Grant: Research Tools and Instruments

The Roussel and Wetmore labs at the University of Lethbridge are leaders in studying biochemical systems using computational and mathematical methods. The problems our teams study range in spatial scale from the molecular to the organ level, and in time scale from femtoseconds to weeks. Techniques used derive from computational chemistry, nonlinear dynamics and stochastic kinetics. Problems studied include the mutagenicity of pollutants, nucleic acid-protein interactions, the role of biochemical network structure in cell fate determination, and the effects of gene expression delays in biochemical dynamics. Internationally competitive computational biochemistry labs require high-end computers to efficiently conduct simulations, analyses and visualization, as well as preparation of jobs for Compute/Calcul Canada (CCC) high-performance systems. Cutting-edge desktop computers maximize throughput and alleviate the pressure on CCC facilities, which can then be reserved for the most demanding jobs. In particular, smaller calculations as well as testing and optimization of larger jobs can be carried out locally, avoiding waste of CCC CPU and, especially, GPU cycles. Our computational biochemistry facilities, located in the state-of-the-art Science Commons complex, are designed to maximize trainee-supervisor and trainee-trainee interactions, with faculty offices directly adjacent to our labs, accelerating research and resulting in high occupancy of the labs during the day. Desk computers cannot be shared given that students are working in the lab every day. Equity in computational science requires ready access to high-end computing, which the requested equipment will ensure.  Different high-end workstation configurations are needed for the variety of tasks carried out. For instance, AMBER (molecular dynamics simulations) runs about 500 times faster on GPUs than on CPU-only machines; graph algorithms in Python scale almost linearly with the number of CPU cores; and both of these as well as Maple symbolic algebra computations (not available on CCC hardware) often require large memory spaces. The Roussel and Wetmore labs currently house computers of different vintages, roughly half of which are 8-10 years old. Both hardware failures and obsolescence, which hinders equitable access to updated software, are eroding our ability to advance our research programs and provide student training. Maintaining world-class competitiveness and training capacity in our labs requires the urgent replacement of more computers than can realistically be purchased with operating grants. Funding is therefore requested to replace 14 of 27 workstations in our computational labs by modern workstations with high-end capabilities. Since current local storage is inadequate to handle the larger data sets we now routinely generate, we are requesting a complementary disk array to enable post-processing and visualization while minimizing time-consuming transfers to and from CCC arrays.