Improving the Compilation Process Using Program Annotations
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Generalized Jump Threading in Libfirm
Institut für Programmstrukturen und Datenorganisation (IPD) Lehrstuhl Prof. Dr.-Ing. Snelting Generalized Jump Threading in libFIRM Masterarbeit von Joachim Priesner an der Fakultät für Informatik Erstgutachter: Prof. Dr.-Ing. Gregor Snelting Zweitgutachter: Prof. Dr.-Ing. Jörg Henkel Betreuender Mitarbeiter: Dipl.-Inform. Andreas Zwinkau Bearbeitungszeit: 5. Oktober 2016 – 23. Januar 2017 KIT – Die Forschungsuniversität in der Helmholtz-Gemeinschaft www.kit.edu Zusammenfassung/Abstract Jump Threading (dt. „Sprünge fädeln“) ist eine Compileroptimierung, die statisch vorhersagbare bedingte Sprünge in unbedingte Sprünge umwandelt. Bei der Ausfüh- rung kann ein Prozessor bedingte Sprünge zunächst nur heuristisch mit Hilfe der Sprungvorhersage auswerten. Sie stellen daher generell ein Performancehindernis dar. Die Umwandlung ist insbesondere auch dann möglich, wenn das Sprungziel nur auf einer Teilmenge der zu dem Sprung führenden Ausführungspfade statisch be- stimmbar ist. In diesem Fall, der den überwiegenden Teil der durch Jump Threading optimierten Sprünge betrifft, muss die Optimierung Grundblöcke duplizieren, um jene Ausführungspfade zu isolieren. Verschiedene aktuelle Compiler enthalten sehr unterschiedliche Implementierungen von Jump Threading. In dieser Masterarbeit wird zunächst ein theoretischer Rahmen für Jump Threading vorgestellt. Sodann wird eine allgemeine Fassung eines Jump- Threading-Algorithmus entwickelt, implementiert und in diverser Hinsicht untersucht, insbesondere auf Wechselwirkungen mit anderen Optimierungen wie If -
Dominator Tree Certification and Independent Spanning Trees
Dominator Tree Certification and Independent Spanning Trees∗ Loukas Georgiadis1 Robert E. Tarjan2 October 29, 2018 Abstract How does one verify that the output of a complicated program is correct? One can formally prove that the program is correct, but this may be beyond the power of existing methods. Alternatively one can check that the output produced for a particular input satisfies the desired input-output relation, by running a checker on the input-output pair. Then one only needs to prove the correctness of the checker. But for some problems even such a checker may be too complicated to formally verify. There is a third alternative: augment the original program to produce not only an output but also a correctness certificate, with the property that a very simple program (whose correctness is easy to prove) can use the certificate to verify that the input-output pair satisfies the desired input-output relation. We consider the following important instance of this general question: How does one verify that the dominator tree of a flow graph is correct? Existing fast algorithms for finding dominators are complicated, and even verifying the correctness of a dominator tree in the absence of additional information seems complicated. We define a correctness certificate for a dominator tree, show how to use it to easily verify the correctness of the tree, and show how to augment fast dominator-finding algorithms so that they produce a correctness certificate. We also relate the dominator certificate problem to the problem of finding independent spanning trees in a flow graph, and we develop algorithms to find such trees. -
Maker-Breaker Total Domination Game Valentin Gledel, Michael A
