Data search and reorganization using FPGAs: application to spatial pointer-based data structures

FPGAs (field programmable gate arrays) have appealing features such as customizable internal and external bandwidth and the ability to exploit vast amounts of fine-grain parallelism. In this paper, we explore the applicability of these features in using FPGAs as smart memory engines for search and reorganization computations over spatial pointer-based data structures. The experimental results in this paper suggests that reconfigurable logic, when combined with the data reorganization, can lead to dramatic performance improvements of up to 20x over traditional computer architectures for pointer-based computations, traditionally not viewed as a good match for reconfigurable technologies.