基于图形硬件的批量式SOM学习过程  

Learning Process of Batch SOM Based on Graphics Hardware

作　　者：徐志鹏 须文波[1] 

机构地区：[1]江南大学信息工程学院,无锡214036

出　　处：《计算机工程》2005年第17期15-17,共3页Computer Engineering

摘　　要：利用非专业图形卡来实现批量式自组织映射(batch version of the SOM)的学习过程。算法基于OpenGL的扩充规范NV_fragment_program,并使用了最新的浮点缓冲区扩充规范NV_float_buffer,使学习过程达到了与CPU运算一致的精度,并且提高了训练速度,缩短了学习时间。This paper describes the realization of learning process of batch SOMs based on commonly available graphics hardware accelerators. The algorithm is based on the extensions of OpenGL. the fragment shader NV fragment_program. It also adopts the floating point buffer extension （NV_float_buffer） which makes the learning process the same precision as CPU does. Compared with CPU, the learning speed is improved and the learning time is reduced.

关 键 词：BATCH SOM GPU计算 图形硬件 机器学习 

分 类 号：TP399[自动化与计算机技术—计算机应用技术]