Advanced Computing,
Mathematics, and Data
Advanced Computing,
Mathematics, and Data
2021
Cupeiro Figueroa, I. Cimmino, M. Drgoňa, J. Helsen, L. (2021). ”Fluid temperature predictions of geothermal borefields using load estimations via state observers”, Journal of Building Performance Simulation, 14 (1), 1-19. DOI: 10.1080/19401493.2020.1838612.
Ghosh, P. Krishnamoorthy, S. Kalyanaraman, A. (2021). ”PaKman: A Scalable Algorithm for Generating Genomic Contigs on Distributed Memory Machines”, IEEE Transactions on Parallel and Distributed Systems, 32 (5), 1191-1209. DOI: 10.1109/TPDS.2020.3043241.
Brabec, J. Brandejs, J. Kowalski, K. Xantheas, S. Legeza, Ö. Veis, L. (2021). ”Massively parallel quantum chemical density matrix renormalization group method”, Journal of Computational Chemistry, 42 (8), 534-544. DOI: 10.1002/jcc.26476.
Chen, Y. Xu, Z. Wang, C. Bao, J. Koeppel, B. Yan, L. Gao, P. Wang, W. (2021). ”Analytical modeling for redox flow battery design”, Journal of Power Sources, 482. DOI: 10.1016/j.jpowsour.2020.228817
Murugesan, V. Nie, Z. Zhang, X. Gao, P. Zhu, Z. Huang, Q. Yan, L. Reed, D. Wang, W. (2021). ”Accelerated design of vanadium redox flow battery electrolytes through tunable solvation chemistry”, Cell Reports Physical Science, 2 (2). DOI: 10.1016/j.xcrp.2021.100323.
Zhang, X. Fu, X. Zhuang, D. Xie, C. Song, S. (2021). ”Enabling Highly Efficient Capsule Networks Processing Through Software-Hardware Co-Design”, IEEE Transactions on Computers, DOI: 10.1109/TC.2021.3056929.
Geng, T. Li, A. Wang, T. Wu, C. Li, Y. Shi, R. Wu, W. Herbordt, M. (2021). ”O3BNN-R: An Out-of-Order Architecture for High-Performance and Regularized BNN Inference”, IEEE Transactions on Parallel and Distributed Systems, 32 (1), 199-213. DOI: 10.1109/TPDS.2020.3013637.
Kharazmi, E. Zhang, Z. Karniadakis, G.E.M. (2021). ”hp-VPINNs: Variational physics-informed neural networks with domain decomposition”, Computer Methods in Applied Mechanics and Engineering, 374. DOI: 10.1016/j.cma.2020.113547.
Kwak, W.-J. Lim, H.-S. Gao, P. Feng, R. Chae, S. Zhong, L. Read, J. Engelhard, M.H. Xu, W. Zhang, J.-G. (2021). ”Effects of Fluorinated Diluents in Localized High-Concentration Electrolytes for Lithium–Oxygen Batteries”, Advanced Functional Materials, 31 (2). DOI: 10.1002/adfm.202002927.
Minutoli, M. Castellana, V.G. Saporetti, N. Devecchi, S. Lattuada, M. Fezzardi, P. Tumeo, A. Ferrandi, F. (2021). ”Svelto: High-Level Synthesis of Multi-Threaded Accelerators for Graph Analytics”, IEEE Transactions on Computers. DOI: 10.1109/TC.2021.3057860.
Wang, T. Li, L. Pallaka, M.R. Das, H. Whalen, S. Soulami, A. Upadhyay, P. Kappagantula, K.S. (2021). ”Mechanical and microstructural characterization of AZ31 magnesium‑carbon fiber reinforced polymer joint obtained by friction stir interlocking technique”, Materials and Design, 198. DOI: 10.1016/j.matdes.2020.109305.
Lu, L. Meng, X. Mao, Z. Karniadakis, G.E. (2021). ”DeepXDE: A deep learning library for solving differential equations”, SIAM Review, 63 (1), 208-228. DOI: 10.1137/19M1274067.
Li, A. Su, S. (2021). ”Accelerating Binarized Neural Networks via Bit-Tensor-Cores in Turing GPUs”, IEEE Transactions on Parallel and Distributed Systems, 32 (7), 1878-1891. DOI: 10.1109/TPDS.2020.3045828.
Cao, X. Gao, P. Ren, X. Zou, L. Engelhard, M.H. Matthews, B.E. Hu, J. Niu, C. Liu, D. Arey, B.W. Wang, C. Xiao, J. Liu, J. Xu, W. Zhang, J.-G. (2021). ”Effects of fluorinated solvents on electrolyte solvation structures and electrode/electrolyte interphases for lithium metal batteries”, Proceedings of the National Academy of Sciences of the United States of America, 118 (9). DOI: 10.1073/pnas.2020357118.
Cromwell, E. Shuai, P. Jiang, P. Coon, E.T. Painter, S.L. Moulton, J.D. Lin, Y. Chen, X. (2021). ”Estimating Watershed Subsurface Permeability From Stream Discharge Data Using Deep Neural Networks”, Frontiers in Earth Science, 9. DOI: 10.3389/feart.2021.613011.
Aksoy, S.G. Bruillard, P. Young, S.J. Raugas, M. (2021). ”Ramanujan graphs and the spectral gap of supercomputing topologies”, Journal of Supercomputing, 77 (2), 1177-1213. DOI: 10.1007/s11227-020-03291-1.
Bauman, N.P. Liu, H. Bylaska, E.J. Krishnamoorthy, S. Low, G.H. Granade, C.E. Wiebe, N. Baker, N.A. Peng, B. Roetteler, M. Troyer, M. Kowalski, K. (2021). ”Toward Quantum Computing for High-Energy Excited States in Molecular Systems: Quantum Phase Estimations of Core-Level States”, Journal of Chemical Theory and Computation, 17 (1), 201-210. DOI: 10.1021/acs.jctc.0c00909.
Tartakovsky, A.M. Barajas-Solano, D.A. He, Q. (2021). ”Physics-informed machine learning with conditional Karhunen-Loève expansions”, Journal of Computational Physics, 426. DOI: 10.1016/j.jcp.2020.109904.
Silva, S.J. Burrows, S.M. Evans, M.J. Halappanavar, M. (2021). ”A Graph Theoretical Intercomparison of Atmospheric Chemical Mechanisms”, Geophysical Research Letters, 48 (1). DOI: 10.1029/2020GL090481.
Childs, A.M. Su, Y. Tran, M.C. Wiebe, N. Zhu, S. (2021). ”Theory of Trotter Error with Commutator Scaling”, Physical Review X, 11 (1). DOI: 10.1103/PhysRevX.11.011020.
Huggins, W.J. McClean, J.R. Rubin, N.C. Jiang, Z. Wiebe, N. Whaley, K.B. Babbush, R. (2021). ”Efficient and noise resilient measurements for quantum chemistry on near-term quantum computers”, npj Quantum Information, 7 (1). DOI: 10.1038/s41534-020-00341-7.
Yang, L. Meng, X. Karniadakis, G.E. (2021). ”B-PINNs: Bayesian physics-informed neural networks for forward and inverse PDE problems with noisy data”, Journal of Computational Physics, 425. DOI: 10.1016/j.jcp.2020.109913.
