AI-driven system-on-chip designs are placing unprecedented demands on compute, memory, and connectivity, according to a new white paper highlighted by Semiconductor Engineering. Interfaces such as PCIe, CXL, Ethernet, HBM, USB, and UFS are no longer afterthoughts; they are now critical to overall system performance and verification success. As software and hardware complexity grow together, development teams need verification strategies that go beyond simple simulation.
The paper argues for a layered approach that combines simulation, hardware-assisted verification, virtual prototyping, and silicon validation. Emulation and prototyping platforms are singled out for their ability to uncover rare protocol issues, long-duration failures, and software-driven corner cases before tape-out. These tools help reduce risk and accelerate time-to-market for complex AI SoCs and multi-die systems.
Virtual models and transaction-level platforms also play a key role by enabling parallel hardware and software development. This parallelization speeds bring-up and lowers project risk. The recommended approach is a continuous verification strategy that spans architectural exploration, software development, simulation, hardware-assisted verification, and post-silicon validation, with proven IP and verification solutions supporting interoperability and reliable system integration throughout.