FCNNLib: An Efficient and Flexible Convolution Algorithm Library on FPGAs

Abstract

Convolutions can be implemented with different algorithms, which are diverse in arithmetic complexity, resource requirement, etc. Multiple algorithms can share the FPGA resources spatially as well as temporally, introducing either reconfiguration overhead or resource underutilization. In this paper, we propose an efficient library FCNNLib to coordinate multiple convolution algorithms on FPGAs. We develop three scheduling techniques: spatial, temporal, and hybrid, which exhibit different trade-offs in latency and throughput. We also expose a set of interfaces to arm the users. Experiments using modern CNNs demonstrate FCNNLib achieves up to 1.315X latency improvement compared with dedicated accelerators and 1.755X energy efficiency improvement compared with cuDNN.