Functional Data Flow Research Articles

Transformation of Functional Dataflow Parallel Programs into Imperative Programs

Transformation of Functional Dataflow Parallel Programs into Imperative Programs

An Interactive Interpreter for Two Dimensional Lucid

We present an initial draft of the “Luminous" interactive interpreter for a new dialect of the functional dataflow language Lucid. Luminous is not the first implementation of Lucid but it is novel in several ways. First, the dialect is two dimensional (has a space as well as a time dimension) with special space operators. And it performs dimensional analysis to determine, for each program variable, which dimensions may be required to evaluate a variable and which are irrelevant. This information is vital for producing output and for avoiding expensive redundancy in the cache. Also, Luminous is interactive: the user can demand the value of an arbitrary expression and immediately see the results in an appropriate form, depending on the dimensionality of the expression. The user can also alter existing definitions and re-demand the value of expressions, to see the effect of the change. Unlike previous Lucid implementation, Luminous operates directly on the source - it doesn’t build a parse tree. The source is ‘dismantled’ into elementary equations in a bottom-up procedure based on program transformation which skips building a parse tree. Dismantling is a non deterministic distributable dataflow procedure. This could become very important when (in the future) we deal with programs millions of lines long, when parsing is a major problem. The final result of dismantling is an (unordered) set of ‘atomic’ equations – so called because they cannot be simplified, each consisting of a simple variable equated to an expression consisting of a single operator applied to arguments, which are also simple variables (or literals). Converting a program to a set of atomic equations (another first for Luminous) vastly simplifies evaluation and static analysis. We discuss shortcomings of the current interpreter, the most glaring of which is the lack of user defined stream transformations.

The System for Transforming the Code of Dataflow Programs into Imperative

Functional dataflow programming languages are designed to create parallel portable programs. The source code of such programs is translated into a set of graphs that reflect information and control dependencies. The main way of their execution is interpretation, which does not allow to perform calculations efficiently on real parallel computing systems and leads to poor performance. To run programs directly on existing computing systems, you need to use specific optimization and transformation methods that take into account the features of both the programming language and the architecture of the system. Currently, the most common is the Von Neumann architecture, however, parallel programming for it in most cases is carried out using imperative languages with a static type system. For different architectures of parallel computing systems, there are various approaches to writing parallel programs. The transformation of dataflow parallel programs into imperative programs allows to form a framework of imperative code fragments that directly display sequential calculations. In the future, this framework can be adapted to a specific parallel architecture. The paper considers an approach to performing this type of transformation, which consists in allocating fragments of dataflow parallel programs as templates, which are subsequently replaced by equivalent fragments of imperative languages. The proposed transformation methods allow generating program code, to which various optimizing transformations can be applied in the future, including parallelization taking into account the target architecture.

Integrated Design of Graduate Education Information System of Universities in Digital Campus Environment

This study takes the digital campus construction planning of the high school as an example and determines the requirements of the postgraduate management information system under the digital campus environment through the analysis of the overall framework and technology of the digital campus. Combining the current situation of computer technology, network technology, and the actual situation of our university, the current mainstream B/S three‐layer architecture is adopted, the web adopts the current popular Java Server Pages technology, and the struts framework connects to the Oracle backend database through the Java Database Connectivity interface to design the browser‐side and server‐side programs. The struts framework connects to the Oracle backend database through the Java Database Connectivity interface to design browser‐side and server‐side programs. The functional model and data flow model of the system were established through a detailed and effective analysis of the entire workflow of postgraduate students’ training management during their school years. Then, the system analysis, design, and drawing of the swim lane diagram and data business flow diagram were carried out. The system was designed in detail in terms of system architecture, development tools, functional modules, and database design, and the core module of training program making in postgraduate training management was highlighted as an example to discuss the principles and methods in the construction of departmental business systems and informatization under the digital campus environment, and a flexible and efficient postgraduate management information system was realized. It standardizes the construction of data standardization in universities; does a good job of standardizing and normalizing information; improves the accuracy, validity, and real‐time production of data collection and the real and safe unified management of historical data; and provides scientific and reasonable data support for the leadership to make relevant decisions.

