Deep neural networks have proven to be effective in solving computer vision and natural language processing problems. To fully leverage its power, manually designed network templates, i.e., Residual Networks, are introduced deal with various tasks. These hand-crafted rely on a large number of parameters, which both data-dependent laborious. On the other hand, architectures suitable for specific...

Row Parallel Coarse-Grained Reconfigurable Architecture (RPCGRA) has the advantages of maximum parallelism and programmable flexibility. Designing an efficient algorithm to map diverse applications onto RPCGRA is difficult due a number hardware constraints. To solve this problem, nodes data flow graph must be partitioned scheduled RPCGRA. In paper, we present Depth-First Greedy Mapping (DFGM) t...

Abstract Modern market scenarios are imposing a radical change in the production concept, driving companies’ attention to customer satisfaction through increased product customization and quick response strategies maintain competitiveness. At same time, growing development of Industry 4.0 technologies made possible creation new manufacturing paradigms which an level autonomy is one key concepts...