Design and Implementation of a Multi-Stage, Object-Oriented Programming Language
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Developer's Guide Sergey A
Complex Event Processing with Triceps CEP v1.0 Developer's Guide Sergey A. Babkin Complex Event Processing with Triceps CEP v1.0 : Developer's Guide Sergey A. Babkin Copyright © 2011, 2012 Sergey A. Babkin All rights reserved. This manual is a part of the Triceps project. It is covered by the same Triceps version of the LGPL v3 license as Triceps itself. The author can be contacted by e-mail at <[email protected]> or <[email protected]>. Many of the designations used by the manufacturers and sellers to distinguish their products are claimed as trademarks. Where those designations appear in this manual, and the author was aware of a trademark claim, the designations have been printed in caps or initial caps. While every precaution has been taken in the preparation of this manual, the author assumes no responsibility for errors or omissions, or for damages resulting from the use of the information contained herein. Table of Contents 1. The field of CEP .................................................................................................................................. 1 1.1. What is the CEP? ....................................................................................................................... 1 1.2. The uses of CEP ........................................................................................................................ 2 1.3. Surveying the CEP langscape ....................................................................................................... 2 1.4. We're not in 1950s any more, -
Program Analysis and Optimization for Embedded Systems
Program Analysis and Optimization for Embedded Systems Mike Jochen and Amie Souter jochen, souter ¡ @cis.udel.edu Computer and Information Sciences University of Delaware Newark, DE 19716 (302) 831-6339 1 Introduction ¢ have low cost A proliferation in use of embedded systems is giving cause ¢ have low power consumption for a rethinking of traditional methods and effects of pro- ¢ require as little physical space as possible gram optimization and how these methods and optimizations can be adapted for these highly specialized systems. This pa- ¢ meet rigid time constraints for computation completion per attempts to raise some of the issues unique to program These requirements place constraints on the underlying analysis and optimization for embedded system design and architecture’s design, which together affect compiler design to address some of the solutions that have been proposed to and program optimization techniques. Each of these crite- address these specialized issues. ria must be balanced against the other, as each will have an This paper is organized as follows: section 2 provides effect on the other (e.g. making a system smaller and faster pertinent background information on embedded systems, de- will typically increase its cost and power consumption). A lineating the special needs and problems inherent with em- typical embedded system, as illustrated in figure 1, consists bedded system design; section 3 addresses one such inherent of a processor core, a program ROM (Read Only Memory), problem, namely limited space for program code; section 4 RAM (Random Access Memory), and an ASIC (Applica- discusses current approaches and open issues for code min- tion Specific Integrated Circuit). -
More Efficient Serialization and RMI for Java
To appear in: Concurrency: Practice & Experience, Vol. 11, 1999. More Ecient Serialization and RMI for Java Michael Philippsen, Bernhard Haumacher, and Christian Nester Computer Science Department, University of Karlsruhe Am Fasanengarten 5, 76128 Karlsruhe, Germany [phlippjhaumajnester]@ira.u ka.de http://wwwipd.ira.uka.de/JavaPa rty/ Abstract. In current Java implementations, Remote Metho d Invo ca- tion RMI is to o slow, esp ecially for high p erformance computing. RMI is designed for wide-area and high-latency networks, it is based on a slow ob ject serialization, and it do es not supp ort high-p erformance commu- nication networks. The pap er demonstrates that a much faster drop-in RMI and an ecient drop-in serialization can b e designed and implemented completely in Java without any native co de. Moreover, the re-designed RMI supp orts non- TCP/IP communication networks, even with heterogeneous transp ort proto cols. We demonstrate that for high p erformance computing some of the ocial serialization's generality can and should b e traded for sp eed. Asaby-pro duct, a b enchmark collection for RMI is presented. On PCs connected through Ethernet, the b etter serialization and the improved RMI save a median of 45 maximum of 71 of the runtime for some set of arguments. On our Myrinet-based ParaStation network a cluster of DEC Alphas wesave a median of 85 maximum of 96, compared to standard RMI, standard serialization, and Fast Ethernet; a remote metho d invo cation runs as fast as 80 s round trip time, compared to ab out 1.5 ms. -
Stochastic Program Optimization by Eric Schkufza, Rahul Sharma, and Alex Aiken
