Exploiting processing locality through paging configurations in multitasked reconfigurable systems

FPGA chips in reconfigurable computer systems are used as malleable coprocessors where components of a hardware library of functions can be configured as needed. As the number of hardware functions to be configured typically exceeds the underlying chip area during the execution of an application, previous efforts have introduced configuration caching. Those efforts, however, have focused on two run-time-reconfiguration scenarios, which consider a single application running on the reconfigurable system. In the full reconfiguration scenario, functions of an application are arranged into blocks each of which has enough functions to fill the entire chip. The blocks are configured in a deterministic sequence needed by the application based on the a priori knowledge about the application. In the partial reconfiguration scenario, each function is configured or replaced on a function-by-function basis, based on the application needs. In the former technique, spatial processing locality is well exploited. In the latter, only temporal processing locality is exploited. In this work, we propose a technique suitable for multitasking and for cases of single applications that can change the course of processing in a non-deterministic fashion based on data. In order to exploit processing locality, both spatial and temporal simultaneously, the proposed model groups hardware functions into hardware configuration blocks (pages) of fixed size, where multiple pages can be configured on a chip simultaneously. By grouping only related functions that are typically requested together, processing spatial locality can be exploited. Temporal locality is exploited through page replacement techniques. Data mining techniques were used to group related functions into pages. Standard, replacement algorithms as those found in caching were considered. Simulations, as well as emulation using the Cray XD1 reconfigurable high-performance computer were used in the experimental study. The results show a significant improvement in performance using the proposed paging technique.