Evaluating GPP Predictors for Software Based Waveform Performance

  • William “BJ” Blair ANDRO Computational Solutions
  • Ashwin Amanna ANDRO Computational Solutions
  • Timothy Reichert ANDRO Computational Solutions
  • Michael Gudaitis Air Force Research Laboratory


Making full use of a computer’s capabilities today is a challenging task due to increased hardware and software complexity, requiring the use of multithreading, SIMD intrinsics, and overclocking to squeeze as much performance out of a system as possible. A challenge is predicting how a software-based waveforms will perform based on published benchmarks on a general purpose processor (GPP) of interest and where the key limiters exist. This is valuable insight to determine implementation and optimization strategies for software-based waveforms. This paper attempts to identify key indicators of modern GPP performance for usage with waveform software, using LDPC and DVB-S2 waveform benchmarks on two consumer grade desktops. We find a correlation in software performance between GPP or memory reliance and GPP clock speed and cache, as well as the importance of system tuning and overclocking.

How to Cite
BLAIR, William “BJ” et al. Evaluating GPP Predictors for Software Based Waveform Performance. Proceedings of the GNU Radio Conference, [S.l.], v. 8, n. 1, sep. 2023. Available at: <https://pubs.gnuradio.org/index.php/grcon/article/view/135>. Date accessed: 23 sep. 2023.