Cross-Platform Language Design
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ML Module Mania: a Type-Safe, Separately Compiled, Extensible Interpreter
ML Module Mania: A Type-Safe, Separately Compiled, Extensible Interpreter The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citation Ramsey, Norman. 2005. ML Module Mania: A Type-Safe, Separately Compiled, Extensible Interpreter. Harvard Computer Science Group Technical Report TR-11-05. Citable link http://nrs.harvard.edu/urn-3:HUL.InstRepos:25104737 Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#LAA ¡¢ £¥¤§¦©¨ © ¥ ! " $# %& !'( *)+ %¨,.-/£102©¨ 3¤4#576¥)+ %&8+9©¨ :1)+ 3';&'( )< %' =?>A@CBEDAFHG7DABJILKM GPORQQSOUT3V N W >BYXZ*[CK\@7]_^\`aKbF!^\K/c@C>ZdX eDf@hgiDf@kjmlnF!`ogpKb@CIh`q[UM W DABsr!@k`ajdtKAu!vwDAIhIkDi^Rx_Z!ILK[h[SI ML Module Mania: A Type-Safe, Separately Compiled, Extensible Interpreter Norman Ramsey Division of Engineering and Applied Sciences Harvard University Abstract An application that uses an embedded interpreter is writ- ten in two languages: Most code is written in the original, The new embedded interpreter Lua-ML combines extensi- host language (e.g., C, C++, or ML), but key parts can be bility and separate compilation without compromising type written in the embedded language. This organization has safety. The interpreter’s types are extended by applying a several benefits: sum constructor to built-in types and to extensions, then • Complex command-line arguments aren’t needed; the tying a recursive knot using a two-level type; the sum con- embedded language can be used on the command line. -
Tierless Web Programming in ML Gabriel Radanne
Tierless Web programming in ML Gabriel Radanne To cite this version: Gabriel Radanne. Tierless Web programming in ML. Programming Languages [cs.PL]. Université Paris Diderot (Paris 7), 2017. English. tel-01788885 HAL Id: tel-01788885 https://hal.archives-ouvertes.fr/tel-01788885 Submitted on 9 May 2018 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. Distributed under a Creative Commons Attribution - NonCommercial - ShareAlike| 4.0 International License Thèse de doctorat de l’Université Sorbonne Paris Cité Préparée à l’Université Paris Diderot au Laboratoire IRIF Ecole Doctorale 386 — Science Mathématiques De Paris Centre Tierless Web programming in ML par Gabriel Radanne Thèse de Doctorat d’informatique Dirigée par Roberto Di Cosmo et Jérôme Vouillon Thèse soutenue publiquement le 14 Novembre 2017 devant le jury constitué de Manuel Serrano Président du Jury Roberto Di Cosmo Directeur de thèse Jérôme Vouillon Co-Directeur de thèse Koen Claessen Rapporteur Jacques Garrigue Rapporteur Coen De Roover Examinateur Xavier Leroy Examinateur Jeremy Yallop Examinateur This work is licensed under a Creative Commons “Attribution- NonCommercial-ShareAlike 4.0 International” license. Abstract Eliom is a dialect of OCaml for Web programming in which server and client pieces of code can be mixed in the same file using syntactic annotations. -
Polyhedral Compilation As a Design Pattern for Compiler Construction
Polyhedral Compilation as a Design Pattern for Compiler Construction PLISS, May 19-24, 2019 [email protected] Polyhedra? Example: Tiles Polyhedra? Example: Tiles How many of you read “Design Pattern”? → Tiles Everywhere 1. Hardware Example: Google Cloud TPU Architectural Scalability With Tiling Tiles Everywhere 1. Hardware Google Edge TPU Edge computing zoo Tiles Everywhere 1. Hardware 2. Data Layout Example: XLA compiler, Tiled data layout Repeated/Hierarchical Tiling e.g., BF16 (bfloat16) on Cloud TPU (should be 8x128 then 2x1) Tiles Everywhere Tiling in Halide 1. Hardware 2. Data Layout Tiled schedule: strip-mine (a.k.a. split) 3. Control Flow permute (a.k.a. reorder) 4. Data Flow 5. Data Parallelism Vectorized schedule: strip-mine Example: Halide for image processing pipelines vectorize inner loop https://halide-lang.org Meta-programming API and domain-specific language (DSL) for loop transformations, numerical computing kernels Non-divisible bounds/extent: strip-mine shift left/up redundant computation (also forward substitute/inline operand) Tiles Everywhere TVM example: scan cell (RNN) m = tvm.var("m") n = tvm.var("n") 1. Hardware X = tvm.placeholder((m,n), name="X") s_state = tvm.placeholder((m,n)) 2. Data Layout s_init = tvm.compute((1,n), lambda _,i: X[0,i]) s_do = tvm.compute((m,n), lambda t,i: s_state[t-1,i] + X[t,i]) 3. Control Flow s_scan = tvm.scan(s_init, s_do, s_state, inputs=[X]) s = tvm.create_schedule(s_scan.op) 4. Data Flow // Schedule to run the scan cell on a CUDA device block_x = tvm.thread_axis("blockIdx.x") 5. Data Parallelism thread_x = tvm.thread_axis("threadIdx.x") xo,xi = s[s_init].split(s_init.op.axis[1], factor=num_thread) s[s_init].bind(xo, block_x) Example: Halide for image processing pipelines s[s_init].bind(xi, thread_x) xo,xi = s[s_do].split(s_do.op.axis[1], factor=num_thread) https://halide-lang.org s[s_do].bind(xo, block_x) s[s_do].bind(xi, thread_x) print(tvm.lower(s, [X, s_scan], simple_mode=True)) And also TVM for neural networks https://tvm.ai Tiling and Beyond 1. -
Seaflow Language Reference Manual Rohan Arora, Junyang Jin, Ho Sanlok Lee, Sarah Seidman Ra3091, Jj3132, Hl3436, Ss5311
Seaflow Language Reference Manual Rohan Arora, Junyang Jin, Ho Sanlok Lee, Sarah Seidman ra3091, jj3132, hl3436, ss5311 1 Introduction 3 2 Lexical Conventions 3 2.1 Comments 3 2.2 Identifiers 3 2.3 Keywords 3 2.4 Literals 3 3 Expressions and Statements 3 3.1 Expressions 4 3.1.1 Primary Expressions 4 3.1.1 Operators 4 3.1.2 Conditional expression 4 3.4 Statements 5 3.4.1 Declaration 5 3.4.2 Immutability 5 3.4.3 Observable re-assignment 5 4 Functions Junyang 6 4.1 Declaration 6 4.2 Scope rules 6 4.3 Higher Order Functions 6 5 Observables 7 5.1 Declaration 7 5.2 Subscription 7 5.3 Methods 7 6 Conversions 9 1 Introduction Seaflow is an imperative language designed to address the asynchronous event conundrum by supporting some of the core principles of ReactiveX and reactive programming natively. Modern applications handle many asynchronous events, but it is difficult to model such applications using programming languages such as Java and JavaScript. One popular solution among the developers is to use ReactiveX implementations in their respective languages to architect event-driven reactive models. However, since Java and JavaScript are not designed for reactive programming, it leads to complex implementations where multiple programming styles are mixed-used. Our goals include: 1. All data types are immutable, with the exception being observables, no pointers 2. The creation of an observable should be simple 3. Natively support core principles in the ReactiveX specification 2 Lexical Conventions 2.1 Comments We use the characters /* to introduce a comment, which terminates with the characters */. -
CS153: Compilers Lecture 19: Optimization
CS153: Compilers Lecture 19: Optimization Stephen Chong https://www.seas.harvard.edu/courses/cs153 Contains content from lecture notes by Steve Zdancewic and Greg Morrisett Announcements •HW5: Oat v.2 out •Due in 2 weeks •HW6 will be released next week •Implementing optimizations! (and more) Stephen Chong, Harvard University 2 Today •Optimizations •Safety •Constant folding •Algebraic simplification • Strength reduction •Constant propagation •Copy propagation •Dead code elimination •Inlining and specialization • Recursive function inlining •Tail call elimination •Common subexpression elimination Stephen Chong, Harvard University 3 Optimizations •The code generated by our OAT compiler so far is pretty inefficient. •Lots of redundant moves. •Lots of unnecessary arithmetic instructions. •Consider this OAT program: int foo(int w) { var x = 3 + 5; var y = x * w; var z = y - 0; return z * 4; } Stephen Chong, Harvard University 4 Unoptimized vs. Optimized Output .globl _foo _foo: •Hand optimized code: pushl %ebp movl %esp, %ebp _foo: subl $64, %esp shlq $5, %rdi __fresh2: movq %rdi, %rax leal -64(%ebp), %eax ret movl %eax, -48(%ebp) movl 8(%ebp), %eax •Function foo may be movl %eax, %ecx movl -48(%ebp), %eax inlined by the compiler, movl %ecx, (%eax) movl $3, %eax so it can be implemented movl %eax, -44(%ebp) movl $5, %eax by just one instruction! movl %eax, %ecx addl %ecx, -44(%ebp) leal -60(%ebp), %eax movl %eax, -40(%ebp) movl -44(%ebp), %eax Stephen Chong,movl Harvard %eax,University %ecx 5 Why do we need optimizations? •To help programmers… •They write modular, clean, high-level programs •Compiler generates efficient, high-performance assembly •Programmers don’t write optimal code •High-level languages make avoiding redundant computation inconvenient or impossible •e.g. -