Оптимизация графов потока управления в промежуточных представлениях языка функционально-потокового параллельного программирования

Functional dataflow programming languages are intended for the development of architecture-independent parallel programs and support the control of computations based on data availability. Due to the fact that at present parallel computing systems are very widespread, and their programming in imperative languages is associated with portability problems, the development of architecturally independent parallel programming tools is an urgent task. When such a program is translated, intermediate representations are formed as the information graph and the corresponding control graph. During program execution, data readiness signals are transmitted along the arcs of the control graph. An explicit selection of the control graph allows us not only to change the computational control strategies and ensure the adaptation of the program to the architecture features, but also to apply specific methods for optimizing control dependencies. The paper proposes transformation methods that provide optimization of the control graph. When generating a control graph from an informational one, redundant arcs are introduced into it, the removal of which does not affect the result of the program, but leads to its more efficient execution. It is shown that in dataflow programs, in addition to control dependencies inherent in other programming languages, additional ones associated with the implementation features of deferred or conditional computations described by delayed lists arise. A formal description of redundant dependencies of various types is given, as well as an effective algorithm for their identification. The developed approach can be applied to such dataflow programming languages as PIFAGOR and Smile.

Research on the application of block chain big data platform in the construction of new smart city for low carbon emission and green environment

The sharing of government information resources is significant for improving the level of governance and social information. However, due to the existence of cross-domain security and trust islands, government departments are hindering the sharing of government information resources with other organizations and the public. To this end, the blockchain technology is used to construct a decentralized distributed peer-to-peer trust service system, which is integrated with the existing PKI/CA security system to establish a new trust model that supports multi-CA coexistence. Based on this, the structural composition and functional data flow of the blockchain smart city information resource sharing and exchange model designed in this paper. This paper launched a study on the role of the smart big data platform, and selected the development of smart cities in Hefei as an empirical analysis. From the connotation of smart city, block chain and big data technology combined, and the positive effects of relevant information technology summarized on the construction of smart city big data platform. Based on this, the smart city development level evaluation model of TOPSIS method constructed. The evaluation model constructed to make a vertical comparison from 2012 to 2017, the scale of smart cities is growing at an average annual rate of more than 30%, saving 20% of urban resource allocation and becoming a new pillar industry. Therefore, Hefei City should further increase environmental supervision and promote the use of low-carbon environmental protection new energy. The improvement of government management level has a positive effect on the construction of smart Hefei.

An Interactive Visualization System for Near-Earth Space Exploration Data

Aiming at the actual needs of efficient and convenient visual analysis of near-Earth space exploration data, this paper studies the functional realization mode, data flow and interactive method, analyzes the functional framework and data flow of the interactive visualization system of near-Earth space exploration data in detail, designs a multi-level, loosely coupled and easily extensible system architecture, and focuses on solving the logic model design, the fusion rendering of the multivariable data, the shadow calculation, the data clustering analysis, and other key technologies. The application of the system has realized the interactive and visual analysis of the massive and multi-source near-Earth space exploration data, and provided convenient data analysis service for the vast number of scientific research and application users, which helps to better play the potential value of near-Earth space exploration data.

Loop-invariant Optimization in the Pifagor Language

The paper considers methods of program transformation equivalent to optimizing the cycle invariant, applied to the functional data-flow model implemented in the Pifagor programming language. Optimization of the cycle invariant in imperative programming languages is reduced to a displacement from the cycle of computations that do not depend on variables that are changes in the loop. A feature of the functional data flow parallel programming language Pifagor is the absence of explicitly specified cyclic computations (the loop operator). However, recurring calculations in this language can be specified recursively or by applying specific language constructs (parallel lists). Both mechanisms provide the possibility of parallel execution. In the case of optimizing a recursive function, repeated calculations are carried out into an auxiliary function, the main function performing only the calculation of the invariant. When optimizing the invariant in computations over parallel lists, the calculation of the invariant moves from the function that executes over the list items to the function containing the call. The paper provides a definition of “invariant” applied to the Pifagor language, algorithms for its optimization, and examples of program source codes, their graph representations (the program dependence graph) before and after optimization. The algorithm shown for computations over parallel lists is applicable only to the Pifagor language, because it rests upon specific data structures and the computational model of this language. However, the algorithm for transforming recursive functions may be applied to other programming languages.

