دورية أكاديمية

A Practically Applicable Performance Prediction Model Based on Capabilities of Texture Mapping Units for Mobile GPUs

التفاصيل البيبلوغرافية
العنوان: A Practically Applicable Performance Prediction Model Based on Capabilities of Texture Mapping Units for Mobile GPUs
المؤلفون: Juwon Yun, Jinyoung Lee, Cheong Ghil Kim, Yeongkyu Lim, Jae-Ho Nah, Youngsik Kim, Woo-Chan Park
المصدر: IEEE Access, Vol 7, Pp 102975-102984 (2019)
بيانات النشر: IEEE, 2019.
سنة النشر: 2019
المجموعة: LCC:Electrical engineering. Electronics. Nuclear engineering
مصطلحات موضوعية: Computer graphics, dynamic voltage scaling, performance analysis, performance evaluation, prediction method, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
الوصف: The power consumption models of mobile application processors have emerged as key objects of interest following the tremendous growth in mobile device production given that such consumption is an important factor in the graphics performance of mobile technologies. Conventionally, the performance of the graphics processing units (GPUs) depends critically on texture mapping units, which is why the number of such GPU components and texture fill rates value prominently whenever the GPU performance is evaluated. Our previous work has established a model to predict maximum performance based on unified shaders. By extending the work, this paper developed a practically applicable GPU performance prediction model on the basis of texture mapping performance. The effects of increased texture mapping units on unified shader performance and GPU efficiency were examined, and a performance prediction model based on the number of frames per second (FPS) was constructed. For these purposes, a benchmark related to texture mapping units was formulated and the experiments were conducted to determine utilization factors that are relevant to GPU performance and efficiency. The final stage in model construction involved establishing a relationship between the previously investigated utilization factors and relevant resources that are consumed during graphics processing. The experimental results showed that the proposed prediction model produced an average error rate of 5.77%.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2169-3536
Relation: https://ieeexplore.ieee.org/document/8777105/; https://doaj.org/toc/2169-3536
DOI: 10.1109/ACCESS.2019.2931290
URL الوصول: https://doaj.org/article/ef5f200d30b24cacae5c6eea58da6acf
رقم الأكسشن: edsdoj.f5f200d30b24cacae5c6eea58da6acf
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:21693536
DOI:10.1109/ACCESS.2019.2931290