Abstract
DAME (Data Migration Environment) uses transparent supports to overcome inefficiencies in data parallel programming. These supports hide irregular network topology, dynamically adapt the data distribution to platform conditions, and mask the consequent nonuniform distribution to the programmer. The authors compare DAME's performance with that of some popular frameworks. They begin by discussing DAME's three main design goals: efficiency, transparency, and scalability. Next, they describe the five supports that DAME gives the programmer: virtual topology, data distribution, data management, interprocess communication, and workload reconfiguration. Then, they present the results they obtained from experiments using 10 workstations that provide a hardware heterogeneous, data homogeneous, nonuniform platform. The results show that DAME provides a virtual single program, multiple data machine that overcomes most of the differences that distinguish a parallel virtual machine from an ideal SPMD machine.
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