Modeling and Simulation of System Bus and Memory Collisions in Heterogeneous SoCs

A system simulator is proposed and developed, which can help to optimize design parameters and hence minimize the number of collisions. In order to search the optimal design parameter combination which meets the user requirement, the proposed simulator has some knobs: partitioning between software and hardware, scheduling the operations in the system, and memory merging, all of which can be adjusted to predict collisions and search the optimal architecture. Also, design parameters can be adjusted sequentially to cover all design options and estimate the predicted performance for each option. The proposed system simulator is evaluated with an example signal processing algorithm, orthogonal matching pursuit (OMP) algorithm. Performances of four cases of the OMP algorithm are predicted by the proposed simulator and in turn are compared with the actual performances on ZedBoard. The proposed simulator can predict the performance of heterogeneous systems on chips with under 5% error for all the candidate architectures for OMP while taking the system bus and memory conflicts into account. Moreover, the optimized heterogeneous SoC architecture for the OMP algorithm improves performance by up to 32% compared with the conventional CAG-based approach. The proposed simulator is verified that the proposed performance estimation algorithm is generally applicable to estimate the performance of any heterogeneous SoC architecture. For example, the estimation error is measured to be no more than 5.9% for the convolutional layers of CNNs and no more than 5.6% for the LDPC-coded MIMO-OFDM. In addition, the optimized heterogeneous SoC architecture improves performance by up to 48% for the third convolutional layer of AlexNet and 56% for the LDPC-coded MIMO-OFDM. Lastly, compared with the conventional simulation-based approaches, the proposed estimation algorithm provides a speedup of one to two orders of magnitudes. The source code is available on the GitHub repository:
https://github.com/SDL-KU/HetSoCopt
.