Hagen, L.H. Brooke, C.G. Shaw, C.A. Norbeck, A.D. Piao, H. Arntzen, M.Ø. Olson, H.M. Copeland, A. Isern, N. Shukla, A. Roux, S. Lombard, V. Henrissat, B. O’Malley, M.A. Grigoriev, I.V. Tringe, S.G. Mackie, R.I. Pasa-Tolic, L. Pope, P.B. Hess, M. (2021). ”Proteome specialization of anaerobic fungi during ruminal degradation of recalcitrant plant fiber”, ISME Journal, 15 (2), 421-434. DOI: 10.1038/s41396-020-00769-x.
Bhuiyan, T.H. Medal, H.R. Nandi, A.K. Halappanavar, M. (2021). ”Risk-averse bi-level stochastic network interdiction model for cyber-security risk management”, International Journal of Critical Infrastructure Protection, 32. DOI: 10.1016/j.ijcip.2021.100408.
2020
Darulová, J. Pauka, S.J. Wiebe, N. Chan, K.W. Gardener, G.C. Manfra, M.J. Cassidy, M.C. Troyer, M. (2020). ”Autonomous Tuning and Charge-State Detection of Gate-Defined Quantum Dots”, Physical Review Applied, 13 (5). DOI: 10.1103/PhysRevApplied.13.054005.
Berry, D.W. Childs, A.M. Su, Y. Wang, X. Wiebe, N. (2020). ”Time-dependent hamiltonian simulation with L1-norm scaling”, Quantum, 4. DOI: 10.22331/q-2020-04-20-254.
Palmer, B.J. Chun, J. Morris, J.F. Mundy, C.J. Schenter, G.K. (2020). ”Correlation function approach for diffusion in confined geometries”, Physical Review E, 102 (2). DOI: 10.1103/PhysRevE.102.022129.
Kwak, W.-J. Chae, S. Feng, R. Gao, P. Read, J. Engelhard, M.H. Zhong, L. Xu, W. Zhang, J.-G. (2020). ”Optimized Electrolyte with High Electrochemical Stability and Oxygen Solubility for Lithium-Oxygen and Lithium-Air Batteries”, ACS Energy Letters, 5 (7), 2182-2190. DOI: 10.1021/acsenergylett.0c00809.
Zou, P. Li, A. Barker, K. Ge, R. (2020). ”Indicator-Directed Dynamic Power Management for Iterative Workloads on GPU-Accelerated Systems”, Proceedings - 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing, CCGRID 2020, 559-568. DOI: 10.1109/CCGrid49817.2020.00-37.
Minutoli, M. Castellana, V.G. Tan, C. Manzano, J. Amatya, V. Tumeo, A. Brooks, D. Wei, G.-Y. (2020). ”SODA: a New Synthesis Infrastructure for Agile Hardware Design of Machine Learning Accelerators”, IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD, 2020. DOI: 10.1145/3400302.3415781.
Poudel, S. Sharma, P. Dubey, A. Schneider, K.P. (2020). ”Advanced FLISR with Intentional Islanding Operations in an ADMS Environment Using GridAPPS-D”, IEEE Access, 8, 113766-113778. DOI: 10.1109/ACCESS.2020.3003325.
Firoz, J.S. Li, A. Li, J. Barker, K. (2020). ”On the Feasibility of Using Reduced-Precision Tensor Core Operations for Graph Analytics”, 2020 IEEE High Performance Extreme Computing Conference, HPEC 2020, DOI: 10.1109/HPEC43674.2020.9286152.
Ren, X. Gao, P. Zou, L. Jiao, S. Cao, X. Zhang, X. Jia, H. Engelhard, M.H. Matthews, B.E. Wu, H. Lee, H. Niu, C. Wang, C. Arey, B.W. Xiao, J. Liu, J. Zhang, J.-G. Xu, W. (2020). ”Role of inner solvation sheath within salt–solvent complexes in tailoring electrode/electrolyte interphases for lithium metal batteries”, Proceedings of the National Academy of Sciences of the United States of America, 117 (46), 28603-28613. DOI: 10.1073/pnas.2010852117.
Jian, J. Fernandez, C.A. Burghardt, J. Bonneville, A. Gupta, V. Garrison, G. (2020). ”Alternative, less water-intensive, fracturing fluids for enhanced geothermal systems”, 54th U.S. Rock Mechanics/Geomechanics Symposium.
Yang, N. Edington, S.C. Choi, T.H. Henderson, E.V. Heindel, J.P. Xantheas, S.S. Jordan, K.D. Johnsn, M.A. (2020). ”Mapping the temperature-dependent and network site-specific onset of spectral diffusion at the surface of a water cluster cage”, Proceedings of the National Academy of Sciences of the United States of America, 117 (42), 26047-26052. DOI: 10.1073/pnas.2017150117.
Meng, X. Karniadakis, G.E. (2020). ”A composite neural network that learns from multi-fidelity data: Application to function approximation and inverse PDE problems”, Journal of Computational Physics, 401. DOI: 10.1016/j.jcp.2019.109020.
Gawande, N.A. Daily, J.A. Siegel, C. Tallent, N.R. Vishnu, A. (2020). ”Scaling Deep Learning workloads: NVIDIA DGX-1/Pascal and Intel Knights Landing”, Future Generation Computer Systems, 108, 1162-1172. DOI: 10.1016/j.future.2018.04.073.
Barik, R. Minutoli, M. Halappanavar, M. Tallent, N.R. Kalyanaraman, A. (2020). ”Vertex Reordering for Real-World Graphs and Applications: An Empirical Evaluation”, Proceedings - 2020 IEEE International Symposium on Workload Characterization, IISWC 2020, 240-251. DOI: 10.1109/IISWC50251.2020.00031.
Wang, T. Geng, T. Li, A. Jin, X. Herbordt, M. (2020). ”FPDeep: Scalable Acceleration of CNN Training on Deeply-Pipelined FPGA Clusters”, IEEE Transactions on Computers, 69 (8), 1143-1158. DOI: 10.1109/TC.2020.3000118.
Cai, Y. Sun, C.Y. Li, Y.L. Hu, S.Y. Zhu, N.Y. Barker, E.I. Qian, L.Y. (2020). ”Phase field modeling of discontinuous dynamic recrystallization in hot deformation of magnesium alloys”, International Journal of Plasticity, 133. DOI: 10.1016/j.ijplas.2020.102773.
Singh, R.K. Bao, J. Wang, C. Fu, Y. Xu, Z. (2020). ”Hydrodynamics of countercurrent flows in a structured packed column: Effects of initial wetting and dynamic contact angle”, Chemical Engineering Journal, 398. DOI: 10.1016/j.cej.2020.125548.
Jia, H. Xu, Y. Burton, S.D. Gao, P. Zhang, X. Matthews, B.E. Engelhard, M.H. Zhong, L. Bowden, M.E. Xiao, B. Han, K.S. Wang, C. Xu, W. (2020). ”Enabling Ether-Based Electrolytes for Long Cycle Life of Lithium-Ion Batteries at High Charge Voltage”, ACS Applied Materials and Interfaces, 12 (49), 54893-54903. DOI: 10.1021/acsami.0c18177.
Liu, X.T. Halappanavar, M. Barker, K.J. Lumsdaine, A. Gebremedhin, A.H. (2020). ”Direction-optimizing label propagation and its application to community detection”, 17th ACM International Conference on Computing Frontiers 2020, CF 2020 - Proceedings, 192-201. DOI: 10.1145/3387902.3392634.
