中文摘要：

以原库与压缩库的性能相似度为出发点,提出了一种buffer库压缩算法,并建立了虚单元、实单元和概率加权距离的概念.用环境参数对原库进行筛选,其结果构成虚单元库;对虚单元进行聚类,将中心点映射到实单元得到压缩库.将单元对环境的适应性量化,作为先验知识,为聚类中心的选择提供优先级.采用3种方案实现该算法思想,经实验证明,所得压缩库与原库的性能相似度高,误差平方和（SSE）仅为已有算法的9.6%、10.4%和6%.

英文摘要：

Taking performance similarity as a point of departure,this paper proposes an algorithm for buffer library compression.Concepts of virtual cell,real cell and probability weighted distance are established.Buffers with best performance under certain environment points are identified as cells of virtual library.Virtual cells are clustered in the second step.Center of each cluster is finally mapped to compressed library.Environmental adaptability of each buffer is quantized to give priority to cluster center identification.Above idea is achieved by using three programs.Result shows that three implementations achieve 9.6%,10.4% and 6% of SSE respectively compared with existed algorithm,which represents better performance similarities between compressed library and the unpruned one.