Parallel shear-warp factorization on THPCS

Several approaches have been proposed to visualize 3D volume data on multiprocessor systems in recent years. Most of these algorithms are tailored for special architectures and hard to immigrate to new architectures, such as the Tsinghua High-Performance Cluster System (THPCS). In this paper, a parallel volume rendering algorithm is presented for THPCS. To reduce the communication cost and the complexity of blending local intermediate images, a static subtask distribution strategy is proposed. Combined with a prediction for the subtask load and node performance, our strategy yields a perfect load balance. An asynchronous binary compositing method is adopted to provide flexibility for our algorithm. The experimental results demonstrate the efficiency and practicality of our algorithm. As a result, THPCS using our algorithm achieves performance of rendering 512/sup 2/ color images for 128/sup 2//spl times/197 volume within 1 second.