Stencil computation is widely used in scientific computations and many accelerators based on multicore CPUs and GPUs have been proposed. Stencil computation has a small operational intensity so that a large external memory bandwidth is usually required for high performance. FPGAs have the potential to solve this problem by utilizing large internal memory efficiently. However, a very large design, testing and debugging time is required to implement an FPGA architecture successfully. To solve this problem, we propose an FPGA-platform using C-like programming language called open computing language (OpenCL). We also propose an optimization methodology to find the optimal architecture for a given application using the proposed FPFA-platform. According to the experimental results, we achieved 119 - 237 Gflop/s of processing power and higher processing speed compared to conventional GPU and multicore CPU implementations.

Heterogeneous multi-core architecture with CPUs and accelerators attract many attentions since they can achieve power-efficient computing in various areas from low-power embedded processing to high-performance computing. Since the optimal architecture is different from application to applications, it is important to explore suitable architectures for different applications. In this paper, we propose an FPGA-based heterogeneous multi-core platform with custom accelerators for power-efficient computing. Our platform allows to select the most suitable accelerator according to the requirements of an application. Moreover, we optimize the number of ALUs, memory and interconnection network of the selected accelerators to increase the performance and to reduce the power consumption. Experimental results with simple media processing applications times power-efficient compared to the GPU.