Various projects and products have been built using off-the-shelf field-programmable gate arrays (FPGAs) as computation accelerators for specific tasks. Such systems typically connect one or more FPGAs to the host computer via an I/O bus. Some have shown remarkable speedups, albeit limited to specific application domains.

Many factors limit the general usefulness of such systems. Long reconfiguration times prevent acceleration of applications that spread their time over many different tasks. Low-bandwidth paths for data transfer limit the usefulness of such systems to tasks that have a high compute-to-memory-bandwidth ratio. In addition, standard FPGA tools require hardware design expertise beyond the knowledge of most programmers.

To help investigate the viability of connected FPGA systems, the authors designed their own architecture called Garp and experimented with running applications on it. They are also investigating whether Garp's design enables automatic, fast, effective compilation across a broad range of applications. They present their results in this article.