Maker-Breaker total domination game Valentin Gledel, Michael A. Henning, Vesna Iršič, Sandi Klavžar To cite this version: Valentin Gledel, Michael A. Henning, Vesna Iršič, Sandi Klavžar. Maker-Breaker total domination game. 2019. hal-02021678 HAL Id: hal-02021678 https://hal.archives-ouvertes.fr/hal-02021678 Preprint submitted on 16 Feb 2019 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Maker-Breaker total domination game Valentin Gledel a Michael A. Henning b Vesna Irˇsiˇc c;d Sandi Klavˇzar c;d;e January 31, 2019 a Univ Lyon, Universit´eLyon 1, LIRIS UMR CNRS 5205, F-69621, Lyon, France [email protected] b Department of Pure and Applied Mathematics, University of Johannesburg, Auckland Park 2006, South Africa [email protected] c Faculty of Mathematics and Physics, University of Ljubljana, Slovenia [email protected] [email protected] d Institute of Mathematics, Physics and Mechanics, Ljubljana, Slovenia e Faculty of Natural Sciences and Mathematics, University of Maribor, Slovenia Abstract Maker-Breaker total domination game in graphs is introduced as a natu- ral counterpart to the Maker-Breaker domination game recently studied by Duch^ene,Gledel, Parreau, and Renault. -
2- Dominator Coloring for Various Graphs in Graph Theory
International Journal of Science and Research (IJSR) ISSN (Online): 2319-7064 Index Copernicus Value (2013): 6.14 | Impact Factor (2015): 6.391 2- Dominator Coloring for Various Graphs in Graph Theory A. Sangeetha Devi1, M. M. Shanmugapriya2 1Research Scholar, Department of Mathematics, Karpagam University, Coimbatore-21, India . 2Assistant Professor, Department of Mathematics, Karpagam University, Coimbatore-21, India Abstract: Given a graph G, the dominator coloring problem seeks a proper coloring of G with the additional property that every vertex in the graphG dominates at least 2-color class. In this paper, as an extension of Dominator coloring such that various graph using 2- dominator coloring has been discussed. Keywords: 2-Dominator Coloring, Barbell Graph, Star Graph, Banana Tree, Wheel Graph 1. Introduction of all the pendent vertices of G by „n‟ different colors. Introduce two new colors „퐶푖 „, „퐶푗 ‟alternatively to the In graph theory, coloring and dominating are two important subdividing vertices of G, C0 will dominates „퐶푖 „, „퐶푗 ‟. Also areas which have been extensively studied. The fundamental all the pendent verticies of G dominates at least two color parameter in the theory of graph coloring is the chromatic class. i.e, 1+n+2 ≤ 푛 + 3. Therefore χ푑,2 {C [ 푆1,푛 ] }≤ 푛 + number χ (G) of a graph G which is defined to be the 3 , n≥ 3. minimum number of colors required to color the vertices of G in such a way that no two adjacent vertices receive the Theorem 2.2 same color. If χ (G) = k, we say that G is k-chromatic. Let 푆 be a star graph, then χ (푆 ) =2, n 1,푛 푑,2 1,푛 .2 A dominating set S is a subset of the vertices in a graph such that every vertex in the graph either belongs to S or has a Proof: neighbor in S. -
An Experimental Study of Dynamic Dominators∗
An Experimental Study of Dynamic Dominators∗ Loukas Georgiadis1 Giuseppe F. Italiano2 Luigi Laura3 Federico Santaroni2 April 12, 2016 Abstract Motivated by recent applications of dominator computations, we consider the problem of dynamically maintaining the dominators of flow graphs through a sequence of insertions and deletions of edges. Our main theoretical contribution is a simple incremental algorithm that maintains the dominator tree of a flow graph with n vertices through a sequence of k edge in- sertions in O(m minfn; kg + kn) time, where m is the total number of edges after all insertions. Moreover, we can test in constant time if a vertex u dominates a vertex v, for any pair of query vertices u and v. Next, we present a new decremental algorithm to update a dominator tree through a sequence of edge deletions. Although our new decremental algorithm is not asymp- totically faster than repeated applications of a static algorithm, i.e., it runs in O(mk) time for k edge deletions, it performs well in practice. By combining our new incremental and decremen- tal algorithms we obtain a fully dynamic algorithm that maintains the dominator tree through intermixed sequence of insertions and deletions of edges. Finally, we present efficient imple- mentations of our new algorithms as well as of existing algorithms, and conduct an extensive experimental study on real-world graphs taken from a variety of application areas. 1 Introduction A flow graph G = (V; E; s) is a directed graph with a distinguished start vertex s 2 V . A vertex v is reachable in G if there is a path from s to v; v is unreachable if no such path exists. -