research highlights DOI:10.1145/2863701 Stochastic Program Optimization By Eric Schkufza, Rahul Sharma, and Alex Aiken Abstract Although the technique sacrifices completeness it pro- The optimization of short sequences of loop-free, fixed-point duces dramatic increases in the quality of the resulting code. assembly code sequences is an important problem in high- Figure 1 shows two versions of the Montgomery multiplica- performance computing. However, the competing constraints tion kernel used by the OpenSSL RSA encryption library. of transformation correctness and performance improve- Beginning from code compiled by llvm −O0 (116 lines, not ment often force even special purpose compilers to pro- shown), our prototype stochastic optimizer STOKE produces duce sub-optimal code. We show that by encoding these code (right) that is 16 lines shorter and 1.6 times faster than constraints as terms in a cost function, and using a Markov the code produced by gcc −O3 (left), and even slightly faster Chain Monte Carlo sampler to rapidly explore the space of than the expert handwritten assembly included in the all possible code sequences, we are able to generate aggres- OpenSSL repository. sively optimized versions of a given target code sequence. Beginning from binaries compiled by llvm −O0, we are able 2. RELATED WORK to produce provably correct code sequences that either Although techniques that preserve completeness are effec- match or outperform the code produced by gcc −O3, icc tive within certain domains, their general applicability −O3, and in some cases expert handwritten assembly. remains limited. The shortcomings are best highlighted in the context of the code sequence shown in Figure 1. -
Course Outlines
COURSE NAME PYTHON PROGRAMMING OVERVIEW OBJECTIVES Python is a general-purpose, versatile, and popular How Python works and its place in the world of programming language. It is a great first language programming languages; to work with and because it is concise and easy to read, and it is also manipulate strings; to perform math operations; to a good language to have in any programmer’s stack work with Python sequences; to collect user input as it can be used for everything from web and output results; flow control processing; to write development to software development and scientific to, and read from, files; to write functions; to handle applications. exception; and work with dates and times. WHO SHOULD ATTEND PRE-REQUISITES Students new to the language. Some experience with other programming languages DELIVERY METHOD DURATION Instructor-led virtual course 5 days (40 hours) COURSE OUTLINE PYTHON INSTALLATION LOOPS Python Distributions (ActivePython, Anaconda, For(each) loop MiniConda) Absence of traditional for (i=0, i<n, i++) loop Additional Modules (Pip, conda, easy_install) Basic Examples with foreach loop PYTHON INTRODUCTION & BASICS Emulating Traditional for loops using range(n) The Python interpreter While Loops Working with command-line/IDE FUNCTIONS Python Data Types Def Keyword Built in operators, functions and methods Functions without args Data and type introspection basics: type (), dir() Functions with fixed num of args Syntax (Blocks and indentation) Functions with variable number of args and default Concepts (Scope, -
The Effect of Code Expanding Optimizations on Instruction Cache Design
May 1991 UILU-EN G-91-2227 CRHC-91-17 Center for Reliable and High-Performance Computing THE EFFECT OF CODE EXPANDING OPTIMIZATIONS ON INSTRUCTION CACHE DESIGN William Y. Chen Pohua P. Chang Thomas M. Conte Wen-mei W. Hwu Coordinated Science Laboratory College of Engineering UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN Approved for Public Release. Distribution Unlimited. UNCLASSIFIED____________ SECURITY ¿LASSIPlOvriON OF t h is PAGE REPORT DOCUMENTATION PAGE 1a. REPORT SECURITY CLASSIFICATION 1b. RESTRICTIVE MARKINGS Unclassified None 2a. SECURITY CLASSIFICATION AUTHORITY 3 DISTRIBUTION/AVAILABILITY OF REPORT 2b. DECLASSIFICATION/DOWNGRADING SCHEDULE Approved for public release; distribution unlimited 4. PERFORMING ORGANIZATION REPORT NUMBER(S) 5. MONITORING ORGANIZATION REPORT NUMBER(S) UILU-ENG-91-2227 CRHC-91-17 6a. NAME OF PERFORMING ORGANIZATION 6b. OFFICE SYMBOL 7a. NAME OF MONITORING ORGANIZATION Coordinated Science Lab (If applicable) NCR, NSF, AMD, NASA University of Illinois N/A 6c ADDRESS (G'ty, Staff, and ZIP Code) 7b. ADDRESS (Oty, Staff, and ZIP Code) 1101 W. Springfield Avenue Dayton, OH 45420 Urbana, IL 61801 Washington DC 20550 Langley VA 20200 8a. NAME OF FUNDING/SPONSORING 8b. OFFICE SYMBOL ORGANIZATION 9. PROCUREMENT INSTRUMENT IDENTIFICATION NUMBER 7a (If applicable) N00014-91-J-1283 NASA NAG 1-613 8c. ADDRESS (City, State, and ZIP Cod*) 10. SOURCE OF FUNDING NUMBERS PROGRAM PROJECT t a sk WORK UNIT 7b ELEMENT NO. NO. NO. ACCESSION NO. The Effect of Code Expanding Optimizations on Instruction Cache Design 12. PERSONAL AUTHOR(S) Chen, William, Pohua Chang, Thomas Conte and Wen-Mei Hwu 13a. TYPE OF REPORT 13b. TIME COVERED 14. OATE OF REPORT (Year, Month, Day) Jl5. -
Reflecting on an Existing Programming Language
