Ever greater amounts of computing and storage are happening remotely in the cloud, and it is estimated that spending on public cloud services will grow by over 19%/year to $140B in 2019. Besides commodity processors, network and storage infrastructure, the end of clock frequency scaling in traditional processors has meant that application-specific accelerators are required in tandem with cloud-based processors to deliver continued improvements in computational performance and energy efficiency. Indeed, graphics processing units (GPUs), as well as custom ASICs, are now widely used within the cloud, particularly for compute-intensive high-value applications like machine learning. In this panel, we intend to consider the opportunities and challenges for broad deployment of FPGAs in the cloud.