Static Analysis for Bsplib Programs Filip Jakobsson
Static Analysis for BSPlib Programs Filip Jakobsson To cite this version: Filip Jakobsson. Static Analysis for BSPlib Programs. Distributed, Parallel, and Cluster Computing [cs.DC]. Université d’Orléans, 2019. English. NNT : 2019ORLE2005. tel-02920363 HAL Id: tel-02920363 https://tel.archives-ouvertes.fr/tel-02920363 Submitted on 24 Aug 2020 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. UNIVERSITÉ D’ORLÉANS ÉCOLE DOCTORALE MATHÉMATIQUES, INFORMATIQUE, PHYSIQUE THÉORIQUE ET INGÉNIERIE DES SYSTÈMES LABORATOIRE D’INFORMATIQUE FONDAMENTALE D’ORLÉANS HUAWEI PARIS RESEARCH CENTER THÈSE présentée par : Filip Arvid JAKOBSSON soutenue le : 28 juin 2019 pour obtenir le grade de : Docteur de l’université d’Orléans Discipline : Informatique Static Analysis for BSPlib Programs THÈSE DIRIGÉE PAR : Frédéric LOULERGUE Professeur, University Northern Arizona et Université d’Orléans RAPPORTEURS : Denis BARTHOU Professeur, Bordeaux INP Herbert KUCHEN Professeur, WWU Münster JURY : Emmanuel CHAILLOUX Professeur, Sorbonne Université, Président Gaétan HAINS Ingénieur-Chercheur, Huawei Technologies, Encadrant Wijnand SUIJLEN Ingénieur-Chercheur, Huawei Technologies, Encadrant Wadoud BOUSDIRA Maître de conference, Université d’Orléans, Encadrante Frédéric DABROWSKI Maître de conference, Université d’Orléans, Encadrant Acknowledgments Firstly, I am grateful to the reviewers for taking the time to read this doc- ument, and their insightful and helpful remarks that have greatly helped its quality. -
Towards Source-Level Timing Analysis of Embedded Software Using Functional Verification Methods
Fakultat¨ fur¨ Elektrotechnik und Informationstechnik Technische Universitat¨ Munchen¨ Towards Source-Level Timing Analysis of Embedded Software Using Functional Verification Methods Martin Becker, M.Sc. Vollst¨andigerAbdruck der von der Fakult¨at f¨urElektrotechnik und Informationstechnik der Technischen Universit¨atM¨unchenzur Erlangung des akademischen Grades eines Doktor-Ingenieurs (Dr.-Ing.) genehmigten Dissertation. Vorsitzender: Prof. Dr. sc. techn. Andreas Herkersdorf Pr¨ufendeder Dissertation: 1. Prof. Dr. sc. Samarjit Chakraborty 2. Prof. Dr. Marco Caccamo 3. Prof. Dr. Daniel M¨uller-Gritschneder Die Dissertation wurde am 13.06.2019 bei der Technischen Universit¨atM¨uncheneingereicht und durch die Fakult¨atf¨urElektrotechnik und Informationstechnik am 21.04.2020 angenommen. Abstract *** Formal functional verification of source code has become more prevalent in recent years, thanks to the increasing number of mature and efficient analysis tools becoming available. Developers regularly make use of them for bug-hunting, and produce software with fewer de- fects in less time. On the other hand, the temporal behavior of software is equally important, yet rarely analyzed formally, but typically determined through profiling and dynamic testing. Although methods for formal timing analysis exist, they are separated from functional veri- fication, and difficult to use. Since the timing of a program is a product of the source code and the hardware it is running on – e.g., influenced by processor speed, caches and branch predictors – established methods of timing analysis take place at instruction level, where enough details are available for the analysis. During this process, users often have to provide instruction-level hints about the program, which is a tedious and error-prone process, and perhaps the reason why timing analysis is not as widely performed as functional verification. -
Control Flow Graphs
