【调研】GPU矩阵乘法的性能预测——Machine Learning Approach for Predicting The Performance of SpMV on GPU 目录 01 研究背景 02 技术背景 03 实验方法 04 工作启迪 附录GPU底层结构与执行流程 不管是解方程还是机器学习,最后在数值上,都是矩阵的计算。 对于非常大的矩阵,需要消耗大量的内存,并且拖慢计算速度。
We applied machine learning methods to predict the relationship between the yield stress and the stacking fault energies landscape in high entropy alloys. The data for learning in this work was taken from phase-field dislocation dynamics simulations of partial dislocations in FCC metals [1]. This ...
Evaluation of machine learning models for predicting TiO2 photocatalytic degradation of air contaminants Article Open access 13 June 2024 Introduction As a highly toxic material, arsenic is distributed all over environmental waters. Arsenic can be produced naturally through biological activity and earth cr...
To predict STB we used a random forests model, which is a non-parametric ensemble machine learning method applicable for both classification and regression prediction26. This technique is broadly used due to its high performance and robustness, and because it enables the use of variables independentl...
Understand the limits and risks inherent in applying machine learning and predictive analytics Obtain a robust knowledge of the business challenges and strategic rewards of Predictive Analytics and Machine Leaning initiatives Be conversant in real world case studies, and the reasons for both their success...
3. Machine learning approaches for predicting self-healing efficiency Regression and classification are well-known machine learning approaches [27]. In this section we will briefly introduce our ideas to use regression and classification for the prediction of SHE. 3.1. Regression for prediction Regressio...
Nowadays, recognizing and predicting students learning achievement introduces a significant challenge, especially in blended learning environments, where online (web-based electronic interaction) and offline (direct face-to-face interaction in classrooms) learning are combined. This paper presents a Machine ...
To investigate the effect of machine learning methods on predicting the Overall Survival (OS) for non-small cell lung cancer based on radiomics features analysis. A total of 339 radiomic features were extracted from the segmented tumor volumes of pretrea
The advances in the machine learning approach help overcome the challenges of predicting current traditional thermal indices in a real-time environment. The ... TMS Kumar,CP Kurian - 《Journal of Ambient Intelligence & Humanized Computing》 被引量: 0发表: 2023年 Suitability of different comfort in...
Table 3 Net Reclassification Indices (NRIs) for machine learning models compared to original models. Full size table Discussion Using a Japanese multicenter PCI registry that was constructed in-sync with NCDR, we demonstrated: (1) The original NCDR CathPCI risk scores for predicting the incidence ...