Reactors: a Deterministic Model of Concurrent Computation for Reactive Systems
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The Implementation of Metagraph Agents Based on Functional Reactive Programming
______________________________________________________PROCEEDING OF THE 26TH CONFERENCE OF FRUCT ASSOCIATION The Implementation of Metagraph Agents Based on Functional Reactive Programming Valeriy Chernenkiy, Yuriy Gapanyuk, Anatoly Nardid, Nikita Todosiev Bauman Moscow State Technical University, Moscow, Russia [email protected], [email protected], [email protected], [email protected] Abstract—The main ideas of the metagraph data model and there is no doubt that it is the functional approach in the metagraph agent model are discussed. The metagraph programming that makes it possible to make such approach for semantic complex event processing is presented. implementation effectively. Therefore, the work is devoted to The metagraph agent implementation based on Functional the implementation of a multi-agent paradigm using functional Reactive Programming is proposed. reactive programming. The advantage of this implementation is that agents can work in parallel, supporting a functional I. INTRODUCTION reactive paradigm. Currently, models based on complex networks are The article is organized as follows. The section II discusses increasingly used in various fields of science, from the main ideas of the metagraph model. The section III mathematics and computer science to biology and sociology. discusses the metagraph agent model. The section IV discusses According to [1]: “a complex network is a graph (network) the Semantic Complex Event Processing approach and its’ with non-trivial topological features – features that do not occur correspondence to the metagraph model. The section V (which in simple networks such as lattices or random graphs but often is the novel result presented in the article) discusses the occur in graphs modeling of real systems.” The terms “complex metagraph agent implementation based on Functional Reactive network” and “complex graph” are often used synonymously. -
Functional Reactive Programming, Refactored
Functional Reactive Programming, Refactored Ivan Perez Manuel Barenz¨ Henrik Nilsson University of Nottingham University of Bamberg University of Nottingham [email protected] [email protected] [email protected] Abstract 18] and Reactive Values [21]. Through composition of standard Functional Reactive Programming (FRP) has come to mean many monads like reader, exception, and state, any desirable combination things. Yet, scratch the surface of the multitude of realisations, and of time domain, dynamic system structure,flexible handling of I/O there is great commonality between them. This paper investigates and more can be obtained in an open-ended manner. this commonality, turning it into a mathematically coherent and Specifically, the contributions of this paper are: practical FRP realisation that allows us to express the functionality We define a minimal Domain-Specific Language of causal • of many existing FRP systems and beyond by providing a minimal Monadic Stream Functions (MSFs), give them precise mean- FRP core parametrised on a monad. We give proofs for our theoreti- ing and analyse the properties they fulfill. cal claims and we have verified the practical side by benchmarking We explore the use of different monads in MSFs, how they nat- a set of existing, non-trivial Yampa applications running on top of • our new system with very good results. urally give rise to known reactive constructs, like termination, switching, higher-order, parallelism and sinks, and how to com- Categories and Subject Descriptors D.3.3 [Programming Lan- pose effects at a stream level using monad transformers [15]. guages]: Language Constructs and Features – Control Structures We implement three different FRP variants on top of our frame- • Keywords functional reactive programming, reactive program- work: 1) Arrowized FRP, 2) Classic FRP and 3) Signal/Sink- ming, stream programming, monadic streams, Haskell based reactivity. -
Flapjax: Functional Reactive Web Programming
Flapjax: Functional Reactive Web Programming Leo Meyerovich Department of Computer Science Brown University [email protected] 1 People whose names should be before mine. Thank you to Shriram Krishnamurthi and Gregory Cooper for ensuring this project’s success. I’m not sure what would have happened if not for the late nights with Michael Greenberg, Aleks Bromfield, and Arjun Guha. Peter Hopkins, Jay McCarthy, Josh Gan, An- drey Skylar, Jacob Baskin, Kimberly Burchett, Noel Welsh, and Lee Butterman provided invaluable input. While not directly involved with this particular project, Kathi Fisler and Michael Tschantz have pushed me along. 1 Contents 4.6. Objects and Collections . 32 4.6.1 Delta Propagation . 32 1. Introduction 3 4.6.2 Shallow vs Deep Binding . 33 1.1 Document Approach . 3 4.6.3 DOM Binding . 33 2. Background 4 4.6.4 Server Binding . 33 2.1. Web Programming . 4 4.6.5 Disconnected Nodes and 2.2. Functional Reactive Programming . 5 Garbage Collection . 33 2.2.1 Events . 6 2.2.2 Behaviours . 7 4.7. Evaluations . 34 2.2.3 Automatic Lifting: Transparent 4.7.1 Demos . 34 Reactivity . 8 4.7.2 Applications . 34 2.2.4 Records and Transparent Reac- 4.8 Errors . 34 tivity . 10 2.2.5 Behaviours and Events: Conver- 4.9 Library vs Language . 34 sions and Event-Based Derivation 10 4.9.1 Dynamic Typing . 34 4.9.2 Optimization . 35 3. Implementation 11 3.1. Topological Evaluation and Glitches . 13 4.9.3 Components . 35 3.1.1 Time Steps . 15 4.9.4 Compilation . -