CONTROL FLOW GRAPHS PROGRAM ANALYSIS AND OPTIMIZATION – DCC888 Fernando Magno Quintão Pereira [email protected] The material in these slides have been taken from the "Dragon Book", Secs 8.5 – 8.7, by Aho et al. Intermediate Program Representations • Optimizing compilers and human beings do not see the program in the same way. – We are more interested in source code. – But, source code is too different from machine code. – Besides, from an engineering point of view, it is better to have a common way to represent programs in different languages, and target different architectures. Fortran PowerPC COBOL x86 Front Back Optimizer Lisp End End ARM … … Basic Blocks and Flow Graphs • Usually compilers represent programs as control flow graphs (CFG). • A control flow graph is a directed graph. – Nodes are basic blocks. – There is an edge from basic block B1 to basic block B2 if program execution can flow from B1 to B2. • Before defining basic void identity(int** a, int N) { int i, j; block, we will illustrate for (i = 0; i < N; i++) { this notion by showing the for (j = 0; j < N; j++) { a[i][j] = 0; CFG of the function on the } right. } for (i = 0; i < N; i++) { What does a[i][i] = 1; this program } do? } The Low Level Virtual Machine • We will be working with a compilation framework called The Low Level Virtual Machine, or LLVM, for short. • LLVM is today the most used compiler in research. • Additionally, this compiler is used in many important companies: Apple, Cray, Google, etc. The front-end Machine independent Machine dependent that parses C optimizations, such as optimizations, such into bytecodes constant propagation as register allocation ../0 %"&'( *+, ""% !"#$% !"#$)% !"#$)% !"#$- Using LLVM to visualize a CFG • We can use the opt tool, the LLVM machine independent optimizer, to visualize the control flow graph of a given function $> clang -c -emit-llvm identity.c -o identity.bc $> opt –view-cfg identity.bc • We will be able to see the CFG of our target program, as long as we have the tool DOT installed in our system. -
Durham E-Theses
Durham E-Theses Hypergraph Partitioning in the Cloud LOTFIFAR, FOAD How to cite: LOTFIFAR, FOAD (2016) Hypergraph Partitioning in the Cloud, Durham theses, Durham University. Available at Durham E-Theses Online: http://etheses.dur.ac.uk/11529/ Use policy The full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that: • a full bibliographic reference is made to the original source • a link is made to the metadata record in Durham E-Theses • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders. Please consult the full Durham E-Theses policy for further details. Academic Support Oce, Durham University, University Oce, Old Elvet, Durham DH1 3HP e-mail: [email protected] Tel: +44 0191 334 6107 http://etheses.dur.ac.uk Hypergraph Partitioning in the Cloud Foad Lotfifar Abstract The thesis investigates the partitioning and load balancing problem which has many applications in High Performance Computing (HPC). The application to be partitioned is described with a graph or hypergraph. The latter is of greater interest as hypergraphs, compared to graphs, have a more general structure and can be used to model more complex relationships between groups of objects such as non- symmetric dependencies. Optimal graph and hypergraph partitioning is known to be NP-Hard but good polynomial time heuristic algorithms have been proposed. -
GCC Internals
GCC Internals Diego Novillo [email protected] Red Hat Canada CGO 2007 San Jose, California March 2007 Outline 1. Overview 2. Source code organization 3. Internal architecture 4. Passes NOTE: Internal information valid for GCC mainline as of 2007-03-02 11 March 2007 GCC Internals - 2 1. Overview ➢ Major features ➢ Brief history ➢ Development model 11 March 2007 GCC Internals - 3 Major Features Availability – Free software (GPL) – Open and distributed development process – System compiler for popular UNIX variants – Large number of platforms (deeply embedded to big iron) – Supports all major languages: C, C++, Java, Fortran 95, Ada, Objective-C, Objective-C++, etc 11 March 2007 GCC