摘要:
The present invention presents an effective Cycle-count Accurate Transaction level (CCA-TLM) full bus modeling and simulation technique. Using the two-phase arbiter and master-slave models, an FSM-based Composite Master-Slave-pair and Arbiter Transaction (CMSAT) model is proposed for efficient and accurate dynamic simulations. This approach is particularly effective for bus architecture exploration and contention analysis of complex Multi-Processor System-on-Chip (MPSoC) designs.
摘要:
The present invention provides a method for simulating processor power consumption, the method comprises: simulating a simulated processor; utilizing a power analysis model to analyze the simulated processor's execution of at least one fragment of a program, for generating power analysis of a plurality of basic blocks of the at least one fragment; computing at least one power correction factor between the plurality of basic block; utilizing a processing apparatus to generate a simulation model with power annotation based on the power analysis and the at least one power correction factor; and predicting power consumption of the simulated processor based on the simulation model with power annotation.
摘要:
The present invention discloses a cycle-count-accurate (CCA) processor modeling, which can achieve high simulation speeds while maintaining timing accuracy of the system simulation. The CCA processor modeling includes a pipeline subsystem model and a cache subsystem model with accurate cycle with accurate cycle count information and guarantees accurate timing and functional behaviors on processor interface. The CCA processor modeling further includes a branch predictor and a bus interface (BIF) to predict the branch of pipeline execution behavior (PEB) and to simulate the data accesses between the processor and the external components via an external bus, respectively. The experimental results show that the CCA processor modeling performs 50 times faster than the corresponding Cycle-accurate (CA) model while providing the same cycle count information as the target RTL model.