Incorparating the Actor Model Into SCIVE on an Abstract Semantic Level
Incorparating the Actor Model into SCIVE on an Abstract Semantic Level Christian Frohlich¨ ∗ Marc E. Latoschik† AI and VR Group, Bielefeld University AI and VR Group, Bielefeld University. ABSTRACT Since visual perception is very important for generating immer- sive environments, most VR applications focus on the graphical This paper illustrates the temporal synchronization and process flow simulation output. Tools like OpenGL Performer, Open Inven- facilities of a real-time simulation system which is based on the ac- tor [12], Open Scene Graph, OpenSG [11] or the VRML successor tor model. The requirements of such systems are compared against X3D [8] are based upon a hierarchical scene graph structure, which the actor model’s basic features and structures. The paper describes allows for complex rendering tasks. Extension mechanisms like how a modular architecture benefits from the actor model on the field routing or rapid prototyping via scipting interfaces allow for module level and points out how the actor model enhances paral- new customized node types and interconnected application graphs. lelism and concurrency even down to the entity level. The actor idea is incorporated into a novel simulation core for intelligent vir- Purpose-built VR application frameworks adopt and extend these mechanisms, by adding in- and output customization, see e.g. tual environments (SCIVE). SCIVE supports well-known and es- TM tablished Virtual Reality paradigms like the scene graph metaphor, Lightning [4], Avango [13], VR Juggler [3] or the CAVELib . field routing concepts etc. In addition, SCIVE provides an explicit Also network distribution paradigms are often integrated to enable semantic representation of its internals as well as of the specific distributed rendering on a cluster architecture, as can be seen in virtual environments’ contents. -
Actor-Based Concurrency by Srinivas Panchapakesan
Concurrency in Java and Actor- based concurrency using Scala By, Srinivas Panchapakesan Concurrency Concurrent computing is a form of computing in which programs are designed as collections of interacting computational processes that may be executed in parallel. Concurrent programs can be executed sequentially on a single processor by interleaving the execution steps of each computational process, or executed in parallel by assigning each computational process to one of a set of processors that may be close or distributed across a network. The main challenges in designing concurrent programs are ensuring the correct sequencing of the interactions or communications between different computational processes, and coordinating access to resources that are shared among processes. Advantages of Concurrency Almost every computer nowadays has several CPU's or several cores within one CPU. The ability to leverage theses multi-cores can be the key for a successful high-volume application. Increased application throughput - parallel execution of a concurrent program allows the number of tasks completed in certain time period to increase. High responsiveness for input/output-intensive applications mostly wait for input or output operations to complete. Concurrent programming allows the time that would be spent waiting to be used for another task. More appropriate program structure - some problems and problem domains are well-suited to representation as concurrent tasks or processes. Process vs Threads Process: A process runs independently and isolated of other processes. It cannot directly access shared data in other processes. The resources of the process are allocated to it via the operating system, e.g. memory and CPU time. Threads: Threads are so called lightweight processes which have their own call stack but an access shared data. -
Liam: an Actor Based Programming Model for Hdls
Liam: An Actor Based Programming Model for HDLs Haven Skinner Rafael Trapani Possignolo Jose Renau Dept. of Computer Engineering Dept. of Computer Engineering Dept. of Computer Engineering [email protected] [email protected] [email protected] ABSTRACT frequency being locked down early in the development process, The traditional model for developing synthesizable digital architec- and adds a high cost in effort and man-hours, to make high-level tures is a clock-synchronous pipeline. Latency-insensitive systems changes to the system. Although these challenges can be managed, are an alternative, where communication between blocks is viewed they represent fundamental obstacles to developing large-scale as message passing. In hardware this is generally managed by con- systems. trol bits such as valid/stop signals or token credit mechanisms. An alternative is a latency-insensitive design, where the system Although prior work has shown that there are numerous benefits is abstractly seen as being comprised of nodes, which communicate to building latency-insensitive digital hardware, a major factor dis- via messages. Synchronous hardware systems can be automatically couraging its use is the difficulty of managing the additional logic transformed to latency-insensitive designs, which we refer to as and infrastructure required to implement it. elastic systems [1–3]. Alternately, the designer can manually con- We propose a new programming paradigm for Hardware Descrip- trol the latency-insensitive backend [4, 5], we call such systems tion Languages, built on the Actor Model, to implicitly implement Fluid Pipelines. The advantage of exposing the elasticity to the latency-insensitive hardware designs. We call this model Liam, for designer is an increase in performance and flexibility in transforma- Latency-Insensitive Actor-based programming Model. -
