High-performance hardware accelerators for sorting and managing priorities

The paper describes the hardware implementation and optimization of algorithms that process tree-like data structures which are needed for numerous practical applications in such areas as databases, embedded systems, and networks requiring priority management. The emphasis is done on applications that involve fast processing of new incoming data items, such as resorting. Parallelism is achieved by constructing N binary trees (N>;1) and applying concurrent operations to N trees at the same time with the aid of N communicating processing modules. It is shown that the considered technique can efficiently be combined with sorting networks, which gives new potentialities for optimization. Modeling in software, experiments with FPGA-based circuits on different computing platforms, and comparisons with the other known methods demonstrate that the performance is increased significantly. It is also shown that the proposed algorithms are easily scalable.