Chen, Y. Glaesemann, K. Li, X. Palmer, B. Huang, R. Vyakaranam, B. (2020). ”A generic advanced computing framework for executing windows-based dynamic contingency analysis tool in parallel on cluster machines”, IEEE Power and Energy Society General Meeting, 2020. DOI: 10.1109/PESGM41954.2020.9281477.
Zhang, D. Guo, L. Karniadakis, G.E. (2020). ”Learning in modal space: Solving time-dependent stochastic PDEs using physics-informed neural networks”, SIAM Journal on Scientific Computing, 42 (2), A639-A665. DOI: 10.1137/19M1260141.
Flamini, F. Walschaers, M. Spagnolo, N. Wiebe, N. Buchleitner, A. Sciarrino, F. (2020). ”Validating multi-photon quantum interference with finite data”, Quantum Science and Technology, 5 (4). DOI: 10.1088/2058-9565/aba03a.
Azad, A. Aznaveh, M.M. Beamer, S. Blanco, M. Chen, J. D'Alessandro, L. Dathathri, R. Davis, T. Deweese, K. Firoz, J. Gabb, H.A. Gill, G. Hegyi, B. Kolodziej, S. Low, T.M. Lumsdaine, A. Manlaibaatar, T. Mattson, T.G. McMillan, S. Peri, R. Pingali, K. Sridhar, U. Szarnyas, G. Zhang, Y. Zhang, Y. (2020). ”Evaluation of Graph Analytics Frameworks Using the GAP Benchmark Suite”, Proceedings - 2020 IEEE International Symposium on Workload Characterization, IISWC 2020, 216-227. DOI: 10.1109/IISWC50251.2020.00029.
Peng, B. Kowalski, K. Panyala, A. Krishnamoorthy, S. (2020). ”Green's function coupled cluster simulation of the near-valence ionizations of DNA-fragments”, Journal of Chemical Physics, 152 (1). DOI: 10.1063/1.5138658.
Minutoli, M. Drocco, M. Halappanavar, M. Tumeo, A. Kalyanaraman, A. (2020). ”CuRipples: Influence maximization on multi-CPU systems”, Proceedings of the International Conference on Supercomputing. DOI: 10.1145/3392717.3392750.
Firoz, J.S. Jenkins, L. Joslyn, C. Praggastis, B. Purvine, E. Raugas, M. (2020). ”Computing hypergraph homology in chapel”, Proceedings - 2020 IEEE 34th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2020, 667-670. DOI: 10.1109/IPDPSW50202.2020.00112.
Jia, H. Gao, P. Zou, L. Han, K.S. Engelhard, M.H. He, Y. Zhang, X. Zhao, W. Yi, R. Wang, H. Wang, C. Li, X. Zhang, J.-G. (2020). ”Controlling ion coordination structure and diffusion kinetics for optimized electrode-electrolyte interphases and high-performance Si anodes”, Chemistry of Materials, 32 (20), 8956-8964. DOI: 10.1021/acs.chemmater.0c02954.
Wiebe, N. (2020). ”Key questions for the quantum machine learner to ask themselves”, New Journal of Physics, 22 (9). DOI: 10.1088/1367-2630/abac39.
Wan, H. Woodward, C.S. Zhang, S. Vogl, C.J. Stinis, P. Gardner, D.J. Rasch, P.J. Zeng, X. Larson, V.E. Singh, B. (2020). ”Improving Time Step Convergence in an Atmosphere Model With Simplified Physics: The Impacts of Closure Assumption and Process Coupling”, Journal of Advances in Modeling Earth Systems, 12 (10). DOI: 10.1029/2019MS001982.
Tan, C. Xie, C. Li, A. Barker, K.J. Tumeo, A. (2020). ”OpenCGRA: An Open-Source Unified Framework for Modeling, Testing, and Evaluating CGRAs”, Proceedings - IEEE International Conference on Computer Design: VLSI in Computers and Processors, 2020, 381-388. DOI: 10.1109/ICCD50377.2020.00070.
Aksoy S.G., K.E. Nowak, and S.J. Young. 2019. "A Linear-Time Algorithm and Analysis of Graph Relative Hausdorff Distance." SIAM Journal on Mathematics of Data Science 1, no. 4:647-666. PNNL-SA-141641. DOI:10.1137/19M1248224.
Schuld, M., Bocharov, A., Svore, K.M., Wiebe, N. (2020). Circuit-centric quantum classifiers. Physical Review A, 101 (3). DOI:10.1103/PhysRevA.101.032308.
Meng, X., Karniadakis, G.E. (2020). A composite neural network that learns from multi-fidelity data: Application to function approximation and inverse PDE problems. Journal of Computational Physics, 401. DOI: 10.1016/j.jcp.2019.109020.
Jagtap, A.D., Kawaguchi, K., Karniadakis, G.E. (2020). Adaptive activation functions accelerate convergence in deep and physics-informed neural networks. Journal of Computational Physics, 404. DOI: 10.1016/j.jcp.2019.109136.
Laureanti, J., Brandi, J., Offor, E., Engel, D., Rallo, R., Ginovska, B., Martinez, X., Baaden, M., Baker, N.A. (2020). Visualizing biomolecular electrostatics in virtual reality with UnityMol-APBS. Protein Science, 29 (1),237-246. DOI: 10.1002/pro.3773.
Gawande, N.A., Daily, J.A., Siegel, C., Tallent, N.R., Vishnu, A. (2020). Scaling Deep Learning workloads: NVIDIA DGX-1/Pascal and Intel Knights Landing. Future Generation Computer Systems, 108,1162-1172. DOI: 10.1016/j.future.2018.04.073.
Kou, E., Urquijo, P., Altmannshofer, W., Beaujean, F., Bell, G., Beneke, M., Bigi, I.I., et al. (2020). Erratum: The Belle II Physics Book (Progress of Theoretical and Experimental Physics (2019) 2019 (123C01) DOI: 10.1093/ptep/ptz106). Progress of Theoretical and Experimental Physics, 2020 (2). DOI: 10.1093/ptep/ptaa008.
Alexander, F., Almgren, A., Bell, J., Bhattacharjee, A., Chen, J., et al. (2020). Exascale applications: Skin in the game. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 378 (2166). DOI: 10.1098/rsta.2019.0056.
Drgoňa, J., Picard, D., Helsen, L. (2020). Cloud-based implementation of white-box model predictive control for a GEOTABS office building: A field test demonstration. Journal of Process Control, 88,63-77. DOI: 10.1016/j.jprocont.2020.02.007.
Darulová, J., Pauka, S.J., Wiebe, N., Chan, K.W., Gardener, G.C., Manfra, M.J., Cassidy, M.C., Troyer, M. (2020). Autonomous Tuning and Charge-State Detection of Gate-Defined Quantum Dots. Physical Review Applied, 13 (5). DOI: 10.1103/PhysRevApplied.13.054005.
Peng, B., Kowalski, K., Panyala, A., Krishnamoorthy, S. (2020). Green's function coupled cluster simulation of the near-valence ionizations of DNA-fragments. Journal of Chemical Physics, 152 (1). DOI: 10.1063/1.5138658.
Wang, Y., Xiao, Z., Hu, S., Li, Y., Shi, S.-Q. (2020). A phase field study of the thermal migration of gas bubbles in UO2 nuclear fuel under temperature gradient. Computational Materials Science, 183. DOI: 10.1016/j.commatsci.2020.109817.
