Novel technique for parallel computations using associative dataflow processor

The prevalent concepts of control-flow and data-flow to build computers have their limitations and weaknesses in exploiting parallelism to the utmost limit. Hence, this paper presents a novel technique to handle parallel computations, called associative dataflow. This approach eliminates the major bottleneck in dataflow architectures concerning the matching of tokens and enhancement of their performance. Preliminary results have indicated faster execution speed and higher ALU utilization for the proposed model compared to conventional dataflow model. These results forecast a promising future for associative dataflow model of computations.