Semester of Graduation
Fall 2024
Degree
Master of Science (MS)
Department
Computer Science and Engineering
Document Type
Thesis
Abstract
The exponential growth in computational power and the increasing demand for high-performance applications have driven the need for greater parallel efficiency. Over the years, the number of cores in consumer-level CPUs and high-performance computing (HPC) systems has grown significantly. In response, numerous parallel programming li- braries have been developed. Each of these libraries offers unique mechanisms to enhance parallel performance. In this paper, we investigate the performance of five such paral- lel programming backends: C++ std::execution::par, OpenMP, TBB, Taskflow, and HPX. We evaluate these libraries using two sets of benchmarks. The first set focuses on standard C++ STL algorithms, including for_each, reduce, scan, and sort. The second set involves real-world mini-applications, such as Black-Scholes, Mandelbrot, LULESH, and miniBUDE. Our findings provide insights into how to further optimize HPX algo- rithms and how to fine-tune performance by adopting the best practices from various par- allel backends. This analysis helps us understand the relative performance of HPX among other libraries and suggests areas for future improvement.
Date
10-31-2024
Recommended Citation
Singanaboina, Srinivas Yadav, "Performance Analysis of C++ Parallel Algorithms in HPX" (2024). LSU Master's Theses. 6064.
https://repository.lsu.edu/gradschool_theses/6064
Committee Chair
Kaiser, Hartmut