Car Systems are becoming more and more intelligent. In addition to trumpeting the entry of self driving cars into the market, today's cars are expected to behave like smart houses because every aspect of their internal operation is monitored, controlled, and communicated with other functions of the car. These complexities, of course, lead to the need for ever more complex special technologies -- a transition from digital to mixed signals. In addition, automotive safety standards, such as ISO 26262, to avoid application-specific integrated circuit system failures and detect control random hardware failures, make these very different from other integrated circuits. Today's Asics must include position control, speed control, hysteresis control, timing control, and so on. These asics must also meet other stringent reliability, eligibility, and longer life-cycle standards, all of this leads to a lot of development time and money being spent on these issues. The qualification process can account for more than 30 per cent of the total cost.

Reduce the risk of multiple rotations

There is an inherent risk that the implementation of this design will require multiple strip changes and re-audits, which will increase costs and extend the time to market beyond acceptable limits. In addition, custom automotive tape out is difficult to arrange with foundries due to the low volume of such specialties compared to other more dominant high volume specialty counterparts. Reducing these risks is essential to staying competitive. The FPGA prototype greatly reduces these risks by testing and validating asic design features long before the design is complete. By performing an fpga-based prototype design prior to layout generation, any problems in the design or specification can be easily identified, thus reducing the possibility of rerotation and multiple tape outputs.

Precision is crucial-to meet stringent safety standards

Today's FPGA prototype systems can handle even the most complex designs. The application-specific Integrated Circuit function not only needs to be verified by the mixed signals, but also needs to detect the parasitic effects that are common in the automotive environment, which may be difficult to model. The prototype systems can easily process mixed-signal aspects of the design and can easily simulate parasitic effects as they occur at low operating frequencies. Unlike analog models, which are either imprecise or too slow, the FPGA prototype model provides the extremely high precision and speed required to effectively validate the design.

Must be able to link the FPGA model to security-compatible development tools such as ISO 26262. Transaction-level interfaces play a key role in bridging the abstraction layer between behavioral models and real-time hardware. These converters provide a means of communication between software running on the host and fpga-based prototype platforms, which usually include memory, processors, and high-speed interfaces.

The unique patent pending protopbridgette system is one solution for this type of high speed communication. Protobridge provides an interface between a software program and the axi-compliant hardware world. There are two key components: the axi-to-pcie Bridge to the host, and the C-API to communicate with the design through the bridge. The software into AXI trading machines provides new flexibility for designers to build arm-based systems. It is coupled to a pcie interface that supports transfer speeds up to 500 MBYTES / SEC, providing a perfect development platform for data intensive applications.

Such a system would allow designers to use fpga-based prototypes for algorithmic verification, IP design, simulation acceleration, and corner implementation testing earlier in the design project. The prototype, combined with the trader interface, enables a number of interesting applications throughout the design process.

Large, decentralized design teams work together within a single FPGA prototype

As we have pointed out before, many of the systems in a car must work together and communicate effectively with each other. However, the design of these individual components is often created, tested, validated, and implemented by very different teams within the same company. In addition, many teams and people in each team are located in different geographical locations, and you start to see another kind of complexity emerge. How do you use these resources to share information about these different groups? Yake Hongyu's cloud cubem and NEUROTM systems provide an ideal host FPGA field, allowing a large number of remote users to run both system testing and software development simultaneously.

Prodigy Cloud Cube is an enterprise-class chassis that supports up to 32 FPGAS, using any combination of Prodigy logic modules, while the neuro cloud-based software interface allows management of parallel / remote software development. This type of approach also provides a low-cost solution to support large amounts of replication.