WildFire: A Scalable Path for SMPs

Researchers have searched for scalable alternatives to the symmetric multiprocessor (SMP) architecture since it was first introduced in 1982. This paper introduces an alternative view of the relationship between scalable technologies and SMPs. Instead of replacing large SMPs with scalable technology, we propose new scalable techniques that allow large SMPs to be tied together efficiently, while maintaining the compatibility with, and performance characteristics of, an SMP. The trade-offs of such an architecture differ from those of traditional, scalable, Non-Uniform Memory Architecture (cc-NUMA) approaches. WildFire is a distributed shared-memory (DSM) prototype implementation based on large SMPs. It relies on two techniques for creating application-transparent locality: Coherent Memory Replication (CMR), which is a variation of Simple COMA/Reactive NUMA, and Hierarchical Affinity Scheduling (HAS). These two optimizations create extra node locality, which blurs the node boundaries to an application such that SMP-like performance can be achieved with no NUMA-specific optimizations. We present a performance study of a large OLTP benchmark running on DSMs built from various-sized nodes and with varying amounts of application-transparent locality. WildFire’s measured performance is shown to be more than two times that of an unoptimized NUMA implementation built from small nodes and within 13% of the performance of the ideal implementation: a large SMP with the same access time to its entire shared memory as the local memory access time of WildFire.