  The decoding performance of polar codes strongly depends on the decoding
algorithm used, while also the decoder throughput and its latency mainly depend
on the decoding algorithm. In this work, we implement the powerful successive
cancellation list (SCL) decoder on a GPU and identify the bottlenecks of this
algorithm with respect to parallel computing and its difficulties. The inherent
serial decoding property of the SCL algorithm naturally limits the achievable
speed-up gains on GPUs when compared to CPU implementations. In order to
increase the decoding throughput, we use a hybrid decoding scheme based on the
belief propagation (BP) decoder, which can be intra and inter-frame
parallelized. The proposed scheme combines excellent decoding performance and
high throughput within the signal-to-noise ratio (SNR) region of interest.
