A context switching streaming memory architecture to accelerate a neocortex model

作者：Vutsinas Christopher N; Taha Tarek M^*; Rice Kenneth L

来源：Microprocessors and Microsystems, 2009, 33(2): 117-128.

DOI：10.1016/j.micpro.2008.08.011

• Biologically inspired
• Neocortex model
• Reconfigurable logic
• Streaming memory
• Context switching

A novel architecture to accelerate a neocortex inspired cognitive model is presented. The architecture utilizes a collection of context switchable processing elements (PEs). This enables time multiplexing of nodes in the model onto available PEs. A streaming memory system is designed to enable high-throughput computation and efficient use of memory resources. Several scheduling algorithms were examined to efficiently assign network nodes to the PEs. Multiple parallel FPGA-accelerated implementations were evaluated on a Cray XD1. Networks of varying complexity were tested and indicate that hardware acceleration can provide an average throughput gain of 184 times over equivalent parallel software implementations.

• 出版日期2009-3