Loop-invariant Optimization in the Pifagor Language

The paper considers methods of program transformation equivalent to optimizing the cycle invariant, applied to the functional data-flow model implemented in the Pifagor programming language. Optimization of the cycle invariant in imperative programming languages is reduced to a displacement from the cycle of computations that do not depend on variables that are changes in the loop. A feature of the functional data flow parallel programming language Pifagor is the absence of explicitly specified cyclic computations (the loop operator). However, recurring calculations in this language can be specified recursively or by applying specific language constructs (parallel lists). Both mechanisms provide the possibility of parallel execution. In the case of optimizing a recursive function, repeated calculations are carried out into an auxiliary function, the main function performing only the calculation of the invariant. When optimizing the invariant in computations over parallel lists, the calculation of the invariant moves from the function that executes over the list items to the function containing the call. The paper provides a definition of ”invariant” applied to the Pifagor language, algorithms for its optimization, and examples of program source codes, their graph representations (the program dependence graph) before and after optimization. The algorithm shown for computations over parallel lists is applicable only to the Pifagor language, because it rests upon specific data structures and the computational model of this language. However, the algorithm for transforming recursive functions may be applied to other programming languages.

Formal Verification of Programs in Functional Dataflow Parallel Language

The article is devoted to the methods of proving parallel programs correctness that are based on the axiomatic approach. Formal system for functional data-flow parallel programming language Pifagor is described. On the basis of this system programs correctness could be proved.

Tail Recursion Transformation in Functional Dataflow Parallel Programs

The peculiarities of transforming functional dataflow parallel programs into programs with finite resources are analysed. It is considered how these transformations are affected by the usage of asynchronous lists, the return of delayed lists and the variation of the data arrival pace relative to the time of its processing. These transformations allow us to generate multiple programs with static parallelism based on one and the some functional dataflow parallel program.

Carrying on the legacy of imperative languages in the future parallel computing era

Abstract There has been a renewed interest in dataflow computing models in recent years of technology scaling. Potentiality of exploiting huge parallelism, with the expense of low power, simpler circuit, less silicon area, is the main characteristic of a dataflow model. Growing trends in housing large number of functional units in a single chip, making use of local clocks, reducing energy consumptions, avoiding global wires are the main reasons behind the resurgence of dataflow models. To program a dataflow machine, new architectures suggest imperative languages rather than functional type dataflow languages or parallel languages because this is the right way to make the new architectures popular among the general community. Although for several decades scientists have been working on how imperative languages can be used in dataflow models efficiently, there is no systematic review on those works. Existing reviews on dataflow paradigm mainly focus on the architectures. Although few papers review programming languages of dataflow architectures, their discussions are limited to only dataflow languages and visual programming languages which are fundamentally different from imperative languages. In this paper, we conduct a systematic review on those works that attempt to provide a way to use imperative languages in any type of dataflow architectures. Our survey of compilers and related architectures cover the aspects like translation mechanisms of program construct, their optimization techniques, memory ordering methods, program allocation and scheduling and special architectural features. We also present some of our observations and future research directions obtained by exploring the literature.

Tail recursion transformation in functional dataflow parallel programs

The peculiarities of transforming functional dataflow parallel programs into programs with finite resources are analysed. It is considered how these transformations are affected by the usage of asynchronous lists, the return of delayed lists and the variation of the data arrival pace relative to the time of its processing. These transformations allow us to generate multiple programs with static parallelism based on one and the same functional dataflow parallel program.

FAULT ANALYSIS ACROSS THE LIFE CYCLE OF INTERNET ROUTERS

This paper presents applications where models developed to support a particular task (end-of-line testing) are exploited to support other work processes during the product life cycle. The application domain is internet routers. The testing solution is based on a functional (data flow) model and a structural (Bayes) model. These models are used to interpret results of router testing for fault detection and diagnosis. Multiple faults and intermittent faults can be diagnosed. The paper shows that the models can also support manufacturing planning, especially test planning and the selection and placement of sensors for testing and diagnosis. Application of the models to fault detection and isolation during router operation is also discussed.

