Although multi-core processors have become dominant computing units in basic system platforms from laptops to supercomputers, software development for effectively running various multi-threaded applications on multi-cores has not made much progress, and effective solutions are still limited to high performance applications relying on exiting parallel computing technology. In practice, majority multi-threaded applications are highly concurrent programs demanding high throughput, such as concurrent database transactions, massive and independent query requests in Web servers and search engines, and executing many-tasks for scientific applications in a multiprogramming mode. To best utilize the increasingly rich computing and cache resources in multi-core processors (many-cores in the near future) we must address several serious and difficult challenges. First, there are several critical hardware resources for multi-threads to share, such as the last level caches and the memory buses. However, the shared resource management is Largely controlled by hardware. Second, OS scheduler has little knowledge about applications' data demanding and access behavior, making sub-optimal task assignment decisions. Finally, the space allocation for each thread in the shared-cache is demand-based, often causing access conflicts and pollution, significantly degrading overall execution performance.