JNI – C++ Integration Made Easy
JNI – C++ integration made easy Evgeniy Gabrilovich Lev Finkelstein [email protected] [email protected] Abstract The Java Native Interface (JNI) [1] provides interoperation between Java code running on a Java Virtual Machine and code written in other programming languages (e.g., C++ or assembly). The JNI is useful when existing libraries need to be integrated into Java code, or when portions of the code are implemented in other languages for improved performance. The Java Native Interface is extremely flexible, allowing Java methods to invoke native methods and vice versa, as well as allowing native functions to manipulate Java objects. However, this flexibility comes at the expense of extra effort for the native language programmer, who has to explicitly specify how to connect to various Java objects (and later to disconnect from them, to avoid resource leak). We suggest a template-based framework that relieves the C++ programmer from most of this burden. In particular, the proposed technique provides automatic selection of the right functions to access Java objects based on their types, automatic release of previously acquired resources when they are no longer necessary, and overall simpler interface through grouping of auxiliary functions. Introduction The Java Native Interface1 is a powerful framework for seamless integration between Java and other programming languages (called “native languages” in the JNI terminology). A common case of using the JNI is when a system architect wants to benefit from both worlds, implementing communication protocols in Java and computationally expensive algorithmic parts in C++ (the latter are usually compiled into a dynamic library, which is then invoked from the Java code). -
Difference Between Method Declaration and Signature
Difference Between Method Declaration And Signature Asiatic and relaxed Dillon still terms his tacheometry namely. Is Tom dirt or hierarchal after Zyrian Nelson hasting so variously? Heterozygous Henrique instals terribly. Chapter 15 Functions. How junior you identify a function? There play an important difference between schedule two forms of code block seeing the. Subroutines in C and Java are always expressed as functions methods which may. Only one params keyword is permitted in a method declaration. Complex constant and so, where you declare checked exception parameters which case, it prompts the method declaration group the habit of control passes the positional. Overview of methods method parameters and method return values. A whole object has the cash public attributes and methods. Defining Methods. A constant only be unanimous a type explicitly by doing constant declaration or. As a stop rule using prototypes is the preferred method as it. C endif Class HelloJNI Method sayHello Signature V JNIEXPORT. Method signature It consists of the method name just a parameter list window of. As I breathe in the difference between static and dynamic binding static methods are. Most electronic signature solutions in the United States fall from this broad. DEPRECATED Method declarations with type constraints and per source filter. Methods and Method Declaration in Java dummies. Class Methods Apex Developer Guide Salesforce Developers. Using function signatures to remove a library method Function signatures are known important snapshot of searching for library functions The F libraries. Many different kinds of parameters with rather subtle semantic differences. For addition as real numbers the distinction is somewhat moot because is. -
Comparative Studies of Programming Languages; Course Lecture Notes
