FPGA platforms are widely used for application acceleration. Although a number of high-level design frameworks exist, application and performance portability across different platforms remain challenging. To address the above problem, we propose an API design for high-level development tools to separate platform-dependent code from the remaining application design. Additionally, we propose design guidelines to assist with performance portability. To demonstrate our techniques, a large-scale application, originally developed for an Intel Stratix-V FPGA is ported to several new Xilinx Virtex UltraScale+ systems. The accelerated application, developed in a high-level framework, is rapidly moved onto the new platforms with minimal changes. The original, unmodified kernel code delivers a 1.74x speedup due to increased clock frequency on the new platform. Subsequently, the application is further optimised to make use of the additional resources available on the larger Ultrascale+ FPGAs, guided by a simple analytical performance model. This results in an additional performance increase of up to 7.4x. Using the presented framework, we demonstrate rapid deployment of the same application across a number of different platforms that leverage the same FPGA family but differ in their low-level implementation details and the available peripherals. As a result, the same application code supports five different platforms: Maxeler MAX5C DFE, Amazon EC2 F1, Xilinx Alveo U200, U250 and the original Intel Stratix-V accelerator card, with performance close to what is theoretically achievable for each of these platforms.

Latency - the delay between a user's action and the response to this action - is known to be detrimental to virtual reality. Latency is typically considered to be a discrete value characterising a delay, constant in time and space - but this characterisation is incomplete. Latency changes across the display during scan-out, and how it does so is dependent on the rendering approach used. In this study, we present an ultra-low latency real-time ray-casting renderer for virtual reality, implemented on an FPGA. Our renderer has a latency of ~1 ms from 'tracker to pixel'. Its frameless nature means that the region of the display with the lowest latency immediately follows the scan-beam. This is in contrast to frame-based systems such as those using typical GPUs, for which the latency increases as scan-out proceeds. Using a series of high and low speed videos of our system in use, we confirm its latency of ~1 ms. We examine how the renderer performs when driving a traditional sequential scan-out display on a readily available HMO, the Oculus Rift OK2. We contrast this with an equivalent apparatus built using a GPU. Using captured human head motion and a set of image quality measures, we assess the ability of these systems to faithfully recreate the stimuli of an ideal virtual reality system - one with a zero latency tracker, renderer and display running at 1 kHz. Finally, we examine the results of these quality measures, and how each rendering approach is affected by velocity of movement and display persistence. We find that our system, with a lower average latency, can more faithfully draw what the ideal virtual reality system would. Further, we find that with low display persistence, the sensitivity to velocity of both systems is lowered, but that it is much lower for ours.

Reconfigurable hardware has been used before for low latency image synthesis. These are typically low level implementations with tight vertical integration. For example the apparatus of both Regan et al and Ng et al had the tracker driven by the same device performing the rendering. Reconfigurable hardware combined with the dataflow programming model can make application specific rendering hardware cost effective. Our sprite renderer has comparable scope to both prior examples, but our dataflow graph can be adapted to other use cases with an effort comparable to GPU shader programming.