Towards Low-Complexity Scalable Shared-Memory Architectures

Plentiful research has addressed low-complexity software-based shared-memory systems since the idea was first introduced more than two decades ago. However, software-coherent systems have not been very successful in the commercial marketplace. We believe there are two main reasons for this: lack of performance and/or lack of binary compatibility. This thesis studies multiple aspects of how to design future binary-compatible high-performance scalable shared-memory servers while keeping the hardware complexity at a minimum. It starts with a software-based distributed shared-memory system relying on no specific hardware support and gradually moves towards architectures with simple hardware support. The evaluation is made in a modern chip-multiprocessor environment with both high-performance compute workloads and commercial applications. It shows that implementing the coherence-violation detection in hardware while solving the interchip coherence in software allows for high-performing binary-compatible systems with very low hardware complexity. Our second-generation hardware-software hybrid performs on par with, and often better than, traditional hardware-only designs. Based on our results, we conclude that it is not only possible to design simple systems while maintaining performance and the binary-compatibility envelope, it is often possible to get better performance than in traditional and more complex designs. We also explore two new techniques for evaluating a new shared-memory design throughout this work: adjustable simulation fidelity and statistical multiprocessor cache modeling.