Stress-testing Control Structures for Dynamic Dispatch in Java

Dynamic dispatch, or late binding of function calls, is a salient feature of object-oriented programming languages like C++ and Java. It can be costly on deeply pipelined processors, because dynamic calls translate to hard-to-predict indirect branch instructions, which are prone to causing pipeline bubbles. Several alternative implementation techniques have been designed in the past in order to perform dynamic dispatch without relying on these expensive branch instructions. Unfortunately it is difficult to compare the performance of these competing techniques, and the issue of which technique is best under what conditions still has no clear answer. In this study we aim to answer this question, by measuring the performance of four alternative control structures for dynamic dispatch on several execution environments, under a variety of precisely controlled execution conditions. We stress test these control structures using micro-benchmarks, emphasizing their strenghts and weaknesses, in order to determine the precise execution circumstances under which a particular technique performs best

The C Object System: Using C as a High-Level Object-Oriented Language

The C Object System (Cos) is a small C library which implements high-level concepts available in Clos, Objc and other object-oriented programming languages: uniform object model (class, meta-class and property-metaclass), generic functions, multi-methods, delegation, properties, exceptions, contracts and closures. Cos relies on the programmable capabilities of the C programming language to extend its syntax and to implement the aforementioned concepts as first-class objects. Cos aims at satisfying several general principles like simplicity, extensibility, reusability, efficiency and portability which are rarely met in a single programming language. Its design is tuned to provide efficient and portable implementation of message multi-dispatch and message multi-forwarding which are the heart of code extensibility and reusability. With COS features in hand, software should become as flexible and extensible as with scripting languages and as efficient and portable as expected with C programming. Likewise, Cos concepts should significantly simplify adaptive and aspect-oriented programming as well as distributed and service-oriented computingComment: 18

Pruning, Pushdown Exception-Flow Analysis

Statically reasoning in the presence of exceptions and about the effects of exceptions is challenging: exception-flows are mutually determined by traditional control-flow and points-to analyses. We tackle the challenge of analyzing exception-flows from two angles. First, from the angle of pruning control-flows (both normal and exceptional), we derive a pushdown framework for an object-oriented language with full-featured exceptions. Unlike traditional analyses, it allows precise matching of throwers to catchers. Second, from the angle of pruning points-to information, we generalize abstract garbage collection to object-oriented programs and enhance it with liveness analysis. We then seamlessly weave the techniques into enhanced reachability computation, yielding highly precise exception-flow analysis, without becoming intractable, even for large applications. We evaluate our pruned, pushdown exception-flow analysis, comparing it with an established analysis on large scale standard Java benchmarks. The results show that our analysis significantly improves analysis precision over traditional analysis within a reasonable analysis time.Comment: 14th IEEE International Working Conference on Source Code Analysis and Manipulatio

Iris: an Extensible Application for Building and Analyzing Spectral Energy Distributions

Iris is an extensible application that provides astronomers with a user-friendly interface capable of ingesting broad-band data from many different sources in order to build, explore, and model spectral energy distributions (SEDs). Iris takes advantage of the standards defined by the International Virtual Observatory Alliance, but hides the technicalities of such standards by implementing different layers of abstraction on top of them. Such intermediate layers provide hooks that users and developers can exploit in order to extend the capabilities provided by Iris. For instance, custom Python models can be combined in arbitrary ways with the Iris built-in models or with other custom functions. As such, Iris offers a platform for the development and integration of SED data, services, and applications, either from the user's system or from the web. In this paper we describe the built-in features provided by Iris for building and analyzing SEDs. We also explore in some detail the Iris framework and software development kit, showing how astronomers and software developers can plug their code into an integrated SED analysis environment.Comment: 18 pages, 8 figures, accepted for publication in Astronomy & Computin

Demand Forecasting Considering Actual Peak Load Periods Using Artificial Neural Network

Presently, electrical energy consumption continues to increase from year to year. Therefore, a short-term load forecasting is required that electricity providers can deliver continuous electrical energy to electricity consumers. By considering the estimation of the electrical load, the scheduling plan for operation and allocation of reserves can be managed well by the supply side. This study is focused on a forecasting of electrical loads using Artificial Neural Network (ANN) method considering a backpropagation algorithm model. The advantage of this method is to forecast the electrical load in accordance with patterns of past loads that have been taught. The data used for the learning is Actual Peak Load Period (APLP) data on the 150 kV system during 2017. Results show that the best network architecture is structured for the APLP Day and Night. Moreover, the momentum setting and understanding rate are 0.85 and 0.1 for the APLP Day. In contrast, 0.9 and 0.15 belong to the APLP Night. Based on the best network architecture, the APLP day testing process generates Mean Squared Error (MSE) around 0.04 and Mean Absolute Percentage Error (MAPE) around 4.66%, while the APLP Night generates MSE in 0.16 and MAPE in 16.83%

Modeling economic systems as locally-constructive sequential games

Real-world economies are open-ended dynamic systems consisting of heterogeneous interacting participants. Human participants are decision-makers who strategically take into account the past actions and potential future actions of other participants. All participants are forced to be locally constructive, meaning their actions at any given time must be based on their local states; and participant actions at any given time affect future local states. Taken together, these essential properties imply real-world economies are locally-constructive sequential games. This paper discusses a modeling approach, Agent-based Computational Economics, that permits researchers to study economic systems from this point of view. ACE modeling principles and objectives are first concisely presented and explained. The remainder of the paper then highlights challenging issues and edgier explorations that ACE researchers are currently pursuing

