Identify Risk and (Opportunity) Cost. Based on the challenges identified in the first step, managers often analyze the risk and cost of such challenges. Costs should include direct costs as well as opportunity costs. Key areas that have been identified by VSD adopters are shown in Table 3 below:

Table 3. Risks and challenges vs costs and side effects

How can organizations implement VSD?
VSD introduces some fundamental process change into existing product life cycle work flows. As a result, its adoption is not an overnight process. It may take some time for the engineering, marketing and support teams to fully realize what can be done, and how it should be done in order to gain the benefits of VSD. Instead, the adoption of VSD should be an evolving process. As it is used, more models are created, developers become more familiar with what can be done and the resultant value and benefit of VSD grows too.

Identify Long-Term Organizational Goals for VSD. The checklist in Table 4 below can be used to help prioritize some of your long-term organizational goals and hopes for VSD. It can also be used to help assess the features and capabilities of candidate solutions.

Table 4. Long-Term Organizational Goals

Identify Short-Term Opportunities for VSD. As VSD represents a significant change to the way that engineering, marketing and sales teams have done business, it can be challenging to introduce into an organization. Consequently, it is best to introduce VSD into projects which can immediately benefit from its features and capabilities.

Identify VSD-candidate projects. Often, the projects that offer the easiest path for the introduction of VSD are within the system architecture or software development phases.

However, projects in the deployment phase can also be easy supported if they are based on commodity hardware for which an off-the-shelf model exists or if those models can be easily produced. If the hardware used is sufficiently expensive or hard to configure, creating new VSD models will be profitable even for quite custom hardware setups.

Identify the intersection of physical and virtual platforms. Because it takes some training and effort to create models, those projects that can benefit immediately from VSD will have a good correlation between the physical hardware platform and the available virtual platforms or component models.

Indentify problematic projects or programs. Projects that have progressed far into the software development and even deployment phases have used VSD to capture and resolve bugs that had evaded resolution for months. VSD also provides developers and testers with increased access to hardware so that they can put more resources towards problem solving.

Selecting the simulation-model infrastructure
The simulation-model infrastructure is that software which manages and runs virtual platforms. Some might consider it to be a simulation engine or the simulator itself. Many features and characteristics of this infrastructure are critical to enabling the full benefits of VSD. The model infrastructure must contain key high-level system features, including:

* Fast performance " the system must be fast enough to run the target software fast enough to satisfy software developers who are used to running software on physical hardware.

Speed is one thing that differentiates a VSD platform from those simulation tools provided by the electronic design automation (EDA) industry. Although EDA tools are extremely accurate from a hardware perspective and they can be used to develop low level initialization and test code, they are too slow to be practical for OS, application or systems software.

* Scalability and High Fidelity (accuracy) " virtual models must be able to scale from a simple register model to one that precisely duplicates the functionality of the physical hardware component must be supported.

* Host Scalable " in order to retain adequate performance, the model infrastructure must be capable of utilizing multiple hosts for work sharing on large models.

* Extensive Off-the-Shelf Model Selection " given the complexity of model development, the selected solution must not only support the ability to run complex, mixed-architecture systems, but it should also provide a range of off-the-shelf models across the various CPU, DSP, and network options. These models can be run standalone, or they can be used as the basis for custom model development.