Computer Science – Distributed – Parallel – and Cluster Computing
Scientific paper
2011-04-19
Computer Science
Distributed, Parallel, and Cluster Computing
Scientific paper
Many-core architectures of the future are likely to have distributed memory organizations and need fine grained concurrency management to be used effectively. The Self-adaptive Virtual Processor (SVP) is an abstract concurrent programming model which can provide this, but the model and its current implementations assume a single address space shared memory. We investigate and extend SVP to handle distributed environments, and discuss a prototype SVP implementation which transparently supports execution on heterogeneous distributed memory clusters over TCP/IP connections, while retaining the original SVP programming model.
Koivisto Juha
van Tol Michiel W.
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