IS TOPOLOGY IMPORTANT AGAIN? Effects of Contention on Message Latencies in Large Supercomputers
ACM Student Research Competition (SRC) 2008
Publication Type: Talk
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Summary
The largest and fastest supercomputers in the top 500 list deploy a scalable, three-dimensional torus or mesh interconnect. For these machines, the number of links (hops) traversed by a message has a direct effect on the time required to reach the destination. This is especially true in presence of bandwidth congestion, when multiple messages share links from source to destination. For large parallel machines with a significant diameter, this can become a serious performance bottleneck. Traditionally, application developers have neglected this fact because of the advantages of virtual cut-through and wormhole routing for most message sizes on small machines. This might not be true any longer due to the large diameters of machines.
This research will demonstrate the effect of network contention on message latencies and propose and evaluate techniques to minimize communication traffic and hence, bandwidth congestion on the network. This will be achieved by topology-aware mapping of tasks in an application. By placing communication tasks on processors which are in physical proximity on the network, communication can be restricted to near neighbors. This reduces link-sharing among messages and leads to a better utilization of the available bandwidth. Our aim is to minimize hop-bytes, which is a weighted sum of the number of hops between the source and destination for all messages, the weights being the message sizes. This can minimize the communication time and hence, lead to significant speed-ups for parallel applications and in certain cases, also remove scaling bottlenecks. The research will involve developing a general automatic topology-aware mapping framework which takes the task graph and processor graph as input, and outputs near-optimal mapping solutions.
This research will demonstrate the effect of network contention on message latencies and propose and evaluate techniques to minimize communication traffic and hence, bandwidth congestion on the network. This will be achieved by topology-aware mapping of tasks in an application. By placing communication tasks on processors which are in physical proximity on the network, communication can be restricted to near neighbors. This reduces link-sharing among messages and leads to a better utilization of the available bandwidth. Our aim is to minimize hop-bytes, which is a weighted sum of the number of hops between the source and destination for all messages, the weights being the message sizes. This can minimize the communication time and hence, lead to significant speed-ups for parallel applications and in certain cases, also remove scaling bottlenecks. The research will involve developing a general automatic topology-aware mapping framework which takes the task graph and processor graph as input, and outputs near-optimal mapping solutions.
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