Driven by the demands of scientific computing and big data processing, high performance computers in the world have been more powerful and the system scales have been larger than ever before. However, the power consumption of the whole system is becoming a severe bottleneck in the further improvement of performance. In this paper, after analyzing four types of HPC systems deeply, we propose and study two key technologies which include reconfigurable micro server (RMS) technology and cluster constructing technology with the combination of node autonomy and node cooperation. RMS technology provides a new way to make the performance, the power consumption and the size of computing nodes in balance. By combining the node autonomy and the node cooperation, a large amount of small-sized computing nodes can be aggregated to be a scalable RMS cluster. Based on these technologies, we propose a new high-efficiency multipurpose computing platform architecture called Ant Cluster and construct a prototype system which consists of 2,048 low-power ant-like small-sized computing nodes. On this cluster, we implement two actual applications. The test results show that, for real-time large-scale fingerprint matching, single RMS node can achieve 34 times speed-up compared with single Inter Xeon core and the power consumption is only 5W. The whole prototype system supports processing hundreds of queries on a database of 10 million fingerprints in real time. For data sorting, our prototype system achieves 10 times more performance per watt than GPU platform and obtains higher efficiency.