Adjustable contiguity of run-time task allocation in networked many-core systems

In this paper, we propose a run-time mapping algorithm, CASqA, for networked many-core systems. In this algorithm, the level of contiguousness of the allocated processors (α) can be adjusted in a fine-grained fashion. A strictly contiguous allocation (α = 0) decreases the latency and power dissipation of the network and improves the applications execution time. However, it limits the achievable throughput and increases the turnaround time of the applications. As a result, recent works consider non-contiguous allocation (α = 1) to improve the throughput traded off against applications execution time and network metrics. In contradiction, our experiments show that a higher throughput (by 3%) with improved network performance can be achieved when using intermediate α values. More precisely, up to 35% drop in the network costs can be gained by adjusting the level of contiguity compared to non-contiguous cases, while the achieved throughput is kept constant. Moreover, CASqA provides at least 32% energy saving in the network compared to other works.