Aprà, E., Bylaska, E.J., de Jong, W.A., Govind, N., Kowalski, K., Straatsma, T.P., Valiev, M., et al. (2020). NWChem: Past, present, and future. The Journal of chemical physics, 152 (18). DOI: 10.1063/5.0004997.
Abudinén, F., Adachi, I., Ahlburg, P., Aihara, H., Akopov, N., Aloisio, A., Ameli, F., Andricek, L., Anh Ky, N., et al. (2020). Measurement of the integrated luminosity of the Phase 2 data of the Belle II experiment. Chinese Physics C, 44 (2). DOI: 10.1088/1674-1137/44/2/021001.
Rehr, J.J., Vila, F.D., Kas, J.J., Hirshberg, N.Y., Kowalski, K., Peng, B. (2020). Equation of motion coupled-cluster cumulant approach for intrinsic losses in x-ray spectra. The Journal of chemical physics, 152 (17). DOI: 10.1063/5.0004865.
Bauman, N.P., Peng, B., Kowalski, K. (2020). Coupled Cluster Green's function formulations based on the effective Hamiltonians. Molecular Physics. DOI: 10.1080/00268976.2020.1725669.
Bakker, C., Bhattacharya, A., Chatterjee, S., Vrabie, D.L. (2020). Learning and Information Manipulation: Repeated Hypergames for Cyber-Physical Security. IEEE Control Systems Letters, 4 (2),295-300. DOI: 10.1109/LCSYS.2019.2925681.
Tartakovsky, A.M., Marrero, C.O., Perdikaris, P., Tartakovsky, G.D., Barajas-Solano, D. (2020). Physics-Informed Deep Neural Networks for Learning Parameters and Constitutive Relationships in Subsurface Flow Problems. Water Resources Research, 56 (5). DOI: 10.1029/2019WR026731.
Li, A., Song, S.L., Chen, J., Li, J., Liu, X., Tallent, N.R., Barker, K.J. (2020). Evaluating Modern GPU Interconnect: PCIe, NVLink, NV-SLI, NVSwitch and GPUDirect. IEEE Transactions on Parallel and Distributed Systems, 31 (1),94-110. DOI: 10.1109/TPDS.2019.2928289.
Zhou, W., Zhou, E., Liu, G., Lin, L., Lumsdaine, A. (2020). Unsupervised Monocular Depth Estimation from Light Field Image. IEEE Transactions on Image Processing, 29,1606-1617. DOI: 10.1109/TIP.2019.2944343.
Zou, P., Lp, A., Barker, K., Ge, R. (2020). Indicator-Directed Dynamic Power Management for Iterative Workloads on GPU-Accelerated Systems. Proceedings - 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing, CCGRID 2020,559-568. DOI: 10.1109/CCGrid49817.2020.00-37.
Poudel, S., Sharma, P., Dubey, A., Schneider, K.P. (2020). Advanced FLISR with Intentional Islanding Operations in an ADMS Environment Using GridAPPS-D. IEEE Access, 8,113766-113778. DOI: 10.1109/ACCESS.2020.3003325.
Zhang, D., Guo, L., Karniadakis, G.E. (2020). Learning in modal space: Solving time-dependent stochastic PDEs using physics-informed neural networks. SIAM Journal on Scientific Computing, 42 (2), A639-A665. DOI: 10.1137/19M1260141.
Lin, P., Song, Q., Wu, Y., Pi, J. (2020). Repairing entities using star constraints in multirelational graphs. Proceedings - International Conference on Data Engineering, 2020, 229-240. DOI: 10.1109/ICDE48307.2020.00027.
Joslyn, C.A., Charles, L., Deperno, C., Gould, N., Nowak, K., Praggastis, B., Purvine, E., Robinson, M., Strules, J., Whitney, P. (2020). A sheaf theoretical approach to uncertainty quantification of heterogeneous geolocation information. Sensors (Switzerland), 20 (12),1-36. DOI: 10.3390/s20123418.
Wang, T., Geng, T., Li, A., Jin, X., Herbordt, M. (2020). FPDeep: Scalable Acceleration of CNN Training on Deeply-Pipelined FPGA Clusters. IEEE Transactions on Computers, 69 (8),1143-1158. DOI: 10.1109/TC.2020.3000118.
Liu, X.T., Halappanavar, M., Barker, K.J., Lumsdaine, A., Gebremedhin, A.H. (2020). Direction-optimizing label propagation and its application to community detection. 17th ACM International Conference on Computing Frontiers 2020, CF 2020 - Proceedings,192-201. DOI: 10.1145/3387902.3392634.
Chen, X., Duan, J., Karniadakis, G.E.M. (2020). Learning and meta-learning of stochastic advection-diffusion-reaction systems from sparse measurements. European Journal of Applied Mathematics. DOI: 10.1017/S0956792520000169.
Chakraborty, I., Chen, Y., Li, J., Vrabie, D. (2020). Theoretical Development of Controller Transfer applied to Dynamical Systems. e-Energy 2020 - Proceedings of the 11th ACM International Conference on Future Energy Systems,445-453. DOI: 10.1145/3396851.3402368.
Shi, R., Dong, P., Geng, T., Ding, Y., Ma, X., So, H.K.-H., Herbordt, M., Li, A., Wang, Y. (2020). CSB-RNN: A faster-than-realtime RNN acceleration framework with compressed structured blocks. Proceedings of the International Conference on Supercomputing. DOI: 10.1145/3392717.3392749.
Flamini, F., Walschaers, M., Spagnolo, N., Wiebe, N., Buchleitner, A., Sciarrino, F. (2020). Validating multi-photon quantum interference with finite data. Quantum Science and Technology, 5 (4). DOI: 10.1088/2058-9565/aba03a.
Minutoli, M., Drocco, M., Halappanavar, M., Tumeo, A., Kalyanaraman, A. (2020). CuRipples: Influence maximization on multi-CPU systems. Proceedings of the International Conference on Supercomputing. DOI: 10.1145/3392717.3392750.
Singh, R.K., Bao, J., Wang, C., Fu, Y., Xu, Z. (2020). Hydrodynamics of countercurrent flows in a structured packed column: Effects of initial wetting and dynamic contact angle. Chemical Engineering Journal, 398. DOI: 10.1016/j.cej.2020.125548.
Hagen, A., Church, E., Strube, J., Bhattacharya, K., Amatya, V. (2020). Scaling the training of particle classification on simulated MicroBooNE events to multiple GPUs. Journal of Physics: Conference Series, 1525 (1). DOI: 10.1088/1742-6596/1525/1/012104.
Stinis, P., Lei, H., Li, J., Wan, H. (2020). Improving solution accuracy and convergence for stochastic physics parameterizations with colored noise. Monthly Weather Review, 48, 2251-2263. DOI: 10.1175/MWR-D-19-0178.1.
