Automated Fortran–C++ Bindings for Scientific Applications

Total Page:16

File Type:pdf, Size:1020Kb

Automated Fortran–C++ Bindings for Scientific Applications Automated Fortran–C++ Bindings for Scientific Applications Seth R Johnson High Performance Computing Methods & Applications Team Reactor and Nuclear Systems Division Oak Ridge National Laboratory ORNL is managed by UT–Battelle, LLC for the US Department of Energy Project collaborators: Matt Bement, Kate Evans, Tim Fuller, Andrey Prokopenko github.com/swig-fortran Motivation • C++ library developers: expand user base, more opportunities for development and follow-on funding • Fortran scientific app developers: use newly exposed algorithms and tools for your code • Multiphysics project integration: in-memory coupling of C++ physics code to Fortran physics code • Transitioning application teams: bite-size migration from Fortran to C++ !2 Background • Exascale Computing Project: many petascale scientific app codes still are primarily Fortran • Numerical/scientific libraries are primarily C/C++ • Expose Trilinos solver library to Fortran app developers: ForTrilinos product !3 Supported SWIG: Simplified Wrapper and Interface Generator Languages • Allegro CL • C# • CFFI • CLISP • Chicken • Generate interfaces to existing C and C++ code and data • D • Go types so that a target language can invoke functions and • Guile use the data • Java • Javascript • “Glue” code: flat C-linkage wrappers to C++ functions, • Lua • Modula-3 corresponding interfaces in target language • Mzscheme • OCAML • Does not couple target languages to other target languages • Octave • Perl • PHP • Does not parse target languages or create C++ proxy • Python wrappers • R • Ruby • Scilab • Tcl • UFFI !4 SWIG execution sequence • SWIG reads .i interface file which may %include other C/C++ headers to parse them • Interface file can be as little as a couple of lines for simple interfaces • More difficult C++/Fortran conversions require more interface code • SWIG generates source code files: .cxx and .f90 • This wrapper code can be distributed like regular source files • Library users don’t need to know SWIG User-written code SWIG-generated code Foo.cxx Foo.hh SWIG foo.f90 main.f90 Foo.i foo_wrap.cxx !5 Control flow and data conversion Call “native” procedure user.f90 Public module procedure Convert Fortran types to ISO_C_BINDING types module.f90 Call BIND(C) interface • Fortran 2003 standard defines C-compatible datatypes • Use only Fortran-compatible ISO C datatypes extern "C" wrapper function Convert C type to C++ type • Minimize data movement of numerical arrays Call C++ library function module_wrap.cxx C++ Library code library.cxx !6 Features • Primitive types • Function overloading • Enumerations • Template instantiation • Classes (with inheritance) • Compile-time constants • C strings and std::string • Exception handling • Function pointers • OpenACC and Thrust • Arrays and std::vector !7 Simple addition function: input and generated C code F/C interface #ifndef simplest_h SWIGEXPORT int _wrap_add( #define simplest_h int const *farg1, int add(int a, int b); #endif int const *farg2) { int fresult ; Input argument int arg1 ; conversion simplest.h int arg2 ; int result; arg1 = (int)(*farg1); arg2 = (int)(*farg2); %module simplest Wrapped result = (int)add(arg1,arg2); function call %include "simplest.h" fresult = (int)(result); return fresult; } simplest.i Output simplest_wrap.c argument conversion !8 Simple addition function: generated Fortran Fortran proxy function module simplest F/C .... use, intrinsic :: ISO_C_BINDING implicit none interface function add(a, b) & private result(swig_result) public :: add integer(C_INT) :: swig_result interface integer(C_INT), intent(in) :: a function swigc_add(farg1, farg2) & integer(C_INT), intent(in) :: b