ODIN-Based CPU-GPU Architecture with Replay-Driven Simulation and Emulation

TL;DR

This paper introduces a replay-driven validation approach for CPU-GPU chiplet architectures, enabling reliable system-level testing and debugging through deterministic waveform replay in simulation and emulation.

Contribution

It presents a novel replay-based validation methodology that improves efficiency and confidence in pre-silicon validation of complex CPU-GPU chiplet systems.

Findings

Accelerates system integration and debugging processes.

Enables end-to-end workload execution within a quarter.

Improves validation reliability through deterministic replay.

Abstract

Integration of CPU and GPU technologies is a key enabler for modern AI and graphics workloads, combining control-oriented processing with massive parallel compute capability. As systems evolve toward chiplet-based architectures, pre-silicon validation of tightly coupled CPU-GPU subsystems becomes increasingly challenging due to complex validation framework setup, large design scale, high concurrency, non-deterministic execution, and intricate protocol interactions at chiplet boundaries, often resulting in long integration cycles. This paper presents a replay-driven validation methodology developed during the integration of a CPU subsystem, multiple Xe GPU cores, and a configurable Network-on-Chip (NoC) within a foundational SoC building block targeting the ODIN integrated chiplet architecture. By leveraging deterministic waveform capture and replay across both simulation and emulation using a single design database, complex GPU workloads and protocol sequences can be reproduced reliably at the system level. This approach significantly accelerates debug, improves integration confidence, and enables end-to-end system boot and workload execution within a single quarter, demonstrating the effectiveness of replay-based validation as a scalable methodology for chiplet-based systems.