In order to comprehend their significant influence on programming difficulties and efficiency gains, the study investigates the application of AI techniques in algorithm optimization and design frameworks. Using the GPU Benchmarks Compilation dataset, this study examines GPU performance and evaluates its effects on the functioning of AI-based algorithms. In addition to changing sectors, this shift is completely changing how companies run, interact with clients, and make strategic choices. GPU performance in AI-based algorithm optimization using a standardized method. The first step in the research process is gathering survey data that correctly reflects real-world application domains where AI algorithms require improvement. Strong foundations for examining AI-driven computing advancements are established by the dataset's comprehensive benchmarking information for GPUs, which includes computational throughput along with cost performance ratios and energy efficiency measurements. This study revealed significant advancements in GPU capabilities that show why GPUs are still crucial for processing sophisticated AI processing models.
Kumar et al. (2025) studied this question.