Shodor

tation in education through disseminating unique uses of computation in the classroom as well as research findings in computational science education, with submissions from both professionals and students. JOCSE utilizes internet technology and a web-based format to allow for enhanced interactivity in all publications.

ccount the effect of antibiotics and immunity of the person. We use discrete dynamical systems or difference equations to model the situation; and Excel to obtain the numerical solutions and visualize the solution using graphing capabilities of Excel.

s has been a challenge for the computational science education community. Scaling successful local efforts has been particularly difficult. In this article we describe how a training model from one place and time can be translated into a training model for another very different place and time if critical factors such as school system culture, professional development organization, local learning standards and goals, and collaboration between STEM disciplines are taken into account.

d a computational science module, "Living Links: Applications of Matrix Operations to Population Studies," which introduces matrix operations using applications to population studies and provides accompanying programs in a variety of systems (C/MPI, MATLAB, Mathematica). The module provides a foundation for the use of matrix operations that are essential to modeling numerous computational science applications from population studies to social networks. This paper describes the module; details experiences using the material in two undergraduate courses (High Performance Computing and Linear Algebra) in 2010 and 2011 at Wofford College and two workshops for Ph.D. students at Monash University in Melbourne, Australia, in 2011; and describes refinements to the module based on suggestions in student and instructor evaluations.

used by many computational geophysicists to study the Earth's interior. In order to allow faster experiments and greater simulation capability, there is a push to increase the performance of the code to allow more computations to complete in the same amount of time. To accomplish this we leverage the massively parallel capabilities of graphics processors (GPUs), specifically those using NVIDIA's CUDA framework. We translated existing functions to run in parallel on the GPU, starting with the functions where the most computing time is spent. Running on NVIDIA Tesla GPUs, initial results show an average speedup of 1.8 that stays constant with increasing problem sizes and scales with increasing numbers of MPI processes. As more of the CitcomS code is successfully translated to CUDA, and as newer general purpose GPU frameworks like Fermi are released, we should continue to see further speedups in the future.

e in the lifecycle of the virus, specifically in the maturation of new viral particles. Therefore, delaying the onset of AIDS, the primary goal of HIV treatment, can be achieved by inhibiting this protease.[1] However, the rapidly mutating virus quickly develops drug resistance to current inhibitors, thus novel protease inhibitors are needed. Here, 100ns molecular dynamics (MD) simulations were done for the wild type and two mutant proteases to gain insight into the mechanisms by which the mutations confer drug resistance. Several different metrics were used to search for differences between the wild type and mutant proteases including: flap tip distance and root-mean-square deviation (RMSD), mutual information, and Kullback-Leibler divergence. Finally, it is found at the 100ns timescale there are not large differences in the structure, flexibility and motions of the wild type protease relative to the mutants, and longer simulations may be needed to identify how the structural changes imparted by the mutations affect the protease's functionality.