The Cornell Theory Center (CTC), directed by Thomas Coleman, advances Cornell research by providing researchers with a high-performance computing environment, extensive technical expertise, and support for visualization. CTC resources include a 160-processor IBM RS/6000 POWER parallel System (SP), a 24-node Intel NT cluster, and a virtual reality environment called the Visual Insight Zone.
CTC supports a number of interdisciplinary research projects, several of which apply computer science expertise to problems in other disciplines. For example, sample projects through CTC's Computational Finance Institute include exploring new optimization algorithms for the determination of implied volatility and the solution of the American put pricing model; investigating new computational procedures for American option problems suitable for large-scale problems based on inverse problem formulations and new fast methods for non-negative nonlinear least-squares; developing parallel "scenario optimization" toolkits on top of environments such as MATLAB for multiple processors and applying automatic differentiation technology; and adapting new algorithms suitable for large problems and parallel computing for norm and down-side norm minimization applied to portfolio analysis and value-at-risk calculations.
CTC's Parallel Processing Resource for Biomedical Scientists focuses on pushing algorithm development and software advances to lay the basis for further advances in biomedical science. The Parallel Resource is aimed primarily at the protein folding problem and structure-based drug design, but computer scientists have also worked with imaging problems. Projects have included image segmentation for lung nodule detection; high-resolution and quantitative ultrasonic imaging; rational design of MRI contrast enhancement agents; and the development of a quantitative theory for physical phenomena that affect MRI microscopy and the numerical modeling of these phenomena.
Another interdisciplinary project, Crack Propagation on Teraflop Computers, focuses on the design of algorithms and systems to support the numerical simulation of crack propagation problems. The focus is on 3-dimensional, time-dependent fracture simulations using unstructured, adaptive grids on the SP and on EARTH-MANNA, a machine based on a fine-grain, multi-headed program execution model. The effort involves three major tasks: designing and implementing 3-D adaptive, parallel mesh generators producing meshes of provably good quality; developing and implementing restructuring compiler technology to support the automatic generation of efficient parallel code, starting with equations that arise in the simulation; and evaluating the adequacy of existing thread generation and load balancing mechanisms on the parallel platforms and reimplementing the mechanisms for crack propagation studies on parallel computers.
A new and growing interdisciplinary initiative centers around genomics. Premised on the idea that the ability to interpret genomic data will be the chief enabling technology that will lead to the next major breakthroughs in understanding the relationship between genomic structure and biological function, the Cornell Genomics Initiative has a strong computational genomics and bioinformatics component. For example, one group is trying to see if inexpensive parallelization techniques can be used to increase the speed of ACEDB genome database query responses. ACEDB is the pre-eminent database management system for agricultural, human, and model-biological-system genome projects world-wide.
A number of faculty integrate the use of CTC high-performance computing resources into their courses. In CS, this has occurred in courses such as CS 417/418 (Computer Graphics and a Computer Graphics Lab, which cover the basics of modeling, rendering, and animation), CS 522 (Computational Tools and Methods for Finance), and CS 612 (Software Design for High Performance Architectures).