Behavioral Simulation in FPGAs

16/08/2019, hardwarebee

An FPGA simulation can roughly be defined as an attempt to imitate or recreate the execution of a design or the operation of a system in an artificially produced environment. The simulation uses a model that is extremely close to or almost the same as the actual subject at question. The user clearly defines the characteristics, functions, properties, and behavior of the model, making it a thoroughly defined and described description of the design.


With the increasing advancements being made in the field of technology, newer ways of creating and FPGA simulations for theoretical designs before actual implementations are being discovered and made commonplace.


What is Behavioral Simulation?


A behavioral simulation focuses primarily on a high-level simulation model. It’s a fast simulation method but is also less accurate in its results. The goal here is to take an abstract or general idea for a FPGA code and use a behavioral simulation to run it through in order to determine what components, gates, connections, and structures actually need to be used in order to physically and functionally implement that design in real time.


Using behavioral simulation, we take a pre synthesis description of the design that we wish to simulate, in a Hardware Description Language, or HDL. Using such FPGA simulation, designers can also view and implement alternative options to test the range of possibilities within their ideal frame.


As the design is developed, it is tested and verified using behavioral simulation as it allows you to test the syntax and functionality of the design and its various connections without having to admit information regarding the timing. With the testing function being available so early to use in the designing and execution process, it is relatively easy to catch any potential errors and nip the issue resulting in significant cost and time reduction.


One of the greatest benefits of behavioral simulation as opposed to structural and timing simulations, is that it is a much faster solution and produces rapid results. The downside, however, is that it is relatively vague and general, skipping over the minor details of the design and only focusing on a diffuse design outline.

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