This is the dataset of three non-Spiking Neural Network applications running on the SpiNNaker platform: JPEG image encoding, JPEG image decoding, and edge detection (referred to as A1, A2, and A3 respectively in the paper). The application A1 and A2 are the first applications that are developed by considering the impact of DMA Full Counter (DFC) for performance improvement. Both application retrieve/store data from/to SDRAM using DMA mechanism. The application A3 uses the old mechanism (without involving DFC), in which a master core is assigned with a task for coordinating DMA among cores in a SpiNNaker chip. The applications A1, A2, and A3 were run alternately whilst changing the governor. During the application execution, we measure the energy consumption and temperature of SpiNNaker chips using a SpiNNaker profiler program.
|Date made available||30 Oct 2017|
|Publisher||University of Manchester|