Design and Implementation of a Tricore Backend for the LLVM Compiler Framework
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Bit Shifts Bit Operations, Logical Shifts, Arithmetic Shifts, Rotate Shifts
Why bit operations Assembly languages all provide ways to manipulate individual bits in multi-byte values Some of the coolest “tricks” in assembly rely on Bit Shifts bit operations With only a few instructions one can do a lot very quickly using judicious bit operations And you can do them in almost all high-level ICS312 programming languages! Let’s look at some of the common operations, Machine-Level and starting with shifts Systems Programming logical shifts arithmetic shifts Henri Casanova ([email protected]) rotate shifts Shift Operations Logical Shifts The simplest shifts: bits disappear at one end A shift moves the bits around in some data and zeros appear at the other A shift can be toward the left (i.e., toward the most significant bits), or toward the right (i.e., original byte 1 0 1 1 0 1 0 1 toward the least significant bits) left log. shift 0 1 1 0 1 0 1 0 left log. shift 1 1 0 1 0 1 0 0 left log. shift 1 0 1 0 1 0 0 0 There are two kinds of shifts: right log. shift 0 1 0 1 0 1 0 0 Logical Shifts right log. shift 0 0 1 0 1 0 1 0 Arithmetic Shifts right log. shift 0 0 0 1 0 1 0 1 Logical Shift Instructions Shifts and Numbers Two instructions: shl and shr The common use for shifts: quickly multiply and divide by powers of 2 One specifies by how many bits the data is shifted In decimal, for instance: multiplying 0013 by 10 amounts to doing one left shift to obtain 0130 Either by just passing a constant to the instruction multiplying by 100=102 amounts to doing two left shifts to obtain 1300 Or by using whatever -
Resourceable, Retargetable, Modular Instruction Selection Using a Machine-Independent, Type-Based Tiling of Low-Level Intermediate Code
Reprinted from Proceedings of the 2011 ACM Symposium on Principles of Programming Languages (POPL’11) Resourceable, Retargetable, Modular Instruction Selection Using a Machine-Independent, Type-Based Tiling of Low-Level Intermediate Code Norman Ramsey Joao˜ Dias Department of Computer Science, Tufts University Department of Computer Science, Tufts University [email protected] [email protected] Abstract Our compiler infrastructure is built on C--, an abstraction that encapsulates an optimizing code generator so it can be reused We present a novel variation on the standard technique of selecting with multiple source languages and multiple target machines (Pey- instructions by tiling an intermediate-code tree. Typical compilers ton Jones, Ramsey, and Reig 1999; Ramsey and Peyton Jones use a different set of tiles for every target machine. By analyzing a 2000). C-- accommodates multiple source languages by providing formal model of machine-level computation, we have developed a two main interfaces: the C-- language is a machine-independent, single set of tiles that is machine-independent while retaining the language-independent target language for front ends; the C-- run- expressive power of machine code. Using this tileset, we reduce the time interface is an API which gives the run-time system access to number of tilers required from one per machine to one per archi- the states of suspended computations. tectural family (e.g., register architecture or stack architecture). Be- cause the tiler is the part of the instruction selector that is most dif- C-- is not a universal intermediate language (Conway 1958) or ficult to reason about, our technique makes it possible to retarget an a “write-once, run-anywhere” intermediate language encapsulating instruction selector with significantly less effort than standard tech- a rigidly defined compiler and run-time system (Lindholm and niques. -
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. -
Automatic Isolation of Compiler Errors
Automatic Isolation of Compiler Errors DAVID B.WHALLEY Flor ida State University This paper describes a tool called vpoiso that was developed to automatically isolate errors in the vpo com- piler system. The twogeneral types of compiler errors isolated by this tool are optimization and nonopti- mization errors. When isolating optimization errors, vpoiso relies on the vpo optimizer to identify sequences of changes, referred to as transformations, that result in semantically equivalent code and to pro- vide the ability to stop performing improving (or unnecessary) transformations after a specified number have been performed. Acompilation of a typical program by vpo often results in thousands of improving transformations being performed. The vpoiso tool can automatically isolate the first improving transforma- tion that causes incorrect output of the execution of the compiled program by using a binary search that varies the number of improving transformations performed. Not only is the illegaltransformation automati- cally isolated, but vpoiso also identifies the location and instant the transformation is performed in vpo. Nonoptimization errors occur from problems in the front end, code generator,and necessary transforma- tions in the optimizer.Ifanother compiler is available that can produce correct (but perhaps more ineffi- cient) code, then vpoiso can isolate nonoptimization errors to a single function. Automatic isolation of compiler errors facilitates retargeting a compiler to a newmachine, maintenance of the compiler,and sup- porting experimentation with newoptimizations. General Terms: Compilers, Testing Additional Key Words and Phrases: Diagnosis procedures, nonoptimization errors, optimization errors 1. INTRODUCTION To increase portability compilers are often split into twoparts, a front end and a back end. -
