Partial forwarding is a design method to place forwarding paths on a part of processor pipeline. Hardware cost of processor can be reduced without performance loss by partial forwarding. However, compiler with the instruction scheduler which considers partial forwarding structure of the target processor is required since conventional scheduling algorithm cannot make the most of partial forwarding structure. In this paper, we propose a heuristic instruction scheduling method for processors with partial forwarding structure. The proposed algorithm uses available distance to schedule instructions which are suitable for the target partial forwarding processor. Experimental results show that the proposed method generates near-optimal solutions in practical time and some of the optimized codes for partial forwarding processor run in the shortest time among the target processors. It also shows that the proposed method is superior to hazard detection unit.

This paper studies mapping techniques of multiple applications on embedded many-core SoCs. The mapping techniques proposed in this paper are static which means the mapping is decided at design time. The mapping techniques take into account both inter-application and intra-application parallelism in order to fully utilize the potential parallelism of the many-core architecture. Additionally, the proposed static mapping supports dynamic application switching, which means the applications mapped onto the same cores are switched to each other at runtime. Two approaches are proposed for static mapping: one approach is based on integer linear programming and the other is based on a greedy algorithm. Experimental results show the effectiveness of the proposed techniques.

This paper studies the static mapping of multiple applications on embedded many-core SoCs. The mapping techniques proposed in this paper take into account both inter-application and intra-application parallelism in order to fully utilize the potential parallelism of the many-core architecture. Two approaches are proposed for static mapping: one approach is based on integer linear programming and the other is based on a greedy algorithm. Experiments show the effectiveness of the proposed techniques.