Remote Large Data Set Visualization

摘要

Simulations run on large parallel systems produce data sets that contain hundreds of megabytes to terabytes of data. The researchers producing these data sets prefer to visualize them using their personal workstations. High-end PC workstations currently have the computation and graphics power to perform these visualizations. However, these workstations do not have sufficient memory to completely load large data sets. This research, which enables the use of personal workstations for visualizing data sets that are too large to be stored on personal workstations, will increase the productivity of researchers who are pushing the limits of simulations by producing very large data sets. Because personal workstations have limited memory, out-of-core visualization techniques must be used. These techniques calculate the visualization with only a fraction of the data set resident in memory. In addition, many data sets are so large that they can only fit on central file servers. Since most file servers do not have significant extra central processing unit (CPU) and memory capacity, remote out-of-core visualization is required. Our earlier research developed an out-of-core visualization technique called application-controlled demand paging. This technique loads the data required by the visualization algorithm from disk into main memory as necessary. The technique works well because most visualization algorithms only use a small fraction of the entire data set. The overall speed typically increases as the user interacts with the data set, since previously loaded data are retained if possible. This means that the overall speed will soon approach the speed that would be seen if the entire data set were loaded into memory.