Towards quantification of the Role of Materials Innovation in overall Technological Development

This report develops a method for quantitatively assessing the role of materials innovation in overall technological development. The report demonstrates the method for one specific case and defines the key requirements to use it in a number of other cases. The new method involves the comparative examination of overall technical capability metrics with performance metrics at more detailed levels of progress where materials and process innovation dominates the progress. This analysis is supplemented by exploration of the specific technical capabilities utilized in technological development areas of interest. It is specifically found that about 2/3 of the total progress in computation over the past 40 years has been due to materials/process innovations. It is also found that making reasonably reliable estimates in other functional areas such as energy storage, information transmission, etc. could be possible if more attention were paid to the development and collection of technical progress metrics at the level of materials and processes (such as Moore’s Law has done for information transformation). Examination of what is known leads to three other key (but more speculative) findings: 1) Materials/process innovation contributes at least 20% of the progress in all areas examined; 2) The contribution of materials/process innovations in energy storage are possibly 80% or higher; 3) The relative contribution of materials/process innovation to overall technological progress has grown in the past few decades

HARDWARE-ACCELERATED AUTOMATIC 3D NONRIGID IMAGE REGISTRATION

Software implementations of 3D nonrigid image registration, an essential tool in medical applications like radiotherapies and image-guided surgeries, run excessively slow on traditional computers. These algorithms can be accelerated using hardware methods by exploiting parallelism at different levels in the algorithm. We present here, an implementation of a free-form deformation-based algorithm on a field programmable gate array (FPGA) with a customized, parallel and pipelined architecture. We overcome the performance bottlenecks and gain speedups of up to 40x over traditional computers while achieving accuracies comparable to software implementations. In this work, we also present a method to optimize the deformation field using a gradient descent-based optimization scheme and solve the problem of mesh folding, commonly encountered during registration using free-form deformations, using a set of linear constraints. Finally, we present the use of novel dataflow modeling tools to automatically map registration algorithms to hardware like FPGAs while allowing for dynamic reconfiguration