Vol. 6, No. 9, Special Issue: TOOLS EUROPE 2007, October 2007 Reflecting on an Existing Programming Language Andreas Leitner, Dept. of Computer Science, ETH Zurich, Switzerland Patrick Eugster, Dept. of Computer Science, Purdue University, USA Manuel Oriol, Dept. of Computer Science, ETH Zurich, Switzerland Ilinca Ciupa, Dept. of Computer Science, ETH Zurich, Switzerland Reflection has proven to be a valuable asset for programming languages, es- pecially object-oriented ones, by promoting adaptability and extensibility of pro- grams. With more and more applications exceeding the boundary of a single address space, reflection comes in very handy for instance for performing con- formance tests dynamically. The precise incentives and thus mechanisms for reflection vary strongly between its incarnations, depending on the semantics of the considered programming lan- guage, the architecture of its runtime environment, safety and security concerns, etc. Another strongly influential factor is legacy, i.e., the point in time at which the corresponding reflection mechanisms are added to the language. This parameter tends to dictate the feasible breadth of the features offered by an implementation of reflection. This paper describes a pragmatic approach to reflection, consisting in adding introspection to an existing object-oriented programming language a posteriori, i.e., without extending the programming language, compiler, or runtime environ- ment in any specific manner. The approach consists in a pre-compiler generating specific code for types which are to be made introspectable, and an API through which this code is accessed. We present two variants of our approach, namely a homogeneous approach (for type systems with a universal root type) and a heterogeneous approach (without universal root type), and the corresponding generators. -
An Organized Repository of Ethereum Smart Contracts' Source Codes and Metrics
Article An Organized Repository of Ethereum Smart Contracts’ Source Codes and Metrics Giuseppe Antonio Pierro 1,* , Roberto Tonelli 2,* and Michele Marchesi 2 1 Inria Lille-Nord Europe Centre, 59650 Villeneuve d’Ascq, France 2 Department of Mathematics and Computer Science, University of Cagliari, 09124 Cagliari, Italy; [email protected] * Correspondence: [email protected] (G.A.P.); [email protected] (R.T.) Received: 31 October 2020; Accepted: 11 November 2020; Published: 15 November 2020 Abstract: Many empirical software engineering studies show that there is a need for repositories where source codes are acquired, filtered and classified. During the last few years, Ethereum block explorer services have emerged as a popular project to explore and search for Ethereum blockchain data such as transactions, addresses, tokens, smart contracts’ source codes, prices and other activities taking place on the Ethereum blockchain. Despite the availability of this kind of service, retrieving specific information useful to empirical software engineering studies, such as the study of smart contracts’ software metrics, might require many subtasks, such as searching for specific transactions in a block, parsing files in HTML format, and filtering the smart contracts to remove duplicated code or unused smart contracts. In this paper, we afford this problem by creating Smart Corpus, a corpus of smart contracts in an organized, reasoned and up-to-date repository where Solidity source code and other metadata about Ethereum smart contracts can easily and systematically be retrieved. We present Smart Corpus’s design and its initial implementation, and we show how the data set of smart contracts’ source codes in a variety of programming languages can be queried and processed to get useful information on smart contracts and their software metrics. -
Flexible Composition for C++11
Maximilien de Bayser Flexible Composition for C++11 Disserta¸c~aode Mestrado Dissertation presented to the Programa de P´os-Gradua¸c~ao em Inform´atica of the Departamento de Inform´atica, PUC-Rio as partial fulfillment of the requirements for the degree of Mestre em Inform´atica. Advisor: Prof. Renato Fontoura de Gusm~ao Cerqueira Rio de Janeiro April 2013 Maximilien de Bayser Flexible Composition for C++11 Dissertation presented to the Programa de P´os-Gradua¸c~ao em Inform´atica of the Departamento de Inform´atica, PUC-Rio as partial fulfillment of the requirements for the degree of Mestre em Inform´atica. Approved by the following commission: Prof. Renato Fontoura de Gusm~aoCerqueira Advisor Pontif´ıcia Universidade Cat´olica do Rio de Janeiro Prof. Alessandro Garcia Department of Informatics { PUC-Rio Prof. Waldemar Celes Department of Informatics { PUC-Rio Prof. Jos´eEugenio Leal Coordinator of the Centro T´ecnico Cient´ıfico Pontif´ıcia Universidade Cat´olica do Rio de Janeiro Rio de Janeiro | April 4th, 2013 All rights reserved. It is forbidden partial or complete reproduction without previous authorization of the university, the author and the advisor. Maximilien de Bayser Maximilien de Bayser graduated from PUC-Rio in Computer Engineering. He is also working at the Research Center for Inspection Technology where he works on software for non- destructive testing of oil pipelines and flexible risers for PE- TROBRAS. Bibliographic data de Bayser, Maximilien Flexible Composition for C++11 / Maximilien de Bayser; advisor: Renato Fontoura de Gusm~ao Cerqueira . | 2013. 107 f. : il. ; 30 cm 1. Disserta¸c~ao(Mestrado em Inform´atica) - Pontif´ıcia Universidade Cat´olica do Rio de Janeiro, Rio de Janeiro, 2013. -
