Deep Machine Learning and Signal Processing by NVIDIA and Deepwave Digital

John Ferguson (Deepwave Digital) and Adam Thompson (NVIDIA) present at the GNU Radio Conference where they discussed MatX, Radio-ASR, heterogeneous computing for systems and signals. Title: The Role of GPUs in Modern Software Defined Radio Abstract Applications like machine learning, deep learning, and the promise of high-performance compute abstracted from highly programmable software APIs are driving future requirements for Software Defined Radios; these challenges cannot be met by CPUs or FPGAs alone. While Graphics Processing Units (GPUs) provide an attractive alternative, they require a unique perspective on SDR architecture to best make use of their capabilities and overcome their limitations. This talk will delve into the architecture tradeoffs best suited to meet these new challenges. Tradeoffs between FPGA, CPU, and GPU technologies, and their associated software stack, community of support, and hardware limitations, will be described. We suggest that the optimal architecture is a smaller FPGA wit