bind(C, name="_wrap_add") & integer(C_INT) :: fresult Input result(fresult) integer(C_INT) :: farg1 argument integer(C_INT), intent(in) :: farg1 integer(C_INT) :: farg2 integer(C_INT), intent(in) :: farg2 conversion integer(C_INT) :: fresult farg1 = a Wrapper end function farg2 = b function call end interface fresult = swigc_add(farg1, farg2) contains Output swig_result = fresult argument end function .... conversion end module simplest.f90 !9 Simple addition function: the part app devs care about SWIGEXPORT int swigc_add(int const *farg1, program main int const *farg2); use simplest, only : add write (0,*) add(10,20) end program simplest_wrap.c module simplest use, intrinsic :: ISO_C_BINDING main.f90 … contains function add(a, b) & result(swigf_result) integer(C_INT) :: swigf_result integer(C_INT), intent(in) :: a integer(C_INT), intent(in) :: b … end function $ ./main.exe end module simplest.f90 30 !10 Templated class Insert raw C++ template<typename T> %module "templated" Tell SWIG to class Thing { code into parse the T val_; generated %{ header file public: wrapper file #include "templated.hpp" Thing(T val); %} T get() const; %include "templated.hpp" }; // Instantiate templated classes template<typename T> %template(Thing_Int) Thing<int>; void print_thing(const Thing<T>& t); %template(Thing_Dbl) Thing<double>; // Instantiate and overload a function Instantiate %template(print_thing) print_thing<int>; templates %template(print_thing) print_thing<double>; at SWIG time templated.i !11 Templated class: generated Fortran wrapper code Memory module templated ownership interface print_thing … module procedure swigf_print_thing__SWIG_1, integer, parameter, public :: swig_cmem_own_bit = 0 swigf_print_thing__SWIG_2 integer, parameter, public :: swig_cmem_rvalue_bit = 1 end interface integer, parameter, public :: swig_cmem_const_bit = 2 public :: print_thing type, bind(C) :: SwigClassWrapper interface Overloaded type(C_PTR), public :: cptr = C_NULL_PTR subroutine swigc_delete_Thing_Int(farg1) & integer(C_INT), public :: cmemflags = 0 bind(C, name="_wrap_delete_Thing_Int") function end type ! class Thing< int > Opaque class … type, public :: Thing_Int wrapper contains type(SwigClassWrapper), public :: swigdata subroutine swigf_release_Thing_Int(self) Call delete if contains use, intrinsic :: ISO_C_BINDING we “own” procedure :: get => swigf_Thing_Int_get class(Thing_Int), intent(inout) :: self procedure :: release => swigf_release_Thing_Int type(SwigClassWrapper) :: farg1 the memory procedure, private :: swigf_Thing_Int_op_assign__ farg1 = self%swigdata generic :: assignment(=) => swigf_Thing_Int_op_assign__ end type Thing_Int if (btest(farg1%cmemflags, swig_cmem_own_bit)) then interface Thing_Int call swigc_delete_Thing_Int(farg1) module procedure swigf_create_Thing_Int Fortran endif end interface proxy class farg1%cptr = C_NULL_PTR ! class Thing< double > Second farg1%cmemflags = 0 type, public :: Thing_Dbl self%swigdata = farg1 … template end subroutine end type Thing_Dbl … instantiation … end module templated.f90 (2/2) !12 Exception handling %module except program main %include <std_except.i> use except, only : do_it, do_it_again, ierr, get_serr %exception { call do_it(-3) if (ierr /= 0) then SWIG_check_unhandled_exception(); write(0,*) "Got error ", ierr, ": ", get_serr() try { Replaced with ierr = 0 $action endif } wrapper call call do_it(2) catch (const std::exception& e) { call do_it(-2) SWIG_exception(SWIG_RuntimeError, e.what()); call do_it_again(321) } end program } main.f90 %{ #include <stdexcept> Got error -3 : In do_it(int): #include <iostream> %} NOOOOO %inline { Yes! I got 2 void do_it(int i) { terminate called after throwing an if (i < 0) throw std::logic_error("NOOOOO"); instance of 'std::runtime_error' std::cout << "Yes! I got " << i what(): An unhandled exception << std::endl; occurred before a call to } void do_it_again(int i) { do_it(i); } do_it_again(int); in do_it(int): NOOOOO } !13 Array views subroutine sort(data) use, intrinsic :: ISO_C_BINDING integer(C_INT), dimension(:), target :: data integer(C_INT), pointer :: farg1_view %module algorithm type(SwigArrayWrapper) :: farg1 Treat as native if (size(data) > 0) then %{ Fortran array farg1_view => data(1) #include <algorithm> farg1%data = c_loc(farg1_view) %} farg1%size = size(data) else %include <typemaps.i> farg1%data = c_null_ptr %apply (SWIGTYPE *DATA, size_t SIZE) { farg1%size = 0 (int* data, std::size_t size) }; end if call swigc_sort(farg1) %inline { end subroutine void sort(int* data, std::size_t size) { program main std::sort(data, data + size); use, intrinsic :: ISO_C_BINDING } use algorithm, only : sort } implicit none integer(C_INT), dimension(6) & :: test_int = (/ 3, -1, 7, 3, 1, 5 /) call sort(test_int) write (*,*) test_int end program !14 Thrust + OpenACC %module thrustacc; program test_thrustacc use thrustacc %include <openacc.i> implicit none %include <thrust.i> integer, parameter :: n = 32768 integer :: i real, dimension(:), allocatable :: a %{ #include <thrust/sort.h> ! Generate N uniform numbers on [0,1) %} allocate(a(n)) %inline %{ call random_number(a) template<typename T> void swig_thrust_sort(thrust::device_ptr<T> !$acc data copy(a) DATA, size_t SIZE) { !$acc kernels do i = 1,n thrust::sort(DATA, DATA + SIZE); a(i) = a(i) * 10 + i } end do %} !$acc end kernels call sort(a) %template(sort) swig_thrust_sort<int>; !$acc end data %template(sort) swig_thrust_sort<float>; write(*,*) sum(a) %template(sort) swig_thrust_sort<double>; end program !15 Automatic BIND(C) wrapping %module bindc module bindc Only generate … interface code type, bind(C), public :: Point %fortranbindc; real(C_FLOAT), public :: x real(C_FLOAT), public :: y %fortran_struct(Point) Don’t create real(C_FLOAT), public :: z end type Point proxy class … %inline { interface typedef struct { float x, y, z; } Point; subroutine print_point(p) & bind(C, name="print_point")
Recommended publications
  • The Shogun Machine Learning Toolbox
    The Shogun Machine Learning Toolbox Heiko Strathmann, Gatsby Unit, UCL London Open Machine Learning Workshop, MSR, NY August 22, 2014 A bit about Shogun I Open-Source tools for ML problems I Started 1999 by SÖren Sonnenburg & GUNnar Rätsch, made public in 2004 I Currently 8 core-developers + 20 regular contributors I Purely open-source community driven I In Google Summer of Code since 2010 (29 projects!) Ohloh - Summary Ohloh - Code Supervised Learning Given: x y n , want: y ∗ x ∗ I f( i ; i )gi=1 j I Classication: y discrete I Support Vector Machine I Gaussian Processes I Logistic Regression I Decision Trees I Nearest Neighbours I Naive Bayes I Regression: y continuous I Gaussian Processes I Support Vector Regression I (Kernel) Ridge Regression I (Group) LASSO Unsupervised Learning Given: x n , want notion of p x I f i gi=1 ( ) I Clustering: I K-Means I (Gaussian) Mixture Models I Hierarchical clustering I Latent Models I (K) PCA I Latent Discriminant Analysis I Independent Component Analysis I Dimension reduction I (K) Locally Linear Embeddings I Many more... And many more I Multiple Kernel Learning I Structured Output I Metric Learning I Variational Inference I Kernel hypothesis testing I Deep Learning (whooo!) I ... I Bindings to: LibLinear, VowpalWabbit, etc.. http://www.shogun-toolbox.org/page/documentation/ notebook Some Large-Scale Applications I Splice Site prediction: 50m examples of 200m dimensions I Face recognition: 20k examples of 750k dimensions ML in Practice I Modular data represetation I Dense, Sparse, Strings, Streams, ... I Multiple types: 8-128 bit word size I Preprocessing tools I Evaluation I Cross-Validation I Accuracy, ROC, MSE, ..