Li, Y., Hu, S., Barker, E., Overman, N., Whalen, S., Mathaudhu, S. (2020). Effect of grain structure and strain rate on dynamic recrystallization and deformation behavior: A phase field-crystal plasticity model. Computational Materials Science, 180. https:/doi.org/10.1016/j.commatsci.2020.109707
Stinis, P. (2020). Enforcing constraints for time series prediction in supervised, unsupervised and reinforcement learning. CEUR Workshop Proceedings, 2587. https:/doi.org/-
Sabet, A.H.N., Qiu, J., Zhao, Z., Krishnamoorthy, S. (2020). Reliability Analysis for Unreliable FSM Computations. ACM Transactions on Architecture and Code Optimization, 17 (2). https:/doi.org/10.1145/3377456
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Aksoy, S.G., Purvine, E., Cotilla-Sanchez, E., Halappanavar, M., Lambiotte, R. (2018). A generative graph model for electrical infrastructure networks. Journal of Complex Networks, 7 (1),128-162. https:/doi.org/10.1093/comnet/cny016
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Hou, G.-L., Govind, N., Xantheas, S.S., Wang, X.-B. (2018). Deviation from the trans-Effect in Ligand-Exchange Reactions of Zeise's Ions PtCl3(C2H4)- with Heavier Halides (Br-, I-). Journal of Physical Chemistry A, 122 (5),1209-1214. https:/doi.org/10.1021/acs.jpca.7b10808
Tipireddy, R., Stinis, P., Tartakovsky, A.M. (2018). Stochastic basis adaptation and spatial domain decomposition for partial differential equations with random coefficients. SIAM-ASA Journal on Uncertainty Quantification, 6 (1),273-301. https:/doi.org/10.1137/16M1097134
Bakker, C., Halappanavar, M., Visweswara Sathanur, A. (2018). Dynamic graphs, community detection, and Riemannian geometry. Applied Network Science, 3 (1). https:/doi.org/10.1007/s41109-018-0059-2
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Lin, P., Song, Q., Shen, J., Wu, Y. (2018). Discovering graph patterns for fact checking in knowledge graphs. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10827, 783-801. https:/doi.org/10.1007/978-3-319-91452-7_50
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McDermott, T.E., Stephan, E.G., Gibson, T.D. (2018). Alternative Database Designs for the Distribution Common Information Model. Proceedings of the IEEE Power Engineering Society Transmission and Distribution Conference, 2018-. https:/doi.org/10.1109/TDC.2018.8440470
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Stetcu, I., Bulgac, A., Jin, S., Roche, K.J., Schunck, N. (2018). Real time description of fission. Proceedings of the 15th International Conference on Nuclear Reaction Mechanisms, NRM 2018, 197-202. https:/doi.org/-
Wickramasinghe, U., Lumsdaine, A. (2018). RMalloc() and RpIPE(): A uGNI-based distributed remote memory allocator and access library for one-sided messaging. Proceedings of the 8th International Workshop on Runtime and Operating Systems for Supercomputers, ROSS 2018 - In conjunction with HPDC 2018. https:/doi.org/10.1145/3217189.3217191
Hong, C., Sukumaran-Rajam, A., Kim, J., Rawat, P.S., Krishnamoorthy, S., Pouchet, L.-N., Rastello, F., Sadayappan, P. (2018). POSTER: Performance modeling for GPUs using abstract kernel emulation. Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPOPP, 397-398. https:/doi.org/10.1145/3178487.3178524
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Firoz, J.S., Zalewski, M., Lumsdaine, A. (2018). POSTER: A scalable distance-1 vertex coloring algorithm for power-law graphs. Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPOPP, 391-392. https:/doi.org/10.1145/3178487.3178521
Kanewala, T.A., Zalewski, M., Lumsdaine, A. (2018). Distributed, shared-memory parallel triangle counting. Proceedings of the Platform for Advanced Scientific Computing Conference, PASC 2018. https:/doi.org/10.1145/3218176.3218229
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Kowalski, K., Brabec, J., Peng, B. (2018). Regularized and Renormalized Many-Body Techniques for Describing Correlated Molecular Systems: A Coupled-Cluster Perspective. Annual Reports in Computational Chemistry, 14, 3-45. https:/doi.org/10.1016/bs.arcc.2018.06.001
Young, S.J., Makarov, Y., Diao, R., Fan, R., Huang, R., Orbrien, J., Halappanavar, M., Vallem, M., Huang, Z.H. (2018). Synthetic Power Grids from Real World Models. IEEE Power and Energy Society General Meeting, 2018-. https:/doi.org/10.1109/PESGM.2018.8585792
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Zhou, W., Li, P., Lumsdaine, A., Lin, L. (2018). Light-field flow: A subpixel-accuracy depth flow estimation with geometric occlusion model from a single light-field image. Proceedings - International Conference on Image Processing, ICIP, 2017, 1632-1636. https:/doi.org/10.1109/ICIP.2017.8296558
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Panyala, A., Subasi, O., Halappanavar, M., Kalyanaraman, A., Chavarría-Miranda, D., Krishnamoorthy, S. (2018). Approximate Computing Techniques for Iterative Graph Algorithms. Proceedings - 24th IEEE International Conference on High Performance Computing, HiPC 2017, 2017- ,23-32. https:/doi.org/10.1109/HiPC.2017.00013
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Ritter, M., Wood, L., Kuhr, T., Bracko, M., Elsethagen, T., Fox, K., Hall, J., Pulvermacher, C., Raju, B., Schram, M., Stephan, E. (2018). Belle II Conditions Database. Journal of Physics: Conference Series, 1085 (3). https:/doi.org/10.1088/1742-6596/1085/3/032032
Chen, Y., Etingov, P., Fitzhenry, E., Sharma, P., Nguyen, T., Makarov, Y., Rice, M., Allwardt, C., Widergren, S. (2018). Bringing probabilistic analysis capability from planning to operation. Control Engineering Practice, 71, 18-25. https:/doi.org/10.1016/j.conengprac.2017.06.006
Li, W., Lian, J., Engel, D., Wang, H. (2018). Ensemble-based uncertainty quantification for coordination and control of thermostatically controlled loads. Journal of Control and Decision, 5 (2),148-168. https:/doi.org/10.1080/23307706.2017.1353931
Chen, Y., Palmer, B., Sharma, P., Yuan, Y., Mathew, B., Huang, Z. (2018). A High Performance Computational Framework for Dynamic Security Assessment under Uncertainty. Conference Record of the 3rd IEEE International Workshop on Electronic Power Grid, eGrid 2018. https:/doi.org/10.1109/eGRID.2018.8598684
Tumeo, A., Franke, H., Palermo, G., Feo, J. (2018). Guest Editorial: Special Issue on Computing Frontiers. International Journal of Parallel Programming, 46 (2),333-335. https:/doi.org/10.1007/s10766-018-0556-z
Chakraborty, I., Chakraborty, R., Vrabie, D. (2018). Generative adversarial network based autoencoder: Application to fault detection problem for closed-loop dynamical systems ∗. CEUR Workshop Proceedings, 2289. https:/doi.org/-
Tartakovsky, A.M. (2018). Effective Stochastic Model For Reactive Transport. Reactive Transport Modeling: Applications in Subsurface Energy and Environmental Problems ,511-531. https:/doi.org/10.1002/9781119060031.ch11
