Application-Specific Foreign-Interface Generation
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Jeannie: Granting Java Native Interface Developers Their Wishes
Jeannie: Granting Java Native Interface Developers Their Wishes Martin Hirzel Robert Grimm IBM Watson Research Center New York University [email protected] [email protected] Abstract higher-level languages and vice versa. For example, a Java Higher-level languages interface with lower-level languages project can reuse a high-performance C library for binary such as C to access platform functionality, reuse legacy li- decision diagrams (BDDs) through the Java Native Inter- braries, or improve performance. This raises the issue of face [38] (JNI), which is the standard FFI for Java. how to best integrate different languages while also recon- FFI designs aim for productivity, safety, portability, and ciling productivity, safety, portability, and efficiency. This efficiency. Unfortunately, these goals are often at odds. For paper presents Jeannie, a new language design for integrat- instance, Sun’s original FFI for Java, the Native Method In- ing Java with C. In Jeannie, both Java and C code are nested terface [52, 53] (NMI), directly exposed Java objects as C within each other in the same file and compile down to JNI, structs and thus provided simple and fast access to object the Java platform’s standard foreign function interface. By fields. However, this is unsafe, since C code can violate Java combining the two languages’ syntax and semantics, Jean- types, notably by storing an object of incompatible type in a nie eliminates verbose boiler-plate code, enables static error field. Furthermore, it constrains garbage collectors and just- detection across the language boundary, and simplifies dy- in-time compilers, since changes to the data representation namic resource management. -
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, .. -
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). -
T U M a Digital Wallet Implementation for Anonymous Cash
Technische Universität München Department of Informatics Bachelor’s Thesis in Information Systems A Digital Wallet Implementation for Anonymous Cash Oliver R. Broome Technische Universität München Department of Informatics Bachelor’s Thesis in Information Systems A Digital Wallet Implementation for Anonymous Cash Implementierung eines digitalen Wallets for anonyme Währungen Author Oliver R. Broome Supervisor Prof. Dr.-Ing. Georg Carle Advisor Sree Harsha Totakura, M. Sc. Date October 15, 2015 Informatik VIII Chair for Network Architectures and Services I conrm that this thesis is my own work and I have documented all sources and material used. Garching b. München, October 15, 2015 Signature Abstract GNU Taler is a novel approach to digital payments with which payments are performed with cryptographically generated representations of actual currencies. The main goal of GNU Taler is to allow taxable anonymous payments to non-anonymous merchants. This thesis documents the implementation of the Android version of the GNU Taler wallet, which allows users to create new Taler-based funds and perform payments with them. Zusammenfassung GNU Taler ist ein neuartiger Ansatz für digitales Bezahlen, bei dem Zahlungen mit kryptographischen Repräsentationen von echten Währungen getätigt werden. Das Hauptziel von GNU Taler ist es, versteuerbare, anonyme Zahlungen an nicht-anonyme Händler zu ermöglichen. Diese Arbeit dokumentiert die Implementation der Android-Version des Taler-Portemonnaies, der es Benutzern erlaubt, neues Taler-Guthaben zu erzeugen und mit ihnen Zahlungen zu tätigen. I Contents 1 Introduction 1 1.1 GNU Taler . .2 1.2 Goals of the thesis . .2 1.3 Outline . .3 2 Implementation prerequisites 5 2.1 Native libraries . .5 2.1.1 Libgcrypt . -
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. -
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 ............................... -
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) . -
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, . -
Nacldroid: Native Code Isolation for Android Applications
NaClDroid: Native Code Isolation for Android Applications Elias Athanasopoulos1, Vasileios P. Kemerlis2, Georgios Portokalidis3, and Angelos D. Keromytis4 1 Vrije Universiteit Amsterdam, The Netherlands [email protected] 2 Brown University, Providence, RI, USA [email protected] 3 Stevens Institute of Technology, Hoboken, NJ, USA [email protected] 4 Columbia University, New York, NY, USA [email protected] Abstract. Android apps frequently incorporate third-party libraries that contain native code; this not only facilitates rapid application develop- ment and distribution, but also provides new ways to generate revenue. As a matter of fact, one in two apps in Google Play are linked with a library providing ad network services. However, linking applications with third-party code can have severe security implications: malicious libraries written in native code can exfiltrate sensitive information from a running app, or completely modify the execution runtime, since all native code is mapped inside the same address space with the execution environment, namely the Dalvik/ART VM. We propose NaClDroid, a framework that addresses these problems, while still allowing apps to include third-party code. NaClDroid prevents malicious native-code libraries from hijacking Android applications using Software Fault Isolation. More specifically, we place all native code in a Native Client sandbox that prevents uncon- strained reads, or writes, inside the process address space. NaClDroid has little overhead; for native code running inside the NaCl sandbox the slowdown is less than 10% on average. Keywords: SFI, NaCl, Android 1 Introduction Android is undoubtedly the most rapidly growing platform for mobile devices, with estimates predicting one billion Android-based smartphones shipping in 2017 [12]. -
Developing and Benchmarking Native Linux Applications on Android
Developing and Benchmarking Native Linux Applications on Android Leonid Batyuk, Aubrey-Derrick Schmidt, Hans-Gunther Schmidt, Ahmet Camtepe, and Sahin Albayrak Technische Universit¨at Berlin, 10587 Berlin, Germany {aubrey.schmidt,leonid.batyuk,hans-gunther.schmidt,ahmet.camtepe, sahin.albayrak}@dai-labor.de http://www.dai-labor.de Abstract. Smartphones get increasingly popular where more and more smartphone platforms emerge. Special attention was gained by the open source platform Android which was presented by the Open Handset Al- liance (OHA) hosting members like Google, Motorola, and HTC. An- droid uses a Linux kernel and a stripped-down userland with a custom Java VM set on top. The resulting system joins the advantages of both environments, while third-parties are intended to develop only Java ap- plications at the moment. In this work, we present the benefit of using native applications in Android. Android includes a fully functional Linux, and using it for heavy computational tasks when developing applications can bring in substantional performance increase. We present how to develop native applications and software components, as well as how to let Linux appli- cations and components communicate with Java programs. Additionally, we present performance measurements of native and Java applications executing identical tasks. The results show that native C applications can be up to 30 times as fast as an identical algorithm running in Dalvik VM. Java applications can become a speed-up of up to 10 times if utilizing JNI. Keywords: software, performance, smartphones, android, C, Java. 1 Introduction With the growing customer interest in smartphones the number of available platforms increases steadily. -
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. -
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.