Shared memory is widely believed to provide an easier programming model than message passing for expressing parallel algorithms. Distributed Shared Memory (DSM) systems provide the illusion of shared memory on top of standard message passing hardware at very low implementation cost, but provide acceptable performance for only a limited class of applications. We argue that the principal sources of overhead overhead in DSM systems can be dramatically reduced with modest amounts of hardware support (substantially less than is required for hardware cache coherence). Specifically, we present and evaluate a family of protocols designed to exploit hardware support for a global, but non-coherent, physical address space. We consider systems both with and without remote cache fills, fine-grain access faults, "doubled" writes to local and remote memory, and merging write buffers. We also consider varying levels of latency and bandwidth. We evaluate our protocols using execution driven simulation, comparing them to each other and to a state-of-the-art protocol for traditional message-based networks. For the programs in our application suite, protocols taking advantage of the global address space improve performance by a minimum of 50% and sometimes by as much as an order of magnitude.
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