An Efficient and Flexible Implementation of Aspect-Oriented Languages

Compilers for modern object-oriented programming languages generate code in a platform independent intermediate language preserving the concepts of the source language; for example, classes, fields, methods, and virtual or static dispatch can be directly identified within the intermediate code. To execute this intermediate code, state-of-the-art implementations of virtual machines perform just-in-time (JIT) compilation of the intermediate language; i.e., the virtual instructions in the intermediate code are compiled to native machine code at runtime. In this step, a declarative representation of source language concepts in the intermediate language facilitates highly efficient adaptive and speculative optimization of the running program which may not be possible otherwise. In contrast, constructs of aspect-oriented languages - which improve the separation of concerns - are commonly realized by compiling them to conventional intermediate language instructions or by driving transformations of the intermediate code, which is called weaving. This way the aspect-oriented constructs' semantics is not preserved in a declarative manner at the intermediate language level. This representational gap between aspect-oriented concepts in the source code and in the intermediate code hinders high performance optimizations and weakens features of software engineering processes like debugging support or the continuity property of incremental compilation: modifying an aspect in the source code potentially requires re-weaving multiple other modules. To leverage language implementation techniques for aspect-oriented languages, this thesis proposes the Aspect-Language Implementation Architecture (ALIA) which prescribes - amongst others - the existence of an intermediate representation preserving the aspect-oriented constructs of the source program. A central component of this architecture is an extensible and flexible meta-model of aspect-oriented concepts which acts as an interface between front-ends (usually a compiler) and back-ends (usually a virtual machine) of aspect-oriented language implementations. The architecture and the meta-model are embodied for Java-based aspect-oriented languages in the Framework for Implementing Aspect Languages (FIAL) respectively the Language-Independent Aspect Meta-Model (LIAM) which is part of the framework. FIAL generically implements the work flows required from an execution environment when executing aspects provided in terms of LIAM. In addition to the first-class intermediate representation of aspect-oriented concepts, ALIA - and the FIAL framework as its incarnation - treat the points of interaction between aspects and other modules - so-called join points - as being late-bound to an implementation. In analogy to the object-oriented terminology for late-bound methods, the join points are called virtual in ALIA. Together, the first-class representation of aspect-oriented concepts in the intermediate representation as well as treating join points as being virtual facilitate the implementation of new and effective optimizations for aspect-oriented programs. Three different instantiations of the FIAL framework are presented in this thesis, showcasing the feasibility of integrating language back-ends with different characteristics with the framework. One integration supports static aspect deployment and produces results similar to conventional aspect weavers; the woven code is executable on any standard Java virtual machine. Two instantiations are fully dynamic, where one is realized as a portable plug-in for standard Java virtual machines and the other one, called Steamloom^ALIA , is realized as a deep integration into a specific virtual machine, the Jikes Research Virtual Machine Alpern2005. While the latter instantiation is not portable, it exhibits an outstanding performance. Virtual join point dispatch is a generalization of virtual method dispatch. Thus, well established and elaborate optimization techniques from the field of virtual method dispatch are re-used with slight adaptations in Steamloom^ALIA . These optimizations for aspect-oriented concepts go beyond the generation of optimal bytecode. Especially strikingly, the power of such optimizations is shown in this thesis by the examples of the cflow dynamic property, which may be necessary to evaluate during virtual join point dispatch, and dynamic aspect deployment - i.e., the selective modification of specific join points' dispatch. In order to evaluate the optimization techniques developed in this thesis, a means for benchmarking has been developed in terms of macro-benchmarks; i.e., real-world applications are executed. These benchmarks show that for both concepts the implementation presented here is at least circa twice as fast as state-of-the-art implementations performing static optimizations of the generated bytecode; in many cases this thesis's optimizations even reach a speed-up of two orders of magnitude for the cflow implementation and even four orders of magnitude for the dynamic deployment. The intermediate representation in terms of LIAM models is general enough to express the constructs of multiple aspect-oriented languages. Therefore, optimizations of features common to different languages are available to applications written in all of them. To proof that the abstractions provided by LIAM are sufficient to act as intermediate language for multiple aspect-oriented source languages, an automated translation from source code to LIAM models has been realized for three very different and popular aspect-oriented languages: AspectJ, JAsCo and Compose*. In addition, the feasibility of translating from CaesarJ to LIAM models is shown by discussion. The use of an extensible meta-model as intermediate representation furthermore simplifies the definition of new aspect-oriented language concepts as is shown in terms of a tutorial-style example of designing a domain specific extension to the Java language in this thesis

The Impact of Branch Prediction on Control Structures for Dynamic Dispatch in Java

Dynamic dispatch, or late binding of function calls, is a salient feature of object-oriented programming languages like C++ and Java. The target of a dispatched call changes according to the type of the object receiving the call. Due to inheritance the exact type is unknown at compile time, and therefore dispatch must occur in general at run time, implying a cost to the use of object-oriented programming languages. In previous work, we measured the performance of various equivalent non-object-oriented control structures to determine if dispatch cost can be reduced by translation. Measurements on a variety of virtual machines and hardware platforms show that alternative control structures are useful for a low number of expected types (low degrees of polymorphism). However, the gains differ substantially for different type patterns, even when the number of types is constant. The difference is likely to be caused by a processor's branch predictor, which guess the outcome of branches involved in dynamic dispatch . In this paper, we simulate branch predictors of Athlon and Pentium in order to validate this insight. The results show that branch prediction accuracy is indeed responsible. For successful optimization it is therefore not sufficient to guess the number of types occurring in a call. The type pattern should also be taken into account