High-Throughput Maps on Message-Passing Manycore Architectures: Partitioning versus Replication
The advent of manycore architectures raises new scalability challenges for concurrent applications. Implementing scalable data structures is one of them. Several manycore architectures provide hardware message passing as a means to efficiently exchange data between cores. In this paper, we study the implementation of high-throughput concurrent maps in message-passing manycores. Partitioning and replication are the two approaches to achieve high throughput in a message-passing system. Our paper presents and compares different strongly-consistent map algorithms based on partitioning and replication. To assess the performance of these algorithms independently of architecture-specific features, we propose a communication model of message-passing manycores to express the throughput of each algorithm. The model is validated through experiments on a 36-core TILE-Gx8036 processor. Evaluations show that replication outperforms partitioning only in a narrow domain.
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