Stream Computing on FPGAs

Field Programmable Gate Arrays (FPGAs) are programmable logic devices used for the implementation of a wide range of digital systems. In recent years, there has been an increasing interest in design methodologies that allow high-level design descriptions to be automatically implemented in FPGAs. This thesis describes the design and implementation of a novel compilation flow that implements circuits in FPGAs from a streaming programming language. The streaming language supported is called FPGA Brook, and is based on the existing Brook and GPU Brook languages, which target streaming multiprocessors and graphics processing units (GPUs), respectively. A streaming language is suitable for targeting FPGAs because it allows system designers to express applications in a way that exposes parallelism, which can then be exploited through parallel hardware implementation. FPGA Brook supports replication, which allows the system designer to trade-off area for performance, by specifying the parts of an application that should be implemented as multiple hardware units operating in parallel, to achieve desired application throughput. Hardware units are interconnected through FIFO buffers, which effectively utilize the small memory modules available in FPGAs. The FPGA Brook design flow uses a source-to-source compiler, and combines it with a commercial behavioural synthesis tool to generate hardware. The source-to-source compiler was developed as a part of this thesis and includes novel algorithms for implementation of complex reductions in FPGAs. The design flow is fully automated and presents a user-interface similar to traditional software compilers. A suite of benchmark applications was developed in FPGA Brook and implemented using our design flow. Experimental results show that applications implemented using our flow achieve much higher throughput than the Nios II soft processor implemented in the same FPGA device. Comparison to the commercial C2H compiler from Altera shows that while simple applications can be effectively implemented using the C2H compiler, complex applications achieve significantly better throughput when implemented by our system. Performance of many applications implemented using our design flow would scale further if a larger FPGA device were used. The thesis demonstrates that using an automated design flow to implement streaming applications in FPGAs is a promising methodology.Ph