Smart hill climbing for agile dynamic mapping in many-core systems

Stochastic hill climbing algorithm is adapted to rapidly find the appropriate start node in the application mapping of network-based many-core systems. Due to highly dynamic and unpredictable workload of such systems, an agile run-time task allocation scheme is required. The scheme is desired to map the tasks of an incoming application at run-time onto an optimum contiguous area of the available nodes. Contiguous and unfragmented area mapping is to settle the communicating tasks in close proximity. Hence, the power dissipation, the congestion between different applications, and the latency of the system will be significantly reduced. To find an optimum region, we first propose an approximate model that quickly estimates the available area around a given node. Then the stochastic hill climbing algorithm is used as a search heuristic to find a node that has the required number of available nodes around it. Presented agile climber takes the steps using an adapted version of hill climbing algorithm named Smart Hill Climbing, SHiC, which takes the runtime status of the system into account. Finally, the application mapping is performed starting from the selected first node. Experiments show significant gain in the mapping contiguousness which results in better network latency and power dissipation, compared to state-of-the-art works.