Using LLVM for Optimized Lightweight Binary Re-Writing at Runtime
Using LLVM for Optimized Lightweight Binary Re-Writing at Runtime Alexis Engelke, Josef Weidendorfer Department of Informatics Technical University of Munich Munich, Germany EMail: [email protected], [email protected] Abstract—Providing new parallel programming models/ab- helpful in reducing any overhead of provided abstractions. stractions as a set of library functions has the huge advantage But with new languages, porting of existing application that it allows for an relatively easy incremental porting path for code is required, being a high burden for adoption with legacy HPC applications, in contrast to the huge effort needed when novel concepts are only provided in new programming old code bases. Therefore, to provide abstractions such as languages or language extensions. However, performance issues PGAS for legacy codes, APIs implemented as libraries are are to be expected with fine granular usage of library functions. proposed [5], [6]. Libraries have the benefit that they easily In previous work, we argued that binary rewriting can bridge can be composed and can stay small and focused. However, the gap by tightly coupling application and library functions at libraries come with the caveat that fine granular usage of runtime. We showed that runtime specialization at the binary level, starting from a compiled, generic stencil code can help library functions in inner kernels will severely limit compiler in approaching performance of manually written, statically optimizations such as vectorization and thus, may heavily compiled version. reduce performance. In this paper, we analyze the benefits of post-processing the To this end, in previous work [7], we proposed a technique re-written binary code using standard compiler optimizations for lightweight code generation by re-combining existing as provided by LLVM. -
Relational Representation of the LLVM Intermediate Language
NATIONAL AND KAPODISTRIAN UNIVERSITY OF ATHENS SCHOOL OF SCIENCE DEPARTMENT OF INFORMATICS AND TELECOMMUNICATIONS UNDERGRADUATE STUDIES UNDERGRADUATE THESIS Relational Representation of the LLVM Intermediate Language Eirini I. Psallida Supervisors: Yannis Smaragdakis, Associate Professor NKUA Georgios Balatsouras, PhD Student NKUA ATHENS JANUARY 2014 ΕΘΝΙΚΟ ΚΑΙ ΚΑΠΟΔΙΣΤΡΙΑΚΟ ΠΑΝΕΠΙΣΤΗΜΙΟ ΑΘΗΝΩΝ ΣΧΟΛΗ ΘΕΤΙΚΩΝ ΕΠΙΣΤΗΜΩΝ ΤΜΗΜΑ ΠΛΗΡΟΦΟΡΙΚΗΣ ΚΑΙ ΤΗΛΕΠΙΚΟΙΝΩΝΙΩΝ ΠΡΟΠΤΥΧΙΑΚΕΣ ΣΠΟΥΔΕΣ ΠΤΥΧΙΑΚΗ ΕΡΓΑΣΙΑ Σχεσιακή Αναπαράσταση της Ενδιάμεσης Γλώσσας του LLVM Ειρήνη Ι. Ψαλλίδα Επιβλέποντες: Γιάννης Σμαραγδάκης, Αναπληρωτής Καθηγητής ΕΚΠΑ Γεώργιος Μπαλατσούρας, Διδακτορικός φοιτητής ΕΚΠΑ ΑΘΗΝΑ ΙΑΝΟΥΑΡΙΟΣ 2014 UNDERGRADUATE THESIS Relational Representation of the LLVM Intermediate Language Eirini I. Psallida R.N.: 1115200700272 Supervisor: Yannis Smaragdakis, Associate Professor NKUA Georgios Balatsouras, PhD Student NKUA ΠΤΥΧΙΑΚΗ ΕΡΓΑΣΙΑ Σχεσιακή Αναπαράσταση της ενδιάμεσης γλώσσας του LLVM Ειρήνη Ι. Ψαλλίδα Α.Μ.: 1115200700272 Επιβλέπων: Γιάννης Σμαραγδάκης, Αναπληρωτής Καθηγητής ΕΚΠΑ Γεώργιος Μπαλατσούρας, Διδακτορικός φοιτητής ΕΚΠΑ ΠΕΡΙΛΗΨΗ Περιγράφουμε τη σχεσιακή αναπαράσταση της ενδιάμεσης γλώσσας του LLVM, γνωστή ως LLVM IR. Η υλοποίηση μας παράγει σχέσεις από ένα πρόγραμμα εισόδου σε ενδιάμεση μορφή LLVM. Κάθε σχέση αποθηκεύεται σαν πίνακας βάσης δεδομένων σε ένα περιβάλλον εργασίας Datalog. Αναπαριστούμε το σύστημα τύπων καθώς και το σύνολο εντολών της γλώσσας του LLVM. Υποστηρίζουμε επίσης τους περιορισμούς της γλώσσας προσδιορίζοντάς τους με χρήση της προγραμματιστικής γλώσσας Datalog. ΘΕΜΑΤΙΚΗ ΠΕΡΙΟΧΗ: Μεταγλωτιστές, Γλώσσες Προγραμματισμού ΛΕΞΕΙΣ ΚΛΕΙΔΙΑ: σχεσιακή αναπαράσταση, ενδιάμεση αναπαράσταση, σύστημα τύπων, σύνολο εντολών, LLVM, Datalog ABSTRACT We describe the relational representation of the LLVM intermediate language, known as the LLVM IR. Our implementation produces the relation contents of an input program in the LLVM intermediate form. Each relation is stored as a database table into a Datalog workspace. -
Automatic Derivation of Compiler Machine Descriptions
