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Another difference between simulation and acceleration and emulation is a consequence of accelerators using hardware for implementation – they have only two logic states – acting the way the silicon will when fabricated. This implies: They are not useful for analyzing X-state initialization.
After simulation the RTL description must be synthesized to fit in the final hardware (e.g. FPGA, ASIC). This step brings a lot of uncertainties because the real hardware is normally not as ideal as the simulation model. The differences between real world and simulation are a major reason why emulation is used in hardware design.
While emulation could, if taken to the extreme, go down to the atomic level, basing its output on a simulation of the actual circuitry from a virtual power source, this would be a highly unusual solution. Emulators typically stop at a simulation of the documented hardware specifications and digital logic.
Behavioral simulation – high-level simulation of a design's architectural operation, accurate at cycle-level or interface-level. Hardware emulation – Use of special purpose hardware to emulate the logic of a proposed design. Can sometimes be plugged into a system in place of a yet-to-be-built chip; this is called in-circuit emulation.
HIL simulation must include electrical emulation of sensors and actuators. These electrical emulations act as the interface between the plant simulation and the embedded system under test. The value of each electrically emulated sensor is controlled by the plant simulation and is read by the embedded system under test (feedback).
Hybrid simulation (or combined simulation) corresponds to a mix between continuous and discrete event simulation and results in integrating numerically the differential equations between two sequential events to reduce the number of discontinuities. [10] A stand-alone simulation is a simulation running on a single workstation by itself.
An important distinction can be made between two different applications of surrogate models: design optimization and design space approximation (also known as emulation). In surrogate model-based optimization, an initial surrogate is constructed using some of the available budgets of expensive experiments and/or simulations.
Because the results of a simulation are only as good as the underlying model(s), engineers, operators, and analysts must pay particular attention to its construction. To ensure that the results of the simulation are applicable to the real world, the user must understand the assumptions, conceptualizations, and constraints of its implementation.