Основні поняття
Efficiently implementing real-time arbitrary waveform generation using GPUs for various applications.
Анотація
The content discusses the implementation of an Arbitrary Waveform Generation (AWG) framework using GPUs and DAC cards for fast waveform synthesis. It covers the theory, hardware implementation, software implementation, performance evaluation, and future outlook.
I. Introduction to AWG:
- Importance of real-time AWG in various applications.
- Challenges with traditional FPGA-based systems.
II. Theory of Operation:
- Formulation of arbitrary waveform generation using Fourier transform.
- Implementation of amplitude-weighted linear combination for waveform synthesis.
III. Hardware Implementation:
- Utilization of NVIDIA Quadro RTX 6000 GPU and M4i.6622-x8 DAC card for waveform generation.
IV. Software Implementation:
- Description of CUDA kernel functions for waveform synthesis pathways.
V. Performance Evaluation:
- Comparison between GPU and CPU computation times for static AWG pathway.
- Modeling the maximum number of tones that can be streamed in the dynamic pathway.
VI. Summary and Outlook:
- Conclusion on efficient real-time arbitrary waveform generation using GPUs.
- Suggestions for future improvements like multi-GPU setups and high-speed digitizers.
Статистика
The GPU accelerates data parallel additive waveform synthesis framework for AWG at a sampling rate of 560 MB/s.
Two pathways are presented: one offers chirping of 1000 individual tones at 35 ms, the other allows chirping of 194 tones at 100 MB/s or 20 tones at 560 MB/s.
Цитати
"We cast the additive synthesis framework as massively or 'embarrassingly' data parallel and execute it efficiently on a GPU."
"Our code is portable, easy to modify, and can be found here: https://github.com/JQIamo/AWG-on-GPU.git."