2017

• Z. Di, Chen, S., Hong, Y., Jacobsen, C., Leyffer, S., and Wild, S. M., “Joint Reconstruction of X-Ray Fluorescence and Transmission Tomography”, Optics Express, vol. 25, no. 12, pp. 13107-13124, 2017.
• M. Mubarak and Ross, R. B., “Validation Study of CODES Dragonfly Network Model with Theta Cray XC System”, 2017.
• K. Xu, Austin, A. P., and Wei, K., “A Fast Algorithm for the Convolution of Functions with Compact Support Using Fourier Extensions”, 2017.
• A. Walther and Narayanan, S. H. K., “Extending the Binomial Checkpointing Technique for Resilience”, 2017.
• H. Guo, Peterka, T., and Glatz, A., “In Situ Magnetic Flux Vortex Visualization in Time-Dependent Ginzburg-Landau Superconductor Simulations”, 2017.
• P. K. Romano and Siegel, A. R., “Limits on the Efficiency of Event-Based Algorithms for Monte Carlo Neutron Transport”, 2017.
• M. Si and Balaji, P., “Process-Based Asynchronous Progress Model for MPI Point-to-Point Communication”, 2017.
• N. Neveu, Larson, J., Power, J. G., and Spentzouris, L., “Photoinjector Optimization Using a Derivative-Free, Model-Based Trust-Region Algorithm for the Argonne Wakefield Accelerator”, 2017.
• E. Deelman, Peterka, T., Altintas, I., Carothers, C. D., Dam, K. K. V., Moreland, K., Parashar, M., Ramakrishnan, L., Taufer, M., and Vetter, J., “The Future of Scientific Workflows”, The International Journal of High Performance Computing Applications, p. 1094342017704893, 2017.
• K. Kim, Botterud, A., and Qiu, F., “Temporal Decomposition for Improved Unit Commitment in Power System Production Cost Modeling”, 2017.
• C. A. L. Haley and Anitescu, M., “Optimal Bandwidth for Multitaper Spectrum Estimation”, 2017.
• M. R. Norman, Mametjanov, A., and Taylor, M., “Exascale Programming Approaches for the Accelerated Model for Climate and Energy”, 2017.
• “Visual Analytics Techniques for Exploring the Design Space of Large-Scale High-Radix Networks”, 2017.
• M. Hereld and Kim, K., “Disaster = Infrastructure + Hazard”, 2017.
• A. P. Austin and Trefethen, L. N., “Trigonometric Interpolation and Quadrature in Perturbed Points”, 2017.
• K. Kulshreshtha, Narayanan, S. H. K., Bessac, J., and MacIntyre, K., “Efficient Computation of Derivatives for Solving Optimization Problems in R and Python using SWIG-Generated Interfaces to ADOL-C”, 2017.
• S. Madireddy, Balaprakash, P., Carns, P. H., Latham, R., Ross, R., Snyder, S., and Wild, S. M., “Analysis and Correlation of Application I/O Performance and System-Wide I/O Activity”, 2017.
• V. Makarashvili, Merzari, E., Obabko, A. V., Fischer, P., and Siegel, A., “Accelerating The High-Fidelity Simulation of Turbulance: Ensemble Averaging”, in ASME 2016 Fluids Engineering Division Summer Meeting, 2017.
• M. Mubarak, Jain, N., Domke, J., Wolfe, N., Ross, C., Li, K., Bhatele, A., Carothers, C. D., Ma, K. - L., and Ross, R. B., “Toward Reliable Validation of HPC Network Simulation Models”, 2017.
• C. D. Carothers, Vetter, J., Meredith, J. S., Mubarak, M., Moore, S., Blanco, M. P., and LaPre, J., “Durango: Scalable Synthetic Workload Generation for Extreme-Scale Application Performance Modeling and Simulation”, in SIGSIM-PADS '17, Singapore, 2017.