This paper proposes a top-down co-verification approach in the design of embedded systems composed of both hardware and software, for multimedia applications. In order to realize the optimized embedded system in cost, performance, power consumption and flexibility, hardware/software co-design becomes to be essential. In this top-down co-design flow, a target design is verified at three different levels: (1) algorithmic, (2) implementation, and (3) experimental. We have developed a methodology of top-down co-verification, which consists of the system level simulation at the algorithmic level, two type of co-simulations at the implementation level and the co-emulation at the experimental level. We have realized an environment optimized for verification performance by employing verification models appropriate to each verification stage and an efficient top-down environment by introducing the component logical bus architecture as the interface between hardware and software. Through actual application to a image compression and expansion system, the possibility of efficient co-verification was demonstrated.

The problem of synthesizing a minimum-cost logic network is formulated for a genetic algorithm (GA). When benchmarked against a commercial logic synthesis tool, an odd parity circuit required 24 basic cells (BCs) versus 28 BCs for the design produced by the commercial system. A magnitude comparator required 20 BCs versus 21 BCs for the commercial system's design. Poor temporal performance, however, is the main disadvantage of the GA-based approach. The design of a hardware-based cost function that would accelerate the GA by several thousand times is described.

We propose a top-down approach for cosimulation of hardware/software co-designs for embedded systems and introduce a component logical bus architecture as an interface between software components implemented by processors and hardware components implemented by custom logic circuits. Co-simulation using a component logical bus architecture is possible is the same environment from the stage at which the processor is not yet finalized to the stage at which the processor is modeled in register transfer language. Models based upon a component logical bus architecture can be circulated and reused. We further describe experimental results of our approach.

Genetic algorithms were introduced by Holland in 1975 as a method of solving difficult optimization problems by means of simulated evolution. A major drawback of genetic algorithms is their slowness when emulated by software on conventional computers. Described is an adaptation of the original genetic algorithm that is advantageous to hardware implementation along with the architecture of a hardware framework that performs the functions of population storage, selection, crossover, mutation, fitness evaluation, and survival determination. Programming of the framework is illustrated with the set coverage problem that exhibits a 6,000 speed-up over software emulation on a 100 MHz workstation.

In this paper we propose a co-design method for control systems using combination of models. By co-design," we mean a cooperative design method in which the behavior of the entire system is simulated as a single model while parameters of the system are being optimized. Our co-design method enables the various subsystems in the system, which have been designed independently as tasks assigned to different designers in the traditional design method, to be designed simultaneously in a unified cooperative way from the system-wide perspective of a system designer. Our proposed method combines models of controlling and controlled subsystems into a single model for the behavior of the entire control system. After the optimum control conditions are determined through simulation of the combined models, based on the corresponding algorithms and parameters, ASIC design proceeds quickly with accurate verification using iterative replacements of the behavior model by the electronic circuit model. To evaluate the proposed method, we implemented a design environment. We then applied our method to the design of ASICs in three test cases (in a control system and in audio-visual systems) to investigate its effectiveness. This paper introduces the concepts of the proposed co-design method, the design environment and the experimental results, and points out the new issues for system design.