Abstract: The way of computing is being changed due to the end of multicore scaling with traditional microprocessor architectures. The issues of the dark silicon, the bandwidth and latency of data movement, a lack of parallelism, and a general-purpose structure make the multicore architectures inefficient in terms of area, energy, and cost, while they still keep supports from users for their software programming model. FPGA-based custom computing has been spotlighted as a promising means to make a breakthrough in computing efficiency. By customizing hardware for the physical constrains and target algorithms, we can provide a solution to achieve efficient computation with FPGAs. However, the customization is simultaneously a big challenge to computational architectures. We have to find the best mix of a static part (hardware) and a dynamic part (controls) with their interfaces specialized for each individual problem. We also need to improve productivity for architectural exploration and hardware design. This talk presents the advantages, issues, and research opportunities of custom computing with its recent topics.