Improving the performance of hierarchical scheduling for rendering

Abstract

With the improvement and development of the high performance computing systems, the need arises to use the resources available at hand efficiently. Rendering is one kind of application which is suitable for high computing. In the modern era of computing we have got the quad processors available, but the processes and data we manipulate on these, is still based on the serial algorithms in many of the cases. As rendering needs more computing and is associated with huge data access, it can be broken into the smaller subtasks of same nature to be executed on the different processors. The parallel approach works on the principle of solving or computing the different similar sub-tasks using the different available resources of computing (processors) in a parallel fashion. Means at the end of one unit of time, we are having the result of as much number of subtasks in hand, as the number of processors available. The only thing we need to keep in mind is how to efficiently share the resources between different subtasks and how to balance the load factor as per different processors are considered. In this paper we are proposing a hierarchical scheduling policy for rendering to improve its performance as compared to the present day available methods. We will evaluate the approach with the existing approaches for rendering to show the improvement in performance.

A Statistics Based Prediction Method for Rendering Application

“…The render farm with a pool of finite rendering resources receives the rendering jobs, chooses appropriate resources according to the demands of rendering users and scheduling rendering jobs according to some policies. Generally speaking, the research spot is focus on optimizing and design of scheduling policy [9,26,19]. But many issues are based the on the premise of obtaining the application running time in advance or have not a-priori knowledge on execution time prediction [17], which will negatively impacts the efficiency of scheduling policy, especially for the static policy from the view of system.…”