Ghosh, S., Halappanavar, M., Tumeo, A., Kalyanaraman, A., Gebremedhin, A.H. (2018). Scalable Distributed Memory Community Detection Using Vite. 2018 IEEE High Performance Extreme Computing Conference, HPEC 2018. https:/doi.org/10.1109/HPEC.2018.8547534
Shekar, V., Fiondella, L., Chatterjee, S., Halappanavar, M. (2018). A game-theoretic method to efficiently assess the vulnerability of a dynamic transportation network. PSAM 2018 - Probabilistic Safety Assessment and Management. https:/doi.org/-
Palmer, B. (2018). Coarse-grained hydrodynamics from correlation functions. Physical Review E, 97 (2). https:/doi.org/10.1103/PhysRevE.97.022106
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Friese, R.D., Crowder, J.A., Siegel, H.J., Carbone, J.N. (2018). Bi-objective study for the assignment of unmanned aerial vehicles to targets. 2018 World Congress in Computer Science, Computer Engineering and Applied Computing, CSCE 2018 - Proceedings of the 2018 International Conference on Artificial Intelligence, ICAI 2018. https:/doi.org/-
Firoz, J.S., Zalewski, M., Lumsdaine, A. (2018). POSTER: A Scalable Distance-1 Vertex Coloring Algorithm for Power-Law Graphs. ACM SIGPLAN Notices, 53 (1),391-392. https:/doi.org/10.1145/3178487.3178521
Wickramasinghe, U., Lumsdaine, A. (2018). Enabling efficient inter-node message passing and remote memory access via a uGNI based light-weight network substrate for cray interconnects. Proceedings - 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGRID 2018, 578-588. https:/doi.org/10.1109/CCGRID.2018.00006
Kim, J., Sukumaran-Rajam, A., Hong, C., Panyala, A., Srivastava, R.K., Krishnamoorthy, S., Sadayappan, P. (2018). Optimizing tensor contractions in CCSD(T) for efficient execution on GPUs. Proceedings of the International Conference on Supercomputing, 96-106. https:/doi.org/10.1145/3205289.3205296
Vallem, M.R., Vyakaranam, B., Tipireddy, R., Holzer, J.T., Makarov, Y.V., Samaan, N.A. (2018). Stochastic correlation analysis to rank the impact of intermittent wind generation on unreliability margins of power systems. 2018 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2018 - Proceedings. https:/doi.org/10.1109/PMAPS.2018.8440541
Tumeo, A. (2018). Architecture independent integrated early performance and energy estimation. 2017 8th International Green and Sustainable Computing Conference, IGSC 2017, 2017,1-6. https:/doi.org/10.1109/IGCC.2017.8323602
Chin, G., Fitzhenry, E., McBain, A., Beus, S., Marinovici, L., Hansen, J., Studarus, K. (2018). Visual steering and modeling environment for smart grid models and simulations. IEEE Power and Energy Society General Meeting, 2018,1-5. https:/doi.org/10.1109/PESGM.2017.8274093
Kassianov, E., Monroe, J., Riihimaki, L., Flynn, C., Cromwell, E., Hodges, G., McComiskey, A. (2018). Climatology of aerosol optical depth at mid-continental US site: Ground-based observations. Proceedings of SPIE - The International Society for Optical Engineering, 10786. https:/doi.org/10.1117/12.2326690
Bhatia, U., Chatterjee, S., Ganguly, A.R., Gao, J., Halappanavar, M., Oster, M., Clark, K., Brigantic, R., Tipireddy, R. (2018). Aviation Transportation, Cyber Threats, and Network-of-Networks: Modeling Perspectives for Translating Theory to Practice. 2018 IEEE International Symposium on Technologies for Homeland Security, HST 2018. https:/doi.org/10.1109/THS.2018.8574123
Kalyanaraman, A., Halappanavar, M. (2018). Guest editorial: Advances in parallel graph processing: Algorithms, architectures, and application frameworks. IEEE Transactions on Multi-Scale Computing Systems, 4 (3),188-189. https:/doi.org/10.1109/TMSCS.2018.2858297
Abdesselam, A., Adachi, I., Adamczyk, K., Ahn, J.K., Aihara, H., Al Said, S., Arinstein, K., Arita, Y., Asner, et al. (2018). Measurement of the D∗− polarization in the decay B0 → D∗−τ+ντ. 10th International Workshop on the CKM Unitarity Triangle, CKM 2018. https:/doi.org/-
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Subasi, O., Chang, C.-K., Erez, M., Krishnamoorthy, S. (2018). Characterizing the impact of soft errors affecting floating-point ALUs using RTL-level fault injection. ACM International Conference Proceeding Series. https:/doi.org/10.1145/3225058.3225089
Liu, Y., Chase, J.M., Gorton, I., Rice, M., Wynne, A. (2018). Modelling and coordinating multi-source distributed power system models in service-oriented architecture. International Journal of High Performance Computing and Networking, 12 (2),191-206. https:/doi.org/10.1504/ijhpcn.2018.094369
Hong, C., Sukumaran-Rajam, A., Kim, J., Rawat, P.S., Krishnamoorthy, S., Pouchet, L.-N., Rastello, F., Sadayappan, P. (2018). POSTER: Performance Modeling for GPUs using Abstract Kernel Emulation. ACM SIGPLAN Notices, 53 (1),397-398. https:/doi.org/10.1145/3178487.3178524
Young, S.J., Makarov, Y., Diao, R., Halappanavar, M., Vallem, M., Fan, R., Huang, R., Orbrien, J., Huang, Z.H. (2018). Topological Power Grid Statistics from a Network-of-Networks Perspective. IEEE Power and Energy Society General Meeting, 2018-. https:/doi.org/10.1109/PESGM.2018.8586475
Friese, R.D., Tallent, N.R., Schram, M., Halappanavar, M., Barker, K.J. (2018). Optimizing Distributed Data-Intensive Workflows. Proceedings - IEEE International Conference on Cluster Computing, ICCC, 2018- ,279-289. https:/doi.org/10.1109/CLUSTER.2018.00045
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Li, A., Liu, W., Kristensen, M.R.B., Vinter, B., Wang, H., Hou, K., Marquez, A., Song, S.L. (2017). Exploring and analyzing the real impact of modern on-package memory on hpc scientific kernels. Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2017. https:/doi.org/10.1145/3126908.3126931
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Lu, H., Halappanavar, M., Chavarria-Miranda, D., Gebremedhin, A.H., Panyala, A., Kalyanaraman, A. (2017). Algorithms for balanced graph colorings with applications in parallel computing. IEEE Transactions on Parallel and Distributed Systems, 28 (5),1240-1256. https:/doi.org/10.1109/TPDS.2016.2620142
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Douberly, G.E., Miller, R.E., Xantheas, S.S. (2017). Formation of Exotic Networks of Water Clusters in Helium Droplets Facilitated by the Presence of Neon Atoms. Journal of the American Chemical Society, 139 (11),4152-4156. https:/doi.org/10.1021/jacs.7b00510
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Tartakovsky, A.M., Panzeri, M., Tartakovsky, G.D., Guadagnini, A. (2017). Uncertainty Quantification in Scale-Dependent Models of Flow in Porous Media. Water Resources Research, 53 (11),9392-9401. https:/doi.org/10.1002/2017WR020905