A Reference model for enterprise-control system Integration - overview on a standardisation initiative

This paper aims at presenting an overview of an on-going international standardisation initiative carried out by the joint working group JWG15 of IEC and ISO. It is concerned with the development of a multipart standard named IEC 62264:Enterprise-Control system integration. After a brief introduction on the background, goal and the approach, some hierarchy models are reviewed, which are used as a basis to define the scope of the standard. Then functional data flow model, object models and associated data attributes are outlined. The activity models of manufacturing operations management are discussed. Future works and conclusions are given at the end of the paper.

Design and implementation of a CIM information system

Information integration is vital for keeping manufacturing operations competitive. A case study approach has been adopted to better understand the role of informatio in integrated manufacturing. Information is now considered a corporate asset. The creation, processing, movement and security of information is therefore as important as the products/services of an enterprise. The case studies have helped in identifying the requirements and issues involved in developing an information system and supporting software framework for a manufacturing enterprise. This paper deseribes a case study dealing with the integrated manufacture of optical fiber products. A phased development and implementation approach was adopted where a small, manageable slice of the system is considered for the case study followed by functional modeling (IDEFO) and data flow modeling (data flow diagrams). This identifies the pieces of information of interest. The information relationships are modeled using extended entity relationship (EER) diagrams which are then mapped to a relational model. The relational tables thus obtained were implemented on a commercial Database Management System (DBMS). The functional constraints and application interfaces were then built using Structured Query Languages (SQL) and commercial application interface tools. Subsequent sections describe the functional models, data flow diagrams (DFDs), EER diagrams, relational database design and user/application interfaces developed for the system. Implementation experiences and observations are discussed along with the applications of the implemented system. The case study has helped in developing a preliminary data model (i.e., a model about data by which a reasonable interpretation of the data can be obtained) for material handling (MH) functions.

An eductive interpreter for the language Lucid

We describe an interpreter for pLucid, a member of the Lucid family of functional dataflow languages. In appearance, pLucid is similar to Landin's Iswim, exept that individual variables and expressions denote streams (infinite sequences of data items), and function variables denote filters (stream-to-stream transformations). The actual data objects in pLucid (the components of streams) are those of POP2: numbers, strings, words, and lists. The 'inner syntax' (infix operations, conventions for denoting constants) are those of POP2 as well.The interpreter (which was written in C) is eductive: it uses a tagged demand-driven scheme. Demands for values in the output stream generate demands for values of other variables internal to the program. These demands, and the values returned in response, are tagged according to "time" (sequence index) and place (node in the tree of function calls). Once computed, values are stored in an associative memory (the "warehouse") in case they are demanded again later in the computation. The warehouse is periodically cleaned out using a heuristic called the "retirement plan". The heuristic is not perfect, but does not have to be: in an eductive computation, the program is not altered as in reduction. If discarded values are needed again, they can be recomputed.The pLucid interpreter performs extensive runtime checks and error messages quote the source line containing the offended operator. A special end-of-data object permits a very simple treatment of finite (terminating) input and output. Of special interest is its interface to UNIX, which allows any system command to be used as a filter inside a pLucid program.The interpreter performs well enough for nontrivial programs to be developed and tested. These include (simple versions of) a text formatter, a distributed airline reservation system, and a full screen editor.

A fixpoint semantics for nondeterministic data flow

Criteria for adequacy of a data flow semantics are discussed and Kahn's successful semantics for functional (deterministic) data flow is reviewed. Problems arising from nondeterminism are introduced and the paper's approach to overcoming them is introduced. The approach is based on generalizing the notion of input-output relation, essentially to a partially ordered multiset of input-output histories. The Brock-Ackerman anomalies concerning the input-output relation model of nondeterministic data flow are reviewed, and it is indicated how the proposed approach avoids them. A new anomaly is introduced to motivate the use of multisets. A formal theory of asynchronous processes is then developed. The main result is that the operation of forming a process from a network of component processes is associative. This result shows that the approach is not subject to anomalies such as that of Brock and Ackerman.

TUKI

An important feature of the Japanese Fifth Generation initiative is the investigation of novel computer architectures. One promising field of interest is that of data flow architectures inspired by the work at MIT and Manchester University. Having recognised the connection between functional programming and data flow, the work at Westfield has concentrated on the design of high level applicative languages. In this paper we describe a data flow architecture that was designed to support our language CAJOLE. We discuss a single processor architecture, a prototype of which has been built, and that can now be used as the building block for a closely-coupled distributed system.