    [Show full text]
  • SWIG and Ruby
    SWIG and Ruby David Grayson Las Vegas Ruby Meetup 2014-09-10 SWIG ● SWIG stands for: Simplified Wrapper and Interface Generator ● SWIG helps you access C or C++ code from 22 different languages, including Ruby SWIG inputs and outputs Ruby C extension SWIG interface file (.i) source (.c or .cxx) Simple C++ example libdavid.h: libdavid.i #include <stdio.h> %module "david" class David %{ { #include <libdavid.h> public: %} David(int x) { class David this->x = x; { } public: David(int x); void announce() void announce(); { int x; }; printf("David %d\n", x); } int x; }; Compiling Simple C++ example extconf.rb require 'mkmf' system('swig -c++ -ruby libdavid.i') or abort create_makefile('david') Commands to run: $ ruby extconf.rb # create libdavid_wrap.cxx and Makefile $ make # compile david.so $ irb -r./david # try it out irb(main):001:0> d = David::David.new(4) => #<David::David:0x007f40090a5280 @__swigtype__="_p_David"> irb(main):002:0> d.announce David 4 => nil (This example worked for me with SWIG 3.0.2 and Ruby 2.1.2.) That example was pretty simple ● All code was in a .h file ● No external libraries ● Simple data types ● No consideration of deployment ...but SWIG has tons of features C: C++: ● All ISO C datatypes ● All C++ datatypes ● Global functions ● References ● Global variables, constants ● Pointers to members ● Structures and unions ● Classes ● Pointers ● (Multiple) inheritance ● (Multidimensional) arrays ● Overloaded functions ● Pointers to functions ● Overloaded methods ● Variable length arguments ● Overloaded operators ● Typedefs ● Static members ● Enums ● Namespaces ● Templates ● Nested classes ... SWIG Typemaps ● Define custom ways to map between scripting- language types and C++ types. ● Can be used to add and remove parameters from of exposed functions.
    [Show full text]
  • PHP Beyond the Web Shell Scripts, Desktop Software, System Daemons and More
    PHP Beyond the web Shell scripts, desktop software, system daemons and more Rob Aley This book is for sale at http://leanpub.com/php This version was published on 2013-11-25 This is a Leanpub book. Leanpub empowers authors and publishers with the Lean Publishing process. Lean Publishing is the act of publishing an in-progress ebook using lightweight tools and many iterations to get reader feedback, pivot until you have the right book and build traction once you do. ©2012 - 2013 Rob Aley Tweet This Book! Please help Rob Aley by spreading the word about this book on Twitter! The suggested hashtag for this book is #phpbeyondtheweb. Find out what other people are saying about the book by clicking on this link to search for this hashtag on Twitter: https://twitter.com/search?q=#phpbeyondtheweb Contents Welcome ............................................ i About the author ...................................... i Acknowledgements ..................................... ii 1 Introduction ........................................ 1 1.1 “Use PHP? We’re not building a website, you know!”. ............... 1 1.2 Are you new to PHP? ................................. 2 1.3 Reader prerequisites. Or, what this book isn’t .................... 3 1.4 An important note for Windows and Mac users ................... 3 1.5 About the sample code ................................ 4 1.6 External resources ................................... 4 1.7 Book formats/versions available, and access to updates ............... 5 1.8 English. The Real English. .............................. 5 2 Getting away from the Web - the basics ......................... 6 2.1 PHP without a web server .............................. 6 2.2 PHP versions - what’s yours? ............................. 7 2.3 A few good reasons NOT to do it in PHP ...................... 8 2.4 Thinking about security ...............................
    [Show full text]
  • Analytic Center Cutting Plane Method for Multiple Kernel Learning
    Ann Math Artif Intell DOI 10.1007/s10472-013-9331-4 Analytic center cutting plane method for multiple kernel learning Sharon Wulff · Cheng Soon Ong © Springer Science+Business Media Dordrecht 2013 Abstract Multiple Kernel Learning (MKL) is a popular generalization of kernel methods which allows the practitioner to optimize over convex combinations of kernels. We observe that many recent MKL solutions can be cast in the framework of oracle based optimization, and show that they vary in terms of query point generation. The popularity of such methods is because the oracle can fortuitously be implemented as a support vector machine. Motivated by the success of centering approaches in interior point methods, we propose a new approach to optimize the MKL objective based on the analytic center cutting plane method (accpm). Our experimental results show that accpm outperforms state of the art in terms of rate of convergence and robustness. Further analysis sheds some light as to why MKL may not always improve classification accuracy over naive solutions. Keywords Multiple kernel learning · accpm · Oracle methods · Machine learning Mathematics Subject Classification (2010) 68T05 1 Introduction Kernel methods, for example the support vector machine (SVM), are a class of algorithms that consider only the similarity between examples [1]. A kernel function S. Wulff Department of Computer Science, ETH, Zürich, Switzerland e-mail: [email protected] C. S. Ong (B) NICTA, The University of Melbourne, Melbourne, Australia e-mail: [email protected] S. Wulff, C.S. Ong k implicitly maps examples x to a feature space given by a feature map via the identity k(xi, x j) = (xi), (x j) .