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Hawley, A.K., Torres-Beltrán, M., Zaikova, E., Walsh, D.A., Mueller, A., Scofield, M., Kheirandish, S., Payne, C., Pakhomova, L., Bhatia, M., Shevchuk, O., Gies, E.A., Fairley, D., Malfatti, S.A., Norbeck, A.D., Brewer, H.M., Pasa-Tolic, L., Del Rio, T.G., Suttle, C.A., Tringe, S., Hallam, S.J. (2017). A compendium of multi-omic sequence information from the Saanich Inlet water column. Scientific Data, 4. https:/doi.org/10.1038/sdata.2017.160
Willow, S.Y., Xantheas, S.S. (2017). Molecular-Level Insight of the Effect of Hofmeister Anions on the Interfacial Surface Tension of a Model Protein. Journal of Physical Chemistry Letters, 8 (7),1574-1577. https:/doi.org/10.1021/acs.jpclett.7b00069
Peng, B., Govind, N., Aprà, E., Klemm, M., Hammond, J.R., Kowalski, K. (2017). Coupled Cluster Studies of Ionization Potentials and Electron Affinities of Single-Walled Carbon Nanotubes. Journal of Physical Chemistry A, 121 (6),1328-1335. https:/doi.org/10.1021/acs.jpca.6b10874
Perarnau, S., Zounmevo, J.A., Dreher, M., Essen, B.C.V., Gioiosa, R., Iskra, K., Gokhale, M.B., Yoshii, K., Beckman, P. (2017). Argo NodeOS: Toward Unified Resource Management for Exascale. Proceedings - 2017 IEEE 31st International Parallel and Distributed Processing Symposium, IPDPS 2017, 153-162. https:/doi.org/10.1109/IPDPS.2017.25
Subasi, O., Kestor, G., Krishnamoorthy, S. (2017). Toward a General Theory of Optimal Checkpoint Placement. Proceedings - IEEE International Conference on Cluster Computing, ICCC, 2017- ,464-474. https:/doi.org/10.1109/CLUSTER.2017.127
Cheng, G., Choi, K.S., Hu, X., Sun, X. (2017). Predicting Deformation Limits of Dual-Phase Steels Under Complex Loading Paths. JOM, 69 (6),1046-1051. https:/doi.org/10.1007/s11837-017-2333-7
Peng, I.B., Markidis, S., Gioiosa, R., Kestor, G., Laure, E. (2017). MPI Streams for HPC Applications. Advances in Parallel Computing, 30, 75-92. https:/doi.org/10.3233/978-1-61499-816-7-75
Subasi, O., Di, S., Balaprakash, P., Unsal, O., Labarta, J., Cristal, A., Krishnamoorthy, S., Cappello, F. (2017). MACORD: Online adaptive machine learning framework for silent error detection. Proceedings - IEEE International Conference on Cluster Computing, ICCC, 2017- ,717-724. https:/doi.org/10.1109/CLUSTER.2017.128
Hamm, P., Fanourgakis, G.S., Xantheas, S.S. (2017). A surprisingly simple correlation between the classical and quantum structural networks in liquid water. Journal of Chemical Physics, 147 (6). https:/doi.org/10.1063/1.4993166
Peng, I.B., Gioiosa, R., Kestor, G., Laure, E., Markidis, S. (2017). Preparing HPC Applications for the Exascale Era: A Decoupling Strategy. Proceedings of the International Conference on Parallel Processing, 1-10. https:/doi.org/10.1109/ICPP.2017.9
Soulami, A., Burkes, D.E., Joshi, V.V., Lavender, C.A., Paxton, D. (2017). Finite-element model to predict roll-separation force and defects during rolling of U-10Mo alloys. Journal of Nuclear Materials, 494, 182-191. https:/doi.org/10.1016/j.jnucmat.2017.07.006
Li, A., Zhao, W., Song, S.L. (2017). BVF: Enabling significant on-chip power savings via bit-value-favor for throughput processors. Proceedings of the Annual International Symposium on Microarchitecture, MICRO, 131207, 532-545. https:/doi.org/10.1145/3123939.3123944
Ashraf, R.A., Gioiosa, R., Kestor, G., DeMara, R.F. (2017). Exploring the effect of compiler optimizations on the reliability of hpc applications. Proceedings - 2017 IEEE 31st International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017, 1274-1283. https:/doi.org/10.1109/IPDPSW.2017.7
Tipireddy, R., Stinis, P., Tartakovsky, A.M. (2017). Basis adaptation and domain decomposition for steady-state partial differential equations with random coefficients. Journal of Computational Physics, 351, 203-215. https:/doi.org/10.1016/j.jcp.2017.08.067
Savic, V., Hector, L., Basu, U., Basudhar, A., Gandikota, I., Stander, N., Park, T., Pourboghrat, F., Choi, K.S., Sun, X., Hu, J., Abu-Farha, F., Kumar, S. (2017). Integrated Computational Materials Engineering (ICME) Multi-Scale Model Development for Advanced High Strength Steels. SAE Technical Papers, 2017- (March). https:/doi.org/10.4271/2017-01-0226
Xu, K., Schreiber, D.K., Li, Y., Johnson, B.R., McCloy, J. (2017). Effect of defects, magnetocrystalline anisotropy, and shape anisotropy on magnetic structure of iron thin films by magnetic force microscopy. AIP Advances, 7 (5). https:/doi.org/10.1063/1.4976580
Yoo, S., Xantheas, S.X. (2017). Structures, energetics, and spectroscopic fingerprints of water clusters n = 2−24. Handbook of Computational Chemistry, 1139-1173. https:/doi.org/10.1007/978-3-319-27282-5_21
Rivas-Gomez, S., Gioiosa, R., Peng, I.B., Kestor, G., Narasimhamurthy, S., Laure, E., Markidis, S. (2017). MPI windows on storage for HPC applications. ACM International Conference Proceeding Series. https:/doi.org/10.1145/3127024.3127034
Panyala, A., Chavarría-Miranda, D., Manzano, J.B., Tumeo, A., Halappanavar, M. (2017). Exploring performance and energy tradeoffs for irregular applications: A case study on the Tilera many-core architecture. Journal of Parallel and Distributed Computing, 104, 234-251. https:/doi.org/10.1016/j.jpdc.2016.06.006
Peng, B., Kowalski, K. (2017). Low-rank factorization of electron integral tensors and its application in electronic structure theory. Chemical Physics Letters, 672, 47-53. https:/doi.org/10.1016/j.cplett.2017.01.056
Tipireddy, R., Kumar, S. (2017). Spatially-degraded adhesive anchors under material uncertainty. International Journal of Adhesion and Adhesives, 76, 61-69. https:/doi.org/10.1016/j.ijadhadh.2017.02.010
Rubio-Herrero, J., Chandan, V., Siegel, C., Vishnu, A., Vrabie, D. (2017). A learning framework for control-oriented modeling of buildings. Proceedings - 16th IEEE International Conference on Machine Learning and Applications, ICMLA 2017, 2017, 473-478. https:/doi.org/10.1109/ICMLA.2017.00079
Rivas-Gomez, S., Markidis, S., Peng, I.B., Laure, E., Kestor, G., Gioiosa, R. (2017). Extending message passing interface windows to storage. Proceedings - 2017 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGRID 2017, 727-730. https:/doi.org/10.1109/CCGRID.2017.44
Tallent, N.R., Kerbyson, D.J., Hoisie, A. (2017). Representative paths analysis. Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2017. https:/doi.org/10.1145/3126908.3126962
Shekar, V., Fiondella, L., Chatterjee, S., Halappanavar, M. (2017). Quantitative assessment of transportation network vulnerability with dynamic traffic simulation methods. 2017 IEEE International Symposium on Technologies for Homeland Security, HST 2017. https:/doi.org/10.1109/THS.2017.7943454
Lifflander, J., Krishnamoorthy, S. (2017). Cache locality optimization for recursive programs. Proceedings of the ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI), 128414, 1-16. https:/doi.org/10.1145/3062341.3062385
