cuROB

cuROB是由北京大学电子工程与计算机科学学院的丁科和谭英开发的基于CUDA的实参数优化基准。该数据集包含多种属性的测试函数，并利用CUDA实现高效执行，旨在评估和比较GPU和CPU上的优化算法性能。cuROB支持可扩展的维度，适用于不同复杂度的算法测试，并覆盖了多种属性的函数，以进行系统性的优化算法评估。数据集的应用领域主要集中在优化算法的性能评估和比较，特别是在GPU加速的优化算法研究中。

cuROB is a CUDA-based real-parameter optimization benchmark developed by Ke Ding and Ying Tan from the School of Electronic Engineering and Computer Science, Peking University. This dataset encompasses test functions with diverse characteristics, leverages CUDA for high-efficiency execution, and aims to evaluate and compare the performance of optimization algorithms on both GPUs and CPUs. cuROB supports scalable dimensionality, making it suitable for testing algorithms across varying complexity levels, and covers functions with varied attributes to enable systematic assessment of optimization algorithms. The main application scenarios of this dataset focus on performance evaluation and comparison of optimization algorithms, particularly in the research of GPU-accelerated optimization algorithms.