Computer Science 1
Computer Science 1 Computer Science Department Website: https://www.cs.uchicago.edu Program of Study The computer science program offers BA and BS degrees, as well as combined BA/MS and BS/MS degrees. Students who earn the BA are prepared either for graduate study in computer science or a career in industry. Students who earn the BS degree build strength in an additional field by following an approved course of study in a related area. The department also offers a minor. Where to Start The Department of Computer Science offers several different introductory pathways into the program. In consultation with their College adviser and the Computer Science Department advisers, students should choose their introductory courses carefully. Some guidelines follow. For students intending to pursue further study in computer science, we recommend CMSC 15100 Introduction to Computer Science I or CMSC 16100 Honors Introduction to Computer Science I as the first course. CMSC 15100 does not assume prior experience or unusually strong preparation in mathematics. Students with programming experience and strong preparation in mathematics should consider CMSC 16100 Honors Introduction to Computer Science I. First-year students considering a computer science major are strongly advised to register for an introductory sequence in the Winter or Spring Quarter of their first year, and it is all but essential that they start the introductory sequence no later than the second quarter of their second year. Students who are not intending to major in computer science, but are interested in getting a rigorous introduction to computational thinking with a focus on applications are encouraged to start with CMSC 12100 Computer Science with Applications I. -
Compiling Real Time Functional Reactive Programming
Compiling Real Time Functional Reactive Programming Dana N. Xu and Siau-Cheng Khoo Department of Computer Science School of Computing National University of Singapore {xun,khoosc}@comp.nus.edu.sg ABSTRACT 1. INTRODUCTION Most of the past languages for reactive systems are based Reactive systems are required to react in a timely man- on synchronous dataflow. Recently, a new reactive lan- ner to external events. Their use can be found in a broad guage, called Real-Time Functional Reactive Programming range of applications, ranging from high-end consumer prod- (RT-FRP) [18] , has been proposed based on the functional ucts (digital radio, intelligent cookers) to systems used in paradigm. The unique feature of this language is the high- mission-critical applications (such as air-craft and nuclear- level abstraction provided in the form of behaviors for conti- power stations). nuous-time signals, and events for discrete-time signals. RT- Programming these systems poses a great challenge, and FRP also features some performance guarantees in the form a number of programming languages have been proposed of bounded runtime and space usage for each reactive com- over the last two decades. Two main concerns are typically putation step. addressed in these languages. Firstly, some features must In this paper, we propose a new compilation scheme for be available to express signals and events, and how they are RT-FRP. Our compilation scheme is based on two key stages. transformed by the intended reactive systems. Secondly, we In the first stage, we translate RT-FRP program to an in- must be able to show that each reaction could be carried termediate functional code. -
Massachusetts Institute of Technology Artificial Intelligence Laboratory
MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY Working Paper 190 June 1979 A FAIR POWER DOMAIN FOR ACTOR COMPUTATIONS Will Clinger AI Laboratory Working Papers are produced for internal circulation, and may contain information that is, for example, too preliminary or too detailed for formal publication. Although some will be given a limited external distribution, it is not intended that they should be considered papers to which reference can be made in the literature. This report describes research conducted at the Artificial Intelligence Laboratory of the Massachusetts Institute of Technology. Support for this research was provided in part by the Office of Naval Research of the Department of Defense under Contract N00014-75-C-0522. O MASSAnuTsms INSTTUTE OF TECMGoOry FM DRAFT 1 June 1979 -1- A fair power domain A FAIR POWER DOMAIN FOR ACTOR COMPUTATIONS Will Clingerl 1. Abstract Actor-based languages feature extreme concurrency, allow side effects, and specify a form of fairness which permits unbounded nondeterminism. This makes it difficult to provide a satisfactory mathematical foundation for their semantics. Due to the high degree of parallelism, an oracle semantics would be intractable. A weakest precondition semantics is out of the question because of the possibility of unbounded nondeterminism. The most attractive approach, fixed point semantics using power domains, has not been helpful because the available power domain constructions, although very general, seemed to deal inadequately with fairness. By taking advantage of the relatively complex structure of the actor computation domain C, however, a power domain P(C) can be defined which is similar to Smyth's weak power domain but richer. -
Actor Model of Computation
