Optimal task scheduler for multi-core processor

With the advent of multi-core processors, parallel execution of multiple tasks has become a common practice. Various scheduling algorithms have addressed this issue considering multiprocessor systems. Most of these algorithms target application level parallelism. Task level parallelism within an application can be exploited using shared memory architecture such as multi-core processor or in a distributed computing environment. In this paper, we propose a static scheduling algorithm that generates a schedule that can be optimized for one or all parameters including execution time, number of processors, and efficiency of processors. The input to this scheduler is a task dependency matrix is generated using dependency analysis technique. Efficiency of this scheduler is high because it uses multiple parameters such as task wait time, number of tasks whose dependency gets resolved by scheduling a task, and task execution time. The paper concludes with an example of applying this technique to a set of tasks.