Multiple, often conflicting objectives arise naturally in most real-world optimization scenarios. As evolutionary algorithms possess several characteristics due to which they are well suited to this type of problem, evolution-based methods have been used for multiobjective optimization for more than a decade. Meanwhile evolutionary multiobjective optimization has become established as a separate subdiscipline combining the fields of evolutionary computation and classical multiple criteria decision making. In this paper, the basic principles of evolutionary multiobjective optimization are discussed from an algorithm design perspective. The focus is on the major issues such as fitness assignment, diversity preservation, and elitism in general rather than on particular algorithms. Different techniques to implement these strongly related concepts will be discussed, and further important aspects such as constraint handling and preference articulation are treated as well. Finally, two applications will presented and some recent trends in the field will be outlined.

Evolutionary Algorithms for Multiobjective Optimization: Methods and Applications

The authors build upon research by E. A. Lee (1991) concerning the token flow model, an analytical model for the behavior of dataflow graphs with data-dependent control flow, by analyzing the properties of cycles of the schedule: sequences of actor executions that return the graph to its initial state. Necessary and sufficient conditions are given for the existence of a bounded cyclic schedule as well as sufficient conditions for execution of the graph in bounded memory. The techniques presented apply to a more general class of dataflow graphs than previous methods. >

/pdf/scheduling-dynamic-dataflow-graphs-with-bounded-memory-using-3i2kil2dg2.pdf

Scheduling dynamic dataflow graphs with bounded memory using the token flow model

The port-based object is a new software abstraction for designing and implementing dynamically reconfigurable real-time software. It forms the basis of a programming model that uses domain-specific elemental units to provide specific, yet flexible, guidelines to control engineers for creating and integrating software components. We use a port-based object abstraction, based on combining the notion of an object with the port-automaton algebraic model of concurrent processes. It is supported by an implementation using domain-specific communication mechanisms and templates that have been incorporated into the Chimera real-time operating system and applied to several robotic applications. This paper describes the port-based object abstraction, provides a detailed analysis of communication and synchronization based on distributed shared memory, and describes a programming paradigm based on a framework process and code templates for quickly implementing applications.

/pdf/design-of-dynamically-reconfigurable-real-time-software-kod5mxnyqu.pdf

Design of dynamically reconfigurable real-time software using port-based objects

Dataflow has proven to be an attractive computation model for programming digital signal processing (DSP) applications. A restricted version of dataflow, termed synchronous dataflow (SDF), that offers strong compile-time predictability properties, but has limited expressive power, has been studied extensively in the DSP context. Many extensions to synchronous dataflow have been proposed to increase its expressivity while maintaining its compile-time predictability properties as much as possible. We proposed a parameterized dataflow framework that can be applied as a meta-modeling technique to significantly improve the expressive power of any dataflow model that possesses a well-defined concept of a graph iteration, Indeed, the parameterized dataflow framework is compatible with many of the existing dataflow models for DSP including SDF, cyclo-static dataflow, scalable synchronous dataflow, and Boolean dataflow. In this paper, we develop precise, formal semantics for parameterized synchronous dataflow (PSDF)-the application of our parameterized modeling framework to SDF-that allows data-dependent, dynamic DSP systems to be modeled in a natural and intuitive fashion. Through our development of PSDF, we demonstrate that desirable properties of a DSP modeling environment such as dynamic reconfigurability and design reuse emerge as inherent characteristics of our parameterized framework. An example of a speech compression application is used to illustrate the efficacy of the PSDF approach and its amenability to efficient software synthesis techniques. In addition, we illustrate the generality of our parameterized framework by discussing its application to cyclo-static dataflow, which is a popular alternative to the SDF model.

Parameterized dataflow modeling for DSP systems

/pdf/design-of-dynamically-reconfigurable-red-time-software-using-st5mym2mv3.pdf

Design of Dynamically Reconfigurable Red-Time Software using Port-Based Objects

For the design of complex digital signal processing systems, block diagram oriented synthesis of real time software for programmable target processors has become an important design aid. The synthesis approach discussed in this paper is based on multirate block diagrams with scalable synchronous dataflow (SSDF) semantics. For this class of dataflow graphs optimum vectorization techniques are introduced. Vectorization is treated as a transformation on an SSDF graph which increases the number of samples consumed or produced per activation of a block according to a specific optimization criterion. The presented optimization criterion jointly minimizes context-switching overhead caused by an activation of a block and maximizes the degree of vector processing of the important class of "single appearance minimum activation schedules" (SAMAS). This class comprises schedules in which each block appears exactly once and is activated minimum times. First, "single appearance" implies the most compact implementation of a schedule in terms of program memory. Second, "minimum activation" implies increased throughput according to optimum vectorization and minimal context-switching. >

Optimum vectorization of scalable synchronous dataflow graphs

A synthesis environment that targets software programmable architectures such as digital signal processors (DSPs) is presented. These processors are well suited for implementation of real-time signal processing systems with medium throughput requirements. Techniques that tightly couple the synthesis environment to an existing communication system simulator are also presented. This enables a seamless transition between the simulation and implementation design level of communication systems. Special focus is on optimization techniques for mapping data flow oriented block diagrams onto DSPs. The combination of different mapping and optimization strategies allows comfortable synthesis of real-time code that is highly adapted to application-specific needs imposed by constraints on memory space, sampling rate, or latency. Thus, tradeoff analysis is supported by efficient interactive or automatic exploration of the design space. All presented concepts are illustrated by the design of a phase synchronizer with automatic gain control on a floating-point DSP. >

High-level software synthesis for the design of communication systems

Integrating the simulation and implementation of complex digital signal processing systems based on block diagram oriented simulation and code generation is described. The basic concept consists of a generic, i.e., reusable, block diagram with different underlying semantics. This allows the generation of software adapted to the special needs of both simulation and implementation. In order to achieve application-specific implementations, the code generator supports tradeoffs between implementation constraints such as code size, throughput, or latency. Therefore, a wide spectrum of different optimization strategies has been incorporated in the code generator. >

A novel approach to the integration of simulation and implementation to digital signal processing systems

For the design of complex digital signal processing systems, block diagram oriented simulation has become a widely accepted standard Current research is concerned with the coupling of heterogenous simulation engines and the transition from simulation to the implementation of digital signal processing systems Due to the difficulty in mastering complex design spaces high level hardware and software synthesis is becoming increasingly important The authors concentrate on the block diagram oriented software synthesis of digital signal processing systems for programmable processors, such as digital signal processors (DSP) They present the synthesis environment DESCARTES illustrating novel optimization strategies Furthermore they discuss goal directed software synthesis, by which code is interactively or automatically generated, which can be adapted to the application specific needs imposed by constraints on memory space, sampling rate or latency >

High level software synthesis for signal processing systems

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Optimum vectorization of scalable synchronous dataflow graphs

High-level software synthesis for the design of communication systems

A novel approach to the integration of simulation and implementation to digital signal processing systems

High level software synthesis for signal processing systems