Comparative Studies of Programming Languages, COMP6411 Lecture Notes, Revision 1.9 Joey Paquet Serguei A. Mokhov (Eds.) August 5, 2010 arXiv:1007.2123v6 [cs.PL] 4 Aug 2010 2 Preface Lecture notes for the Comparative Studies of Programming Languages course, COMP6411, taught at the Department of Computer Science and Software Engineering, Faculty of Engineering and Computer Science, Concordia University, Montreal, QC, Canada. These notes include a compiled book of primarily related articles from the Wikipedia, the Free Encyclopedia [24], as well as Comparative Programming Languages book [7] and other resources, including our own. The original notes were compiled by Dr. Paquet [14] 3 4 Contents 1 Brief History and Genealogy of Programming Languages 7 1.1 Introduction . 7 1.1.1 Subreferences . 7 1.2 History . 7 1.2.1 Pre-computer era . 7 1.2.2 Subreferences . 8 1.2.3 Early computer era . 8 1.2.4 Subreferences . 8 1.2.5 Modern/Structured programming languages . 9 1.3 References . 19 2 Programming Paradigms 21 2.1 Introduction . 21 2.2 History . 21 2.2.1 Low-level: binary, assembly . 21 2.2.2 Procedural programming . 22 2.2.3 Object-oriented programming . 23 2.2.4 Declarative programming . 27 3 Program Evaluation 33 3.1 Program analysis and translation phases . 33 3.1.1 Front end . 33 3.1.2 Back end . 34 3.2 Compilation vs. interpretation . 34 3.2.1 Compilation . 34 3.2.2 Interpretation . 36 3.2.3 Subreferences . 37 3.3 Type System . 38 3.3.1 Type checking . 38 3.4 Memory management . -
Behavioral Types in Programming Languages
Behavioral Types in Programming Languages Behavioral Types in Programming Languages iv Davide Ancona, DIBRIS, Università di Genova, Italy Viviana Bono, Dipartimento di Informatica, Università di Torino, Italy Mario Bravetti, Università di Bologna, Italy / INRIA, France Joana Campos, LaSIGE, Faculdade de Ciências, Universidade de Lisboa, Portugal Giuseppe Castagna, CNRS, IRIF, Univ Paris Diderot, Sorbonne Paris Cité, Paris, France Pierre-Malo Deniélou, Royal Holloway, University of London, UK Simon J. Gay, School of Computing Science, University of Glasgow, UK Nils Gesbert, Université Grenoble Alpes, France Elena Giachino, Università di Bologna, Italy / INRIA, France Raymond Hu, Department of Computing, Imperial College London, UK Einar Broch Johnsen, Institutt for informatikk, Universitetet i Oslo, Norway Francisco Martins, LaSIGE, Faculdade de Ciências, Universidade de Lisboa, Portugal Viviana Mascardi, DIBRIS, Università di Genova, Italy Fabrizio Montesi, University of Southern Denmark Rumyana Neykova, Department of Computing, Imperial College London, UK Nicholas Ng, Department of Computing, Imperial College London, UK Luca Padovani, Dipartimento di Informatica, Università di Torino, Italy Vasco T. Vasconcelos, LaSIGE, Faculdade de Ciências, Universidade de Lisboa, Portugal Nobuko Yoshida, Department of Computing, Imperial College London, UK Boston — Delft Foundations and Trends R in Programming Languages Published, sold and distributed by: now Publishers Inc. PO Box 1024 Hanover, MA 02339 United States Tel. +1-781-985-4510 www.nowpublishers.com [email protected] Outside North America: now Publishers Inc. PO Box 179 2600 AD Delft The Netherlands Tel. +31-6-51115274 The preferred citation for this publication is D. Ancona et al.. Behavioral Types in Programming Languages. Foundations and Trends R in Programming Languages, vol. 3, no. -
Structuring Languages As Object-Oriented Libraries
Structuring Languages as Object-Oriented Libraries Structuring Languages as Object-Oriented Libraries ACADEMISCH PROEFSCHRIFT ter verkrijging van de graad van doctor aan de Universiteit van Amsterdam op gezag van de Rector Magnificus prof. dr. ir. K. I. J. Maex ten overstaan van een door het College voor Promoties ingestelde commissie, in het openbaar te verdedigen in de Agnietenkapel op donderdag november , te . uur door Pablo Antonio Inostroza Valdera geboren te Concepción, Chili Promotiecommissie Promotores: Prof. Dr. P. Klint Universiteit van Amsterdam Prof. Dr. T. van der Storm Rijksuniversiteit Groningen Overige leden: Prof. Dr. J.A. Bergstra Universiteit van Amsterdam Prof. Dr. B. Combemale University of Toulouse Dr. C. Grelck Universiteit van Amsterdam Prof. Dr. P.D. Mosses Swansea University Dr. B.C.d.S. Oliveira The University of Hong Kong Prof. Dr. M. de Rijke Universiteit van Amsterdam Faculteit der Natuurwetenschappen, Wiskunde en Informatica The work in this thesis has been carried out at Centrum Wiskunde & Informatica (CWI) under the auspices of the research school IPA (Institute for Programming research and Algorith- mics) and has been supported by NWO, in the context of Jacquard Project .. “Next