GC overhead limit exceeded求助

[u010062710]

Exception in thread "main" java.lang.OutOfMemoryError: GC overhead limit exceeded
	at java.util.HashMap.createEntry(HashMap.java:901)
	at java.util.HashMap.addEntry(HashMap.java:888)
	at java.util.HashMap.put(HashMap.java:509)
	at java.util.HashSet.add(HashSet.java:217)
	at java.util.AbstractCollection.addAll(AbstractCollection.java:342)
	at cn.ac.ict.cluster.LinkCluster.clusterSim(LinkCluster.java:134)
	at cn.ac.ict.cluster.LinkCluster.startAnalysis(LinkCluster.java:84)
	at cn.ac.ict.cluster.LinkCluster.main(LinkCluster.java:144)

报如上错误。就是把大量时间用于GC垃圾回收，却只对2%一下的堆有影响，即大量时间用于垃圾回收，还没有效果。
程序是自己实现的一个聚类算法，计算两个cluster的相似度，现在的思路是通过计算两个cluster合并后外部链接会减少的数目，衡量相似度。在 遍历任意两个簇，找到最像似的两簇合并时，会不断调用clusterSim函数，即不断使用set.addAll()函数，set的add方法是通过HashMap实现的，大量GC操作就是在set.addAll()进行的。
自己大概想明白了报错的原理，但没有任何思路怎样解决，跪求大神相助

private int clusterSim(Cluster A, Cluster B) {
		HashSet<Integer> merge = A.getLink();
		merge.addAll(B.getLink());
		return A.getLink().size() + B.getLink().size() - merge.size();
	}
public ArrayList<Cluster> startAnalysis(double threshold, String toFile) {
		long t1, t2;
		t1 = System.currentTimeMillis();
		System.out.println("开始聚类!");
		ArrayList<Cluster> finalClusters = new ArrayList<Cluster>();

		ArrayList<Cluster> originalClusters = initClusters();
		finalClusters = originalClusters;
		int clusternum = -1;
		double mostsim = threshold;
		while (mostsim >= threshold) {
			if (clusternum == finalClusters.size())
				break;
			clusternum = finalClusters.size();
			mostsim = 0;
			int mergeIndexA = 0;
			int mergeIndexB = 0;

			// 遍历任意两个簇，找到最像似的两簇合并
			for (int i = 0; i < clusternum; i++) {
				for (int j = i+1 ; j < clusternum; j++) {
						Cluster clusterA = finalClusters.get(i);
						Cluster clusterB = finalClusters.get(j);
						int tempDis = this.clusterSim(clusterA, clusterB);
						 System.out.println(i+"/"+j+"tempDis: "+tempDis);
						if (tempDis > mostsim) {
							mostsim = tempDis;
							mergeIndexA = i;
							mergeIndexB = j;
						}
				}
			}

			// 合并簇
			if (mostsim >= threshold){
				finalClusters = mergeCluster(finalClusters, mergeIndexA,
						mergeIndexB);
				System.out.println(clusters.size());
			}

		}
		this.clusters = finalClusters;
		for (Cluster cluster : originalClusters) {
			System.out.println(cluster.toString());
			fileUtil.saveToFile(cluster.toString()+"\n", toFile, true);
		}
		System.out.println("==========================================");
		fileUtil.saveToFile("================================="+"\n\n", toFile, true);

		t2 = System.currentTimeMillis();
		System.out.println("聚类完成，耗时：" + (t2 - t1) / 1000 + "s");

		return finalClusters;
	}