    [Show full text]
  • Python and Epics: Channel Access Interface to Python
    Python and Epics: Channel Access Interface to Python Matthew Newville Consortium for Advanced Radiation Sciences University of Chicago October 12, 2010 http://cars9.uchicago.edu/software/python/pyepics3/ Matthew Newville (CARS, Univ Chicago) Epics and Python October 12, 2010 Why Python? The Standard Answers Clean Syntax Easy to learn, remember, and read High Level Language No pointers, dynamic memory, automatic memory Cross Platform code portable to Unix, Windows, Mac. Object Oriented full object model, name spaces. Also: procedural! Extensible with C, C++, Fortran, Java, .NET Many Libraries GUIs, Databases, Web, Image Processing, Array math Free Both senses of the word. No, really: completely free. Matthew Newville (CARS, Univ Chicago) Epics and Python October 12, 2010 Why Python? The Real Answer Scientists use Python. Matthew Newville (CARS, Univ Chicago) Epics and Python October 12, 2010 All of these tools use the C implementation of Python. NOT Jython (Python in Java) or IronPython (Python in .NET): I am not talking about Jython. Why Do Scientists Use Python? Python is great. The tools are even better: numpy Fast arrays. matplotlib Excellent Plotting library scipy Numerical Algorithms (FFT, lapack, fitting, . ) f2py Wrapping Fortran for Python sage Symbolic math (ala Maple, Mathematica) GUI Choices Tk, wxWidgets, Qt, . Free Python is Free. All these tools are Free (BSD). Matthew Newville (CARS, Univ Chicago) Epics and Python October 12, 2010 Why Do Scientists Use Python? Python is great. The tools are even better: numpy Fast arrays. matplotlib Excellent Plotting library scipy Numerical Algorithms (FFT, lapack, fitting, . ) f2py Wrapping Fortran for Python sage Symbolic math (ala Maple, Mathematica) GUI Choices Tk, wxWidgets, Qt, .
    [Show full text]
  • Foreign Library Interface by Daniel Adler Dia Applications That Can Run on a Multitude of Plat- Forms
    30 CONTRIBUTED RESEARCH ARTICLES Foreign Library Interface by Daniel Adler dia applications that can run on a multitude of plat- forms. Abstract We present an improved Foreign Function Interface (FFI) for R to call arbitary na- tive functions without the need for C wrapper Foreign function interfaces code. Further we discuss a dynamic linkage framework for binding standard C libraries to FFIs provide the backbone of a language to inter- R across platforms using a universal type infor- face with foreign code. Depending on the design of mation format. The package rdyncall comprises this service, it can largely unburden developers from the framework and an initial repository of cross- writing additional wrapper code. In this section, we platform bindings for standard libraries such as compare the built-in R FFI with that provided by (legacy and modern) OpenGL, the family of SDL rdyncall. We use a simple example that sketches the libraries and Expat. The package enables system- different work flow paths for making an R binding to level programming using the R language; sam- a function from a foreign C library. ple applications are given in the article. We out- line the underlying automation tool-chain that extracts cross-platform bindings from C headers, FFI of base R making the repository extendable and open for Suppose that we wish to invoke the C function sqrt library developers. of the Standard C Math library. The function is de- clared as follows in C: Introduction double sqrt(double x); We present an improved Foreign Function Interface The .C function from the base R FFI offers a call (FFI) for R that significantly reduces the amount of gate to C code with very strict conversion rules, and C wrapper code needed to interface with C.
    [Show full text]
  • Dynamic Message-Oriented Middleware with Open Sound Control and Odot
    http://www.cnmat.berkeley.edu/publications/dynamic-message-oriented-middleware-open-sound-control-and-odot Dynamic Message-Oriented Middleware with Open Sound Control and Odot John MacCallum1, Rama Gottfried1, Ilya Rostovtsev1, Jean Bresson2, and Adrian Freed1 1Center for New Music and Audio Technologies, Department of Music, University of California, Berkeley, [email protected], [email protected], [email protected], [email protected] 2UMR STMS: IRCAM-CNRS-UPMC, Paris, [email protected] ABSTRACT coding, and the odot framework provides a set of tools for constructing such a layer in a dynamic and agile fashion. We present recent work on odot, a system that extends Open We begin with brief descriptions of Message-Oriented Mid- Sound Control and facilitates the rapid and dynamic con- dleware, OSC, and odot. We then discuss our ongoing work struction of Message-Oriented Middleware providing an in- to provide support for a variety of host and nested host envi- teroperability layer for communication between applications. ronments that can be made to communicate by passing OSC Unlike traditional middleware systems, odot, when embedded between them. Finally, we conclude by discussing a number in a host environment, provides a node where computation of examples and future work. can take place, allowing middleware to take shape dynami- cally as the needs of the system develop. 2. OPEN SOUND CONTROL AND ODOT 2.1 Open Sound Control (OSC) 1. INTRODUCTION Open Sound Control[1][2][3] is a popular encoding in the In the course of a complex design project we often encounter music and media/arts programming communities for moving the need to use multiple applications to satisfy a diverse set data between sensors and actuators, as well as processes and of requirements.