Generation Auditing: Data-Assurance as a Service”. Contents Introduction .Language Libraries . .Object Algebras . .Language Libraries with Object Algebras . .Origins of the Chapters . .Software Artifacts . .Dissertation Structure . Recaf: Java Dialects as Libraries .Introduction . .Overview.................................... .Statement Virtualization . .Full Virtualization . .Implementation of Recaf . .Case Studies . .Discussion . .Related Work . .Conclusion . Tracing Program Transformations with String Origins .Introduction . .String Origins . .Applications of String Origins . .Implementation . .Related Work . .Conclusion . Modular Interpreters with Implicit Context Propagation .Introduction . .Background . v Contents .Implicit Context Propagation . -
Blossom: a Language Built to Grow
Macalester College DigitalCommons@Macalester College Mathematics, Statistics, and Computer Science Honors Projects Mathematics, Statistics, and Computer Science 4-26-2016 Blossom: A Language Built to Grow Jeffrey Lyman Macalester College Follow this and additional works at: https://digitalcommons.macalester.edu/mathcs_honors Part of the Computer Sciences Commons, Mathematics Commons, and the Statistics and Probability Commons Recommended Citation Lyman, Jeffrey, "Blossom: A Language Built to Grow" (2016). Mathematics, Statistics, and Computer Science Honors Projects. 45. https://digitalcommons.macalester.edu/mathcs_honors/45 This Honors Project - Open Access is brought to you for free and open access by the Mathematics, Statistics, and Computer Science at DigitalCommons@Macalester College. It has been accepted for inclusion in Mathematics, Statistics, and Computer Science Honors Projects by an authorized administrator of DigitalCommons@Macalester College. For more information, please contact [email protected]. In Memory of Daniel Schanus Macalester College Department of Mathematics, Statistics, and Computer Science Blossom A Language Built to Grow Jeffrey Lyman April 26, 2016 Advisor Libby Shoop Readers Paul Cantrell, Brett Jackson, Libby Shoop Contents 1 Introduction 4 1.1 Blossom . .4 2 Theoretic Basis 6 2.1 The Potential of Types . .6 2.2 Type basics . .6 2.3 Subtyping . .7 2.4 Duck Typing . .8 2.5 Hindley Milner Typing . .9 2.6 Typeclasses . 10 2.7 Type Level Operators . 11 2.8 Dependent types . 11 2.9 Hoare Types . 12 2.10 Success Types . 13 2.11 Gradual Typing . 14 2.12 Synthesis . 14 3 Language Description 16 3.1 Design goals . 16 3.2 Type System . 17 3.3 Hello World . -
Phase-Ordering in Optimizing Compilers
Phase-ordering in optimizing compilers Matthieu Qu´eva Kongens Lyngby 2007 IMM-MSC-2007-71 Technical University of Denmark Informatics and Mathematical Modelling Building 321, DK-2800 Kongens Lyngby, Denmark Phone +45 45253351, Fax +45 45882673 [email protected] www.imm.dtu.dk Summary The “quality” of code generated by compilers largely depends on the analyses and optimizations applied to the code during the compilation process. While modern compilers could choose from a plethora of optimizations and analyses, in current compilers the order of these pairs of analyses/transformations is fixed once and for all by the compiler developer. Of course there exist some flags that allow a marginal control of what is executed and how, but the most important source of information regarding what analyses/optimizations to run is ignored- the source code. Indeed, some optimizations might be better to be applied on some source code, while others would be preferable on another. A new compilation model is developed in this thesis by implementing a Phase Manager. This Phase Manager has a set of analyses/transformations available, and can rank the different possible optimizations according to the current state of the intermediate representation. Based on this ranking, the Phase Manager can decide which phase should be run next. Such a Phase Manager has been implemented for a compiler for a simple imper- ative language, the while language, which includes several Data-Flow analyses. The new approach consists in calculating coefficients, called metrics, after each optimization phase. These metrics are used to evaluate where the transforma- tions will be applicable, and are used by the Phase Manager to rank the phases.