Field-Programmable Gate Arrays (FPGAs) systems now comprise many processing elements that are processors running software and hardware engines used to accelerate specific functions. To make the programming of such a system simpler, it is easiest to think of a shared-memory environment, much like in current multi-core processor systems. This thesis introduces a novel, shared-memory, cache-coherent infrastructure for heterogeneous systems implemented on FPGAs that can then form the basis of a shared-memory programming model for heterogeneous systems. With simulation results, it is shown that the cache-coherent infrastructure outperforms the infrastructure of Woods [1] with a speedup of 1.10. The thesis explores the various configurations of the cache interconnection network and the benefit of the cache-to-cache cache line data transfer with its impact on main memory access. Finally, the thesis shows the cache-coherent infrastructure has very little overhead when using its cache coherence implementation.

Field-Programmable Gate Arrays (FPGAs) systems now comprise many processing elements that are processors running software and hardware engines used to accelerate specific functions. To make the programming of such a system simpler, it is easiest to think of a shared-memory environment, much like in current multi-core processor systems. This thesis introduces a novel, shared-memory, cache-coherent infrastructure for heterogeneous systems implemented on FPGAs that can then form the basis of a shared-memory programming model for heterogeneous systems. With simulation results, it is shown that the cache-coherent infrastructure outperforms the infrastructure of Woods [1] with a speedup of 1.10. The thesis explores the various configurations of the cache interconnection network and the benefit of the cache-to-cache cache line data transfer with its impact on main memory access. Finally, the thesis shows the cache-coherent infrastructure has very little overhead when using its cache coherence implementation.