CoNA: Dynamic application mapping for congestion reduction in many-core systems

Mohammad Fattah, Marco Ramírez, M. Daneshtalab, P. Liljeberg, J. Plosila
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引用次数: 68

Abstract

Increasing the number of processors in a single chip toward network-based many-core systems requires a run-time task allocation algorithm. We propose an efficient mapping algorithm that assigns communicating tasks of incoming applications onto resources of a many-core system utilizing Network-on-Chip paradigm. In our contiguous neighborhood allocation (CoNA) algorithm, we target at the reduction of both internal and external congestion due to detrimental impact of congestion on the network performance. We approach the goal by keeping the mapped region contiguous and placing the communicating tasks in a close neighborhood. A completely synthesizable simulation environment where none of the system objects are assumed to be ideal is provided. Experiments show at least 40% gain in different mapping cost functions, as well as 16% reduction in average network latency compared to existing algorithms.
CoNA:用于减少多核系统中的拥塞的动态应用程序映射
将单个芯片中的处理器数量增加到基于网络的多核系统需要运行时任务分配算法。我们提出了一种有效的映射算法,该算法利用片上网络范式将传入应用程序的通信任务分配到多核系统的资源上。在我们的连续邻域分配(CoNA)算法中,我们的目标是减少由于拥塞对网络性能的有害影响而导致的内部和外部拥塞。我们通过保持映射区域连续并将通信任务放置在邻近区域来实现目标。提供了一个完全可合成的仿真环境,其中没有一个系统对象被认为是理想的。实验表明,与现有算法相比,不同映射成本函数的增益至少为40%,平均网络延迟降低16%。
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