<p> Software Pipelining is a method of instruction scheduling where loops are scheduled more efficiently by executing operations from more than one iteration of the loop in parallel. Finding an optimal software pipelined schedule is NP-complete, but many heuristic algorithms exist. </p> In iteration i, a software pipelined loop will execute, in parallel, "stage" 1 of iteration i, stage 2 of iteration i- 1 and so on until stage k of iteration i-k+l. </p> <p> We present a new approach to software pipelining based on using a hemistic algorithm to explicitly assign each operation to its stage before the actual scheduling. </p> <p> This explicit assignment allows us to implement control flow mechanisms that are hard to implement with traditional methods of software pipelining, which do not give us direct control over what stages instructions are assigned to. </p> / Thesis / Master of Science (MSc)

Since the development of SoC is very fast, how to reduce the power consumption of SoC and improve the performance of SoC has become a very important issue. The power consumption of a system depends upon the hardware and software of a system. To overcome the issue of power consumption, the hardware circuit provides multi-voltage method to reduce task power consumption. On the other hand, the software tool decides the exact voltage for each task to minimize the total power consumption and finds a pipelined schedule of the periodic tasks to enhance the total throughput. In this thesis, a Tabu search is used to solve the voltage mapping and resource mapping problems of multi-voltage systems. This goal of this Tabu search is to find the solution with minimal power consumption for the multi-voltage system under the time constraints and resource constraints at the same time in the multi-voltage system to. Under the throughput constraints we use Tabu search to find solutions including the task¡¦s execution voltage and resource mapping, and then use list pipelined scheduling to schedule task and data communication and check their correctness. This method can reduce total power consumption. Experimental results show that our proposed algorithm can decide the resources mapping and pipeline in seconds, and it can reduce the power consumption efficiently.