一种自适应的基于预测的I／O性能优化方法

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。

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

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.