一种自适应的基于预测的I/O性能优化方法

A Self-adaptive and Prediction-based I/O Performance Optimization Method

目前计算机的I/O性能已经成为严重制约计算机整体性能提升的瓶颈。在现有技术条件下,I/O性能的优化方法对于提升I/O性能显得尤为重要。本文提出了一种自适应的基于预测的I/O性能的优化方法,该方法采用了基于预测的数据预读策略,改进I/O读操作的响应速度;采用基于预测的缓存分配策略,改进了I/O写操作的响应速度,从而在整体上提高了计算机系统的I/O性能。从实验测试的结果可以看出,这种方法适用于多种不同的负载类型,能够大幅度提升计算机的I/O性能,是一种通用的、效果显著的I/O性能优化方法。

I/O performance has already become the bottleneck of the total performance of computer systems for a long time. And under the condition of the present computer technology, I/O performance optimization method looks especially important for I/O performance. A self-adaptive and prediction-based I/O performance optimization method is proposed in this paper. The method uses prediction-based prefetching to improve the performance of read operation and uses prediction-based buffer allocation to improve the performance of write operation, so the I/O subsystem performance is enhanced totally. The results of testing experiments show that this method is universal and obviously effective to different kinds of I/O workloads.