New algorithms that work entirely on sparse grids can create data sets that cannot be handled on uniform grids any more due to their size. On the other hand, most visualization techniques are only capable of handling uniform grids. As the interpolation on sparse grids is a complicated and time consuming process, direct volume visualization is unthinkable for bigger data sets until the underlying interpolation is accelerated by some orders of magnitude.

On the other hand, quite a number of super computers and PC clusters exist nowadays, providing MPI as the primary communication API. By streaming the data sets and the resulting images from and to the end user's workstation, their processing power can be utilized without leaving the office.

Parallelizing visualization techniques rises the necessity to balance the computational load, and for time consuming rendering methods previews are useful for the user. Both, generating preview images and load balancing, is performed explicitly in most cases. In this case study, we approach these problems by applying a special pixel rendering sequence, which achieves superb results implicitly without generating communication overhead.