information allows malicious parties to foundations of many million-dollar businesses operated globally. abuse or exploit the app-provided services for unrightful profits, However, the prosperity has drawn many malevolent attempts to leading to significant financial losses for app vendors. -
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. -
Overview of LLVM Architecture of LLVM
Overview of LLVM Architecture of LLVM Front-end: high-level programming language => LLVM IR Optimizer: optimize/analyze/secure the program in the IR form Back-end: LLVM IR => machine code Optimizer The optimizer’s job: analyze/optimize/secure programs. Optimizations are implemented as passes that traverse some portion of a program to either collect information or transform the program. A pass is an operation on a unit of IR code. Pass is an important concept in LLVM. LLVM IR - A low-level strongly-typed language-independent, SSA-based representation. - Tailored for static analyses and optimization purposes. Part 1 Part 1 has two kinds of passes: - Analysis pass (section 1): only analyze code statically - Transformation pass (section 2 & 3): insert code into the program Analysis pass (Section 1) Void foo (uint32_t int, uint32_t * p) { LLVM IR ... Clang opt } test.c test.bc stderr mypass.so Transformation pass (Section 2 & 3) mypass.so Void foo (uint32_t int, uint32_t * p) { ... LLVM IR opt LLVM IR } test.cpp Int main () { test.bc test-ins.bc ... Clang++ foo () ... LLVM IR } Clang++ main.cpp main.bc LLVM IR lib.cpp Executable lib.bc Section 1 Challenges: - How to traverse instructions in a function http://releases.llvm.org/3.9.1/docs/ProgrammersManual.html#iterating-over-the-instruction-in-a-function - How to print to stderr Section 2 & 3 Challenges: 1. How to traverse basic blocks in a function and instructions in a basic block 2. How to insert function calls to the runtime library a. Add the function signature to the symbol table of the module Section 2 & 3 Challenges: 1.