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The Importance of Performance-Oriented Flexibility in System Software for Large-Scale Shared-Memory Multiprocessors

There has been a growing interest in large-scale sharedmemory multiprocessors that support a wide range of application workloads. The architectural trend of such systems has been towards a distributed architecture, where processors, memory modules, and I/O modules are distributed throughout the machine, connected by some form of interconnect (rings, meshes, trees). Examples include the Stanford DASH [10] and FLASH [9], Massachusetts Institute of Technology Alewife [2], University of Toronto Hector [15], and Kendall Square Research KSR-1 [3] multiprocessors. In this type of architecture, commonly referred to as a Non-Uniform Memory Access time (NUMA) system, managing the locality between various resources is key to obtaining good performance.