We have developed a parallel visualization system that allows the user to optimize the parallel processing easily according to the data size and the system environment. This system can be serially processed to small data, can be processed in parallel to big data, and can be processed in batch to huge data which exceeds the total amount of memories. Moreover, in order to carry out parallel optimization according to the characteristic of visualization, the arbitrary parts of visualization processing can be parallelized. As a result of examining using this system, it turned out to big data that sort-last parallel rendering is effective. 26GB data exceeding system capacity was visualized by batch processing divided into 8 times.