    [Show full text]
  • Programovacı Jazyky Pro Vy´Uku Programova´Nı Na
    MASARYKOVA UNIVERZITA }w¡¢£¤¥¦§¨ FAKULTA INFORMATIKY !"#$%&'()+,-./012345<yA| Programovacı´jazyky pro vy´uku programova´nı´na SSˇ DIPLOMOVA´ PRA´ CE Bc. Luka´sˇRy´dlo Brno, 2012 Prohla´sˇenı´ Prohlasˇuji, zˇe tato diplomova´pra´ce je my´m pu˚vodnı´m autorsky´m dı´lem, ktere´ jsem vypracoval samostatneˇ. Vsˇechny zdroje, prameny a literaturu, ktere´jsem prˇi vypracova´nı´pouzˇı´val nebo z nich cˇerpal, v pra´ci rˇa´dneˇcituji s uvedenı´m u´plne´ho odkazu na prˇı´slusˇny´zdroj. Vedoucı´pra´ce: doc. RNDr. Toma´sˇPitner, Ph.D. iii Podeˇkova´nı´ Ra´d bych podeˇkoval vedoucı´mu sve´pra´ce, doc. RNDr. Toma´sˇi Pitnerovi, Ph.D. za ochotu ve´st me´te´ma, nevsˇednı´vstrˇı´cnost a trpeˇlivost i konkre´tnı´tipy. v Abstrakt Pra´ce prˇina´sˇı´zhodnocenı´ru˚zny´ch programovacı´ch jazyku˚, metodik a prostrˇedı´ pro potrˇeby vy´uky na strˇednı´ch sˇkola´ch. V u´vodnı´kapitole jsou popsane´teoreticke´ koncepty, formy vy´uky, analy´za metodik v oblasti vy´uky programova´nı´, vhodnost jednotlivy´ch paradigmat. Druha´kapitola prˇina´sˇı´prˇehled za´kladnı´ch metod graficke´ho popisu algoritmu, jejich vhodnost a vyuzˇitelnost prˇi vy´uce. Trˇetı´kapitola zacˇı´na´na´vrhem metodiky hodnocenı´programovacı´ch jazyku˚pro potrˇeby vy´uky a jejich prˇehledem. Dalsˇı´ka- pitola hodnotı´pro zmeˇnu ru˚zna´vy´vojova´prostrˇedı´, at’uzˇpouzˇı´vana´v beˇzˇne´praxi nebo urcˇena´prˇı´mo pro vy´uku. Za´veˇr pra´ce je veˇnova´n vy´ukovy´m materia´lu˚m pro semina´rˇz programova´nı´na gymna´ziu v jazyce Java metodou objects first, resp.
    [Show full text]
  • SWIG-1.3 Documentation
    SWIG−1.3 Documentation SWIG−1.3 Documentation Table of Contents SWIG−1.3 Development Documentation..........................................................................................................................................1 Sections...................................................................................................................................................................................1 SWIG Core Documentation............................................................................................................................................1 Language Module Documentation..................................................................................................................................1 Developer Documentation...............................................................................................................................................1 Documentation that has not yet been updated.................................................................................................................2 1 Preface...............................................................................................................................................................................................3 1.1 Introduction.......................................................................................................................................................................3 1.2 Special Introduction for Version 1.3................................................................................................................................3
    [Show full text]
  • Checking Type Safety of Foreign Function Calls ∗
    Checking Type Safety of Foreign Function Calls ∗ Michael Furr Jeffrey S. Foster University of Maryland, College Park University of Maryland, College Park [email protected] [email protected] Abstract guages. Such interfaces are important for accessing system-wide We present a multi-lingual type inference system for checking type libraries and legacy components, but they are difficult to use cor- safety across a foreign function interface. The goal of our system is rectly, especially when there are mismatches between native and to prevent foreign function calls from introducing type and mem- foreign type systems, data representations, and run-time environ- ory safety violations into an otherwise safe language. Our system ments. In all of the FFIs we are aware of, there is little or no consis- targets OCaml’s FFI to C, which is relatively lightweight and illus- tency checking between foreign and native code [4, 8, 15, 16, 17]. trates some interesting challenges in multi-lingual type inference. As a consequence, adding an FFI to a safe language potentially The type language in our system embeds OCaml types in C types provides a rich source of operations that can violate safety in subtle and vice-versa, which allows us to track type information accu- and difficult-to-find ways. rately even through the foreign language, where the original types This paper presents a multi-lingual type inference system to are lost. Our system uses representational types that can model check type and garbage collection safety across foreign function multiple OCaml types, because C programs can observe that many calls.
