A Task-Level Ooo Framework For Heterogeneous Systems

This paper proposes a framework targeting the problem of task-level out-of-order (OoO) execution for heterogeneous systems. The framework consists of three layers: 1) Programming model; 2) OoO task scheduler; 3) Processing Elements. In order to uncover task-level parallelism automatically, renaming scheme is applied from instruction-level parallelism (ILP) to task-level parallelism (TLP). With the help of renaming scheme, inter-task data dependencies can be detected automatically during execution, and then task-level WAW and WAR dependencies can be eliminated dynamically. We applied Tomasulo algorithm from ILP to perform task-level OoO execution, and implemented a prototype on a state-of-art reconfigurable FPGA platform. Experimental results show that the framework is efficient for heterogeneous systems.