Abstract Coupling recent imaging capabilities with microstructural finite element (µFE) analysis offers a powerful tool to determine bone stiffness and strength. It shows high potential to improve the individual fracture risk prediction, a tool much needed in the diagnosis and treatment of osteoporosis, that is, according to the World Health Organization (WHO), second only to cardiovascular disease as a leading health‐care problem. We adapted a multilevel preconditioned conjugate gradient method to solve the very large voxel models that arise in the µFE bone structure analysis. The intricate microstructure properties of bone lead to sparse matrices with billions of rows, thus rendering this application to be an ideal candidate for massively parallel architectures such as the BG/L Supercomputer. In this work we present our progress as well as the challenges we were able to identify in our quest to achieve scalability to thousands of BG/L cores. Copyright © 2010 John Wiley & Sons, Ltd.

We present a novel architecture for hardware-accelerated rendering of point primitives. Our pipeline implements a refined version of EWA splatting, a high quality method for antialiased rendering of point sampled representations. A central feature of our design is the seamless integration of the architecture into conventional, OpenGL-like graphics pipelines so as to complement triangle-based rendering. The specific properties of the EWA algorithm required a variety of novel design concepts including a ternary depth test and using an on-chip pipelined heap data structure for making the memory accesses of splat primitives more coherent. In addition, we developed a computationally stable evaluation scheme for perspectively corrected splats. We implemented our architecture both on reconfigurable FPGA boards and as an ASIC prototype, and we integrated it into an OpenGL-like software implementation. Our evaluation comprises a detailed performance analysis using scenes of varying complexity.