We present an adaptive dynamic load balancing scheme for 3D texture based sort-last parallel volume rendering on a PC cluster equipped with GPUs. Our scheme exploits not only task parallelism but also data parallelism during rendering by combining the hierarchical data structures (octree and parallel BSP tree) in order to skip empty regions and distribute proper workloads to rendering nodes. Our scheme can also conduct a valid parallel rendering and image compositing in visibility order by employing a 3D clustering algorithm. To alleviate the imbalance when the transfer function is changed, a load rebalancing is inexpensively supported by exchanging only needed data. A detailed performance analysis is provided and scaling characteristics of our scheme are discussed. These show that our scheme can achieve significant performance gains by increasing parallelism and decreasing synchronizing costs compared to the traditional static distribution schemes.

As use of the Internet continues to spread rapidly, Traffic Engineering (TE) is needed to optimize IP network resource utilization. In particular, load balancing with TE can prevent traffic concentration on a single path between ingress and egress routers. To apply TE, we have constructed an MPLS (Multi-Protocol Label Switching) network with TE capability in the JGN (Japan Gigabit Network), and evaluated dynamic load balancing behavior in it from the viewpoint of control stability. We confirmed that with this method, setting appropriate control parameter values enables traffic to be equally distributed over two or more routes in an actual large-scale network. In addition, we verified the method's effectiveness by using a digital cinema application as input traffic.

In this paper, we propose a new job scheduling method for distributed parallel systems that can simultaneously achieve two main goals of the job scheduling in those systems: to minimize the execution time of a parallel job without disturbing the execution of the other jobs. We try to achieve those goals by introducing a new scheduler, called active scheduler, that dynamically controls the priority of parallel programs and balances the workload of host computers depending on the status of the underlying runtime environment. We implemented a prototype system of the scheduler to evaluate its effectiveness. The result of experiments implies that the overhead of introducing the active scheduler is at most 15% of the original execution time, and it is in fact effective to adjust the execution of parallel programs to an actual distributed environment in which many users execute their jobs simultaneously.

A large scale simulation for polymer chains in good solvent is performed. The implementation technique for efficient parallel execution, optimization, and load-balancing are discussed on this practical application. Finally, a simple performance model is proposed.