Internals - 4 Major Features Code quality – Bootstraps on native platforms – Warning-free – Extensive regression testsuite – Widely deployed in industrial and research projects – Merit-based maintainership appointed by steering committee – Peer review by maintainers – Strict coding standards and patch reversion policy 11 March 2007 GCC Internals - 5 Major Features Analysis/Optimization – SSA-based high-level global optimizer – Constraint-based points-to alias analysis – Data dependency analysis based on chains of recurrences – Feedback directed optimization – Interprocedural optimization – Automatic pointer checking instrumentation – Automatic loop vectorization – OpenMP support 11 March 2007 GCC Internals - 6 1. Overview ➢ Major features ➢ Brief history ➢ Development model 11 March 2007 GCC Internals - 7 Brief History GCC 1 (1987) – Inspired on Pastel compiler -
Organization Control-Flow Graphs Dominators
10/14/2019 Organization • Dominator relation of CFGs Dominators, – postdominator relation control-dependence • Dominator tree and SSA form • Computing dominator relation and tree – Dataflow algorithm – Lengauer and Tarjan algorithm • Control-dependence relation • SSA form 12 Control-flow graphs Dominators START • CFG is a directed graph START • Unique node START from which • In a CFG G, node a is all nodes in CFG are reachable a said to dominate node a • Unique node END reachable from b b all nodes b if every path from • Dummy edge to simplify c c discussion START END START to b contains • Path in CFG: sequence of nodes, de de possibly empty, such that a. successive nodes in sequence are connected in CFG by edge f • Dominance relation: f – If x is first node in sequence and y is last node, we will write the path g relation on nodes g as x * y – If path is non-empty (has at least – We will write a dom b one edge) we will write x + y END if a dominates b END 34 1 10/14/2019 Example Computing dominance relation • Dataflow problem: START START A B C D E F G END A START x xxxxxxx x Domain: powerset of nodes in CFG A x x x x xxx B B x x x xxx N C C Dom(N) = {N} U ∩ Dom(M) D x M ε pred(N) DE E x F xx F G x Find greatest solution. END x G Work through example on previous slide to check this. Question: what do you get if you compute least solution? END 56 Properties of dominance Example of proof • Dominance is • Let us prove that dominance is transitive. -
Compiler Construction
Compiler construction PDF generated using the open source mwlib toolkit. See http://code.pediapress.com/ for more information. PDF generated at: Sat, 10 Dec 2011 02:23:02 UTC Contents Articles Introduction 1 Compiler construction 1 Compiler 2 Interpreter 10 History of compiler writing 14 Lexical analysis 22 Lexical analysis 22 Regular expression 26 Regular expression examples 37 Finite-state machine 41 Preprocessor 51 Syntactic analysis 54 Parsing 54 Lookahead 58 Symbol table 61 Abstract syntax 63 Abstract syntax tree 64 Context-free grammar 65 Terminal and nonterminal symbols 77 Left recursion 79 Backus–Naur Form 83 Extended Backus–Naur Form 86 TBNF 91 Top-down parsing 91 Recursive descent parser 93 Tail recursive parser 98 Parsing expression grammar 100 LL parser 106 LR parser 114 Parsing table 123 Simple LR parser 125 Canonical LR parser 127 GLR parser 129 LALR parser 130 Recursive ascent parser 133 Parser combinator 140 Bottom-up parsing 143 Chomsky normal form 148 CYK algorithm 150 Simple precedence grammar 153 Simple precedence parser 154 Operator-precedence grammar 156 Operator-precedence parser 159 Shunting-yard algorithm 163 Chart parser 173 Earley parser 174 The lexer hack 178 Scannerless parsing 180 Semantic analysis 182 Attribute grammar 182 L-attributed grammar 184 LR-attributed grammar 185 S-attributed grammar 185 ECLR-attributed grammar 186 Intermediate language 186 Control flow graph 188 Basic block 190 Call graph 192 Data-flow analysis 195 Use-define chain 201 Live variable analysis 204 Reaching definition 206 Three address