Automatic Derivation of Compiler Machine Descriptions CHRISTIAN S. COLLBERG University of Arizona We describe a method designed to significantly reduce the effort required to retarget a compiler to a new architecture, while at the same time producing fast and effective compilers. The basic idea is to use the native C compiler at compiler construction time to discover architectural features of the new architecture. From this information a formal machine description is produced. Given this machine description, a native code-generator can be generated by a back-end generator such as BEG or burg. A prototype automatic Architecture Discovery Tool (called ADT) has been implemented. This tool is completely automatic and requires minimal input from the user. Given the Internet address of the target machine and the command-lines by which the native C compiler, assembler, and linker are invoked, ADT will generate a BEG machine specification containing the register set, addressing modes, instruction set, and instruction timings for the architecture. The current version of ADT is general enough to produce machine descriptions for the integer instruction sets of common RISC and CISC architectures such as the Sun SPARC, Digital Alpha, MIPS, DEC VAX, and Intel x86. Categories and Subject Descriptors: D.2.7 [Software Engineering]: Distribution, Maintenance, and Enhancement—Portability; D.3.2 [Programming Languages]: Language Classifications— Macro and assembly languages; D.3.4 [Programming Languages]: Processors—Translator writ- ing systems and compiler generators General Terms: Languages Additional Key Words and Phrases: Back-end generators, compiler configuration scripts, retargeting 1. INTRODUCTION An important aspect of a compiler implementation is its retargetability.For example, a new programming language whose compiler can be quickly retar- geted to a new hardware platform or a new operating system is more likely to gain widespread acceptance than a language whose compiler requires extensive retargeting effort. -
Intermediate Representation and LLVM
CS153: Compilers Lecture 6: Intermediate Representation and LLVM Stephen Chong https://www.seas.harvard.edu/courses/cs153 Contains content from lecture notes by Steve Zdancewic and Greg Morrisett Announcements •Homework 1 grades returned •Style •Testing •Homework 2: X86lite •Due Tuesday Sept 24 •Homework 3: LLVMlite •Will be released Tuesday Sept 24 Stephen Chong, Harvard University 2 Today •Continue Intermediate Representation •Intro to LLVM Stephen Chong, Harvard University 3 Low-Level Virtual Machine (LLVM) •Open-Source Compiler Infrastructure •see llvm.org for full documentation •Created by Chris Lattner (advised by Vikram Adve) at UIUC •LLVM: An infrastructure for Multi-stage Optimization, 2002 •LLVM: A Compilation Framework for Lifelong Program Analysis and Transformation, 2004 •2005: Adopted by Apple for XCode 3.1 •Front ends: •llvm-gcc (drop-in replacement for gcc) •Clang: C, objective C, C++ compiler supported by Apple •various languages: Swift, ADA, Scala, Haskell, … •Back ends: •x86 / Arm / PowerPC / etc. •Used in many academic/research projects Stephen Chong, Harvard University 4 LLVM Compiler Infrastructure [Lattner et al.] LLVM llc frontends Typed SSA backend like IR code gen 'clang' jit Optimizations/ Transformations Analysis Stephen Chong, Harvard University 5 Example LLVM Code factorial-pretty.ll define @factorial(%n) { •LLVM offers a textual %1 = alloca %acc = alloca store %n, %1 representation of its IR store 1, %acc •files ending in .ll br label %start start: %3 = load %1 factorial64.c %4 = icmp sgt %3, 0 br %4, label -
Ryan Holland CSC415 Term Paper Final Draft Language: Swift (OSX)
Ryan Holland CSC415 Term Paper Final Draft Language: Swift (OSX) Apple released their new programming language "Swift" on June 2nd of this year. Swift replaces current versions of objective-C used to program in the OSX and iOS environments. According to Apple, swift will make programming apps for these environments "more fun". Swift is also said to bring a significant boost in performance compared to the equivalent objective-C. Apple has not released an official document stating the reasoning behind the launch of Swift, but speculation is that it was a move to attract more developers to the iOS platform. Swift development began in 2010 by Chris Lattner, but would later be aided by many other programmers. Swift employs ideas from many languages into one, not only from objective-C. These languages include Rust, Haskell, Ruby, Python, C#, CLU mainly but many others are also included. Apple says that most of the language is built for Cocoa and Cocoa Touch. Apple claims that Swift is more friendly to new programmers, also claiming that the language is just as enjoyable to learn as scripting languages. It supports a feature known as playgrounds, that allow programmers to make modifications on the fly, and see results immediately without the need to build the entire application first. Apple controls most aspects of this language, and since they control so much of it, they keep a detailed records of information about the language on their developer site. Most information within this paper will be based upon those records. Unlike most languages, Swift has a very small set of syntax that needs to be shown compared to other languages.