    [Show full text]
  • The SHOGUN Machine Learning Toolbox
    Introduction Machine Learning The SHOGUN Machine Learning Toolbox The SHOGUN Machine Learning Toolbox (and its python interface) S¨orenSonnenburg1;2, Gunnar R¨atsch2,Sebastian Henschel2,Christian Widmer2,Jonas Behr2,Alexander Zien2,Fabio de Bona2,Alexander Binder1,Christian Gehl1, and Vojtech Franc3 1 Berlin Institute of Technology, Germany 2 Friedrich Miescher Laboratory, Max Planck Society, Germany 3 Center for Machine Perception, Czech Republic fml Introduction Machine Learning The SHOGUN Machine Learning Toolbox Outline 1 Introduction 2 Machine Learning 3 The SHOGUN Machine Learning Toolbox Introduction Machine Learning The SHOGUN Machine Learning Toolbox About me Who Am I? About Me 1997-2002 studied Computer Science 2002-2009 doing ML & Bioinformatics research at Fraunhofer Institute FIRST and Max Planck Society since 2002 2008 PhD: Machine Learning for Genomic Sequence Analysis 2009- Researcher at Berlin Institute of Technology Open Source Involvement Debian Developer http://www.debian.org Machine Learning OSS http://mloss.org Machine Learning Data http://mldata.org Main author of SHOGUN - this talk More about me http://sonnenburgs.de/soeren Introduction Machine Learning The SHOGUN Machine Learning Toolbox Machine Learning - Learning from Data What is Machine Learning and what can it do for you? What is ML? AIM: Learning from empirical data! Applications speech and handwriting recognition search engines, natural language processing medical diagnosis, bioinformatics, chemoinformatics detecting credit card fraud computer vision, object
    [Show full text]
  • Javascript Tools and Testing
    Tooling and Testing SWE 432, Fall 2019 Web Application Development Quiz Go to: b.socrative.com, Click student login Room name: SWE432 Student Name: Your G-number (Including the G) Reminder: Survey can only be completed if you are in class. If you are not in class and do it you will be referred directly to the honor code board, no questions asked, no warning. LaToza GMU SWE 432 Fall 2019 !2 Review: JSON: JavaScript Object Notation Open standard format for transmitting data objects. No functions, only key / value pairs Values may be other objects or arrays var profHacker = { var profHacker = { firstName: "Alyssa", firstName: "Alyssa", lastName: “P Hacker", lastName: “P Hacker", teaches: "SWE 432", teaches: "SWE 432", office: “ENGR 6409”, office: "ENGR 6409", fullName: function(){ fullName: { return this.firstName + " " + this.lastName; firstName: “Alyssa”, } lastName: “P Hacker”} }; }; Our Object JSON Object LaToza GMU SWE 432 Fall 2019 !3 Logistics • HW1 due next Monday before class LaToza GMU SWE 432 Fall 2019 !4 Today • Web Development Tools • What’s behavior driven development and why do we want it? • Some tools for testing web apps - focus on Jest LaToza GMU SWE 432 Fall 2019 !5 An (older) way to export modules • Prior to ES6, was no language support for exposing modules. • Instead did it with libraries (e.g., node) that handled exports • Works similarly: declare what functions / classes are publicly visible, import classes • Syntax: In the file exporting a function or class sum: module.exports = sum; In the file importing a function or class sum: const sum = require('./sum'); Where sum.js is the name of a file which defines sum.
    [Show full text]