Published in ArXiv http://arxiv.org/abs/1008.1459 Actor Model of Computation Carl Hewitt http://carlhewitt.info This paper is dedicated to Alonzo Church and Dana Scott. The Actor model is a mathematical theory that treats “Actors” as the universal primitives of concurrent digital computation. The model has been used both as a framework for a theoretical understanding of concurrency, and as the theoretical basis for several practical implementations of concurrent systems. Unlike previous models of computation, the Actor model was inspired by physical laws. It was also influenced by the programming languages Lisp, Simula 67 and Smalltalk-72, as well as ideas for Petri Nets, capability-based systems and packet switching. The advent of massive concurrency through client- cloud computing and many-core computer architectures has galvanized interest in the Actor model. An Actor is a computational entity that, in response to a message it receives, can concurrently: send a finite number of messages to other Actors; create a finite number of new Actors; designate the behavior to be used for the next message it receives. There is no assumed order to the above actions and they could be carried out concurrently. In addition two messages sent concurrently can arrive in either order. Decoupling the sender from communications sent was a fundamental advance of the Actor model enabling asynchronous communication and control structures as patterns of passing messages. November 7, 2010 Page 1 of 25 Contents Introduction ............................................................ 3 Fundamental concepts ............................................ 3 Illustrations ............................................................ 3 Modularity thru Direct communication and asynchrony ............................................................. 3 Indeterminacy and Quasi-commutativity ............... 4 Locality and Security ............................................ -
Computer Science (COM S) 1
Computer Science (COM S) 1 COM S 105B: Short Course in Computer Programming: MATLAB COMPUTER SCIENCE (COM S) (2-0) Cr. 2. Any experimental courses offered by COM S can be found at: Prereq: Com S 104 registrar.iastate.edu/faculty-staff/courses/explistings/ (http:// 8-week course in programming using MATLAB. www.registrar.iastate.edu/faculty-staff/courses/explistings/) COM S 106: Introduction to Web Programming Courses primarily for undergraduates: (3-0) Cr. 3. F.S. Introduction to web programming basics. Fundamentals of developing COM S 101: Orientation web pages using a comprehensive web development life cycle. Learn Cr. R. F.S. to design and code practical real-world homepage programs and earn Introduction to the computer science discipline and code of ethics, Com adequate experience with current web design techniques such as HTML5 S courses, research and networking opportunities, procedures, policies, and cascading style sheets. Students also learn additional programming help and computing resources, extra-curricular activities offered by the languages including JavaScript, jQuery, PHP, SQL, and MySQL. Strategies Department of Computer Science and Iowa State University. Discussion for accessibility, usability and search engine optimization. No prior of issues relevant to student adjustment to college life. Offered on a computer programming experience necessary. satisfactory-fail basis only. Offered on a satisfactory-fail basis only. COM S 107: Windows Application Programming COM S 103: Computer Literacy and Applications (3-0) Cr. 3. F.S. Cr. 4. F.S.SS. Introduction to computer programming for non-majors using a language Introduction to computer literacy and applications. Literacy: Impact of such as the Visual Basic language. -
A Model Based Realisation of Actor Model to Conceptualise an Aid for Complex Dynamic Decision-Making
A Model based Realisation of Actor Model to Conceptualise an Aid for Complex Dynamic Decision-making Souvik Barat1, Vinay Kulkarni1, Tony Clark2 and Balbir Barn3 1Tata Consultancy Services Research, Pune, India 2Sheffield Hallam University, Sheffield, U.K. 3Middlesex University, London, U.K. {souvik.barat, vinay.vkulkarni}@tcs.com, [email protected], [email protected] Keywords: Organisational Decision Making, Simulation, Actor Model of Computation, Actor based Simulation. Abstract: Effective decision-making of modern organisation requires deep understanding of various aspects of organisation such as its goals, structure, business-as-usual operational processes etc. The large size and complex structure of organisations, socio-technical characteristics, and fast business dynamics make this decision-making a challenging endeavour. The state-of-practice of decision-making that relies heavily on human experts is often reported as ineffective, imprecise and lacking in agility. This paper evaluates a set of candidate technologies and makes a case for using actor based simulation techniques as an aid for complex dynamic decision-making. The approach is justified by enumeration of basic requirements of complex dynamic decision-making and the conducting a suitability of analysis of state-of-the-art enterprise modelling techniques. The research contributes a conceptual meta-model that represents necessary aspects of organisation for complex dynamic decision-making together with a realisation in terms of a meta model that extends Actor model of computation. The proposed approach is illustrated using a real life case study from business process outsourcing industry. 1 INTRODUCTION reports from leading consulting organisations such as McKinsey and Harvard Business Review (Kahneman Modern organisations constantly attempt to meet et al., 2011, Meissner et al.