Parallelizing Digital Signal Processing for GPU

• Main Authors: Ekstam Ljusegren, Hannes, Jonsson, Hannes
• Format: Others
• Language: English
• Published: Linköpings universitet, Programvara och system 2020
• Subjects: GPU; Signal Processing; Pulse detection; CPU; CUDA; Jetson; NVIDIA; Parallelize; Digital Processing; Computer Engineering; Datorteknik
• Online Access: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-167189

Because of the increasing importance of signal processing in today's society, there is a need to easily experiment with new ways to process signals. Usually, fast-performing digital signal processing is done with special-purpose hardware that are difficult to develop for. GPUs pose an alternative for fast performing digital signal processing. The work in this thesis is an analysis and implementation of a GPU version of a digital signal processing chain provided by SAAB. Through an iterative process of development and testing, a final implementation was achieved. Two benchmarks, both comprised of 4.2 M test samples, were made to compare the CPU implementation with the GPU implementation. The benchmark was run on three different platforms: a desktop computer, a NVIDIA Jetson AGX Xavier and a NVIDIA Jetson TX2. The results show that the parallelized version can reach several magnitudes higher throughput than the CPU implementation.