Evaluating scheduling policies for fine-grain communication protocols on a cluster of SMPs ?
Distributed-memory parallel computers and networks of workstations (NOWs) both rely on efficient communication over increasingly high-speed networks. Software communication protocols are often the performance bottleneck. Several current and proposed parallel systems address this problem by dedicating one general-purpose processor in a symmetric multiprocessor (SMP) node specifically for protocol processing. This protocol processing convention reduces communication latency and increases effective bandwidth, but also reduces the peak performance since the dedicated processor no longer performs computation. In this paper, we study a parallel machine with SMP nodes and compare two protocol processing policies: the Fixed policy, which uses a dedicated protocol processor; and the Floating policy, where all processors perform both computation and protocol processing. The results from synthetic microbenchmarks and five macrobenchmarks show that: (i) a dedicated protocol processor benefits light-weight protocols much more than heavy-weight protocols, (ii) a dedicated protocol processor is generally advantageous when there are four or more processors per node, (iii) multiprocessor node performance is not as sensitive to interrupt overhead as uniprocessor node because a message arrival is likely to find an idle processor on a multiprocessor node, thereby eliminating interrupts, (iv) the system with the lowest cost-performance will include a dedicated protocol processor when interrupt overheads are much higher than protocol weightas in light-weight protocols.
clusters of smps protocol processing policies fine-grain software protocols scheduling communication distributed shared memory