ARM Optimizing C/C++ Compiler V20.2.0.LTS User's Guide (Rev. V)
ARM Optimizing C/C++ Compiler v20.2.0.LTS User's Guide Literature Number: SPNU151V January 1998–Revised February 2020 Contents Preface ........................................................................................................................................ 9 1 Introduction to the Software Development Tools.................................................................... 12 1.1 Software Development Tools Overview ................................................................................. 13 1.2 Compiler Interface.......................................................................................................... 15 1.3 ANSI/ISO Standard ........................................................................................................ 15 1.4 Output Files ................................................................................................................. 15 1.5 Utilities ....................................................................................................................... 16 2 Using the C/C++ Compiler ................................................................................................... 17 2.1 About the Compiler......................................................................................................... 18 2.2 Invoking the C/C++ Compiler ............................................................................................. 18 2.3 Changing the Compiler's Behavior with Options ...................................................................... -
Objective-C Fundamentals
Christopher K. Fairbairn Johannes Fahrenkrug Collin Ruffenach MANNING Objective-C Fundamentals Download from Wow! eBook <www.wowebook.com> Download from Wow! eBook <www.wowebook.com> Objective-C Fundamentals CHRISTOPHER K. FAIRBAIRN JOHANNES FAHRENKRUG COLLIN RUFFENACH MANNING SHELTER ISLAND Download from Wow! eBook <www.wowebook.com> For online information and ordering of this and other Manning books, please visit www.manning.com. The publisher offers discounts on this book when ordered in quantity. For more information, please contact Special Sales Department Manning Publications Co. 20 Baldwin Road PO Box 261 Shelter Island, NY 11964 Email: [email protected] ©2012 by Manning Publications Co. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by means electronic, mechanical, photocopying, or otherwise, without prior written permission of the publisher. Many of the designations used by manufacturers and sellers to distinguish their products are claimed as trademarks. Where those designations appear in the book, and Manning Publications was aware of a trademark claim, the designations have been printed in initial caps or all caps. Recognizing the importance of preserving what has been written, it is Manning’s policy to have the books we publish printed on acid-free paper, and we exert our best efforts to that end. Recognizing also our responsibility to conserve the resources of our planet, Manning books are printed on paper that is at least 15 percent recycled -
Compiler Optimization-Space Exploration
Journal of Instruction-Level Parallelism 7 (2005) 1-25 Submitted 10/04; published 2/05 Compiler Optimization-Space Exploration Spyridon Triantafyllis [email protected] Department of Computer Science Princeton University Princeton, NJ 08540 USA Manish Vachharajani [email protected] Department of Electrical and Computer Engineering University of Colorado at Boulder Boulder, CO 80309 USA David I. August [email protected] Department of Computer Science Princeton University Princeton, NJ 08540 USA Abstract To meet the performance demands of modern architectures, compilers incorporate an ever- increasing number of aggressive code transformations. Since most of these transformations are not universally beneficial, compilers traditionally control their application through predictive heuris- tics, which attempt to judge an optimization’s effect on final code quality a priori. However, com- plex target architectures and unpredictable optimization interactions severely limit the accuracy of these judgments, leading to performance degradation because of poor optimization decisions. This performance loss can be avoided through the iterative compilation approach, which ad- vocates exploring many optimization options and selecting the best one a posteriori. However, existing iterative compilation systems suffer from excessive compile times and narrow application domains. By overcoming these limitations, Optimization-Space Exploration (OSE) becomes the first iterative compilation technique suitable for general-purpose production compilers. OSE nar- rows down the space of optimization options explored through limited use of heuristics. A compiler tuning phase further limits the exploration space. At compile time, OSE prunes the remaining opti- mization configurations in the search space by exploiting feedback from earlier configurations tried. Finally, rather than measuring actual runtimes, OSE compares optimization outcomes through static performance estimation, further enhancing compilation speed.