Considering run-time reconfiguration overhead in task graph transformations for dynamically reconfigurable architectures

In modern dynamic FPGA-based platforms where multiple processes may be executing concurrently, partial dynamic reconfiguration (RTR) is a key technique for maximizing application performance under resource constraints. For platforms with column-based partial RTR, we propose a new technique to statically transform linear task graphs (common in image processing applications). In our approach, the granularity of data parallelism for each task is determined while considering the reconfiguration overhead along with architectural constraints imposed by partial RTR. On JPEG applications, our technique can improve the execution time by up to 37% by choosing the right granularity of task parallelism.