Castellana, V.G., Minutoli, M., Bhatt, S., Agarwal, K., Bleeker, A., Feo, J., Chavarria-Miranda, D., Haglin, D. (2017). High-Performance Data Analytics beyond the Relational and Graph Data Models with GEMS. Proceedings - 2017 IEEE 31st International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017, 1029-1038. https:/doi.org/10.1109/IPDPSW.2017.70
Sharma, V.C., Gopalakrishnan, G., Krishnamoorthy, S. (2017). PRESAGE: Protecting Structured Address Generation against Soft Errors. Proceedings - 23rd IEEE International Conference on High Performance Computing, HiPC 2016, 252-261. https:/doi.org/10.1109/HiPC.2016.037
Bulgac, A., Jin, S., Magierski, P., Roche, K., Schunck, N., Stetcu, I. (2017). Nuclear Fission: From more phenomenology and adjusted parameters to more fundamental theory and increased predictive power. EPJ Web of Conferences, 163. https:/doi.org/10.1051/epjconf/201716300007
Wang, X., Xu, Z., Soulami, A., Hu, X., Lavender, C., Joshi, V. (2017). Modeling Early-Stage Processes of U-10 Wt.%Mo Alloy Using Integrated Computational Materials Engineering Concepts. JOM, 69 (12),2532-2537. https:/doi.org/10.1007/s11837-017-2608-z
Stephan, E., Raju, B., Elsethagen, T., Pouchard, L., Gamboa, C. (2017). A scientific data provenance harvester for distributed applications. 2017 New York Scientific Data Summit, NYSDS 2017 - Proceedings. https:/doi.org/10.1109/NYSDS.2017.8085041
Subasi, O., Krishnamoorthy, S. (2017). A Gaussian Process Approach for Effective Soft Error Detection. Proceedings - IEEE International Conference on Cluster Computing, ICCC, 2017- ,608-612. https:/doi.org/10.1109/CLUSTER.2017.129
Tipireddy, R., Lerchen, M., Ramuhalli, P. (2017). Virtual sensors for robust on-line monitoring (OLM) and diagnostics. 10th International Topical Meeting on Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technologies, NPIC and HMIT 2017, 2, 719-728. https:/doi.org/-
Peng, I.B., Markidis, S., Laure, E., Kestor, G., Gioiosa, R. (2017). Idle period propagation in message-passing applications. Proceedings - 18th IEEE International Conference on High Performance Computing and Communications, 14th IEEE International Conference on Smart City and 2nd IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2016, 937-944. https:/doi.org/10.1109/HPCC-SmartCity-DSS.2016.0134
Amatya, V., Vishnu, A., Siegel, C., Daily, J. (2017). What does fault tolerant deep learning need from MPI?. ACM International Conference Proceeding Series. https:/doi.org/10.1145/3127024.3127037
Subasi, O., Unsal, O., Krishnamoorthy, S. (2017). Automatic risk-based selective redundancy for fault-tolerant task-parallel HPC applications. Proceedings of ESPM2 2017: 3rd International Workshop on Extreme Scale Programming Models and Middleware - Held in conjunction with SC 2017: The International Conference for High Performance Computing, Networking, Storage and Analysis. https:/doi.org/10.1145/3152041.3152083
Ceriani, M., Secchi, S., Villa, O., Tumeo, A., Palermo, G. (2017). Exploring efficient hardware support for applications with irregular memory patterns on multinode manycore architectures. IEEE Transactions on Parallel and Distributed Systems, 28 (6),1635-1648. https:/doi.org/10.1109/TPDS.2014.2345073
Saha, S., Vullikanti, A., Halappanavar, M. (2017). FlipNet: Modeling Covert and Persistent Attacks on Networked Resources. Proceedings - International Conference on Distributed Computing Systems, 2444-2451. https:/doi.org/10.1109/ICDCS.2017.298
Landwehr, J., Suetterlein, J., Manzano, J., Marquez, A., Barker, K.J., Gao, G.R. (2017). Designing scalable distributed memory models: A case study. ACM International Conference on Computing Frontiers 2017, CF 2017 ,174-182. https:/doi.org/10.1145/3075564.3077425
Ramachandran, T., Kundu, S., Chen, Y., Vrabie, D. (2017). Towards a framework for selection of supervisory control for commercial buildings: HVAC system energy efficiency. Proceedings of the American Control Conference, 2925-2930. https:/doi.org/10.23919/ACC.2017.7963395
Ward, T.B., Miliordos, E., Carnegie, P.D., Xantheas, S.S., Duncan, M.A. (2017). Ortho-para interconversion in cation-water complexes: The case of V+(H2O) and Nb+(H2O) clusters. Journal of Chemical Physics, 146 (22). https:/doi.org/10.1063/1.4984826
Singh, A., Stephan, E., Schram, M., Altintas, I. (2017). Deep learning on operational facility data related to large-scale distributed area scientific workflows. Proceedings - 13th IEEE International Conference on eScience, eScience 2017 ,586-591. https:/doi.org/10.1109/eScience.2017.94
Tipireddy, R., Chatterjee, S., Paulson, P., Oster, M., Halappanavar, M. (2017). Agent-centric approach for cybersecurity decision-support with partial observability. 2017 IEEE International Symposium on Technologies for Homeland Security, HST 2017. https:/doi.org/10.1109/THS.2017.7943478
Maglalang, J., Krishnamoorthy, S., Agrawal, K. (2017). Locality-Aware Dynamic Task Graph Scheduling. Proceedings of the International Conference on Parallel Processing ,70-80. https:/doi.org/10.1109/ICPP.2017.16
Ramuhalli, P., Tipireddy, R., Lerchen, M., Shumaker, B., Coble, J., Nair, A., Boring, S. (2017). Robust online monitoring for calibration assessment of transmitters and instrumentation. 10th International Topical Meeting on Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technologies, NPIC and HMIT 2017, 2, 1176-1184. https:/doi.org/-
Bylaska, E.J., Aprà, E., Kowalski, K., Jacquelin, M., De Jong, W.A., Vishnu, A., Palmer, B., Daily, J., Straatsma, T.P., Hammond, J.R., Klemm, M. (2017). Transitioning NWChem to the next generation of manycore machines. Exascale Scientific Applications: Scalability and Performance Portability, 165-186. https:/doi.org/10.1201/b21930
Kanewala, T., Zalewski, M., Lumsdaine, A. (2017). Distributed-memory fast maximal independent set. 2017 IEEE High Performance Extreme Computing Conference, HPEC 2017. https:/doi.org/10.1109/HPEC.2017.8091032
Wood, L., Elsethagen, T., Schram, M., Stephan, E. (2017). Conditions Database for the Belle II Experiment. Journal of Physics: Conference Series, 898 (4). https:/doi.org/10.1088/1742-6596/898/4/042060
Keller, M.T., Young, S.J. (2017). Combinatorial reductions for the Stanley depth of I and S/I. Electronic Journal of Combinatorics, 24 (3). https:/doi.org/10.37236/6783
Zhou, W., Lumsdaine, A., Lin, L., Zhang, W., Wang, R. (2017). Edge-aware light-field flow for depth estimation and occlusion detection. IS and T International Symposium on Electronic Imaging Science and Technology, 94-99. https:/doi.org/10.2352/ISSN.2470-1173.2017.17.COIMG-431
Schram, M., Bansal, V., Friese, R.D., Tallent, N.R., Yin, J., Barker, K.J., Stephan, E., Halappanavar, M., Kerbyson, D.J. (2017). Integrating prediction, provenance, and optimization into high energy workflows. Journal of Physics: Conference Series, 898 (6). https:/doi.org/10.1088/1742-6596/898/6/062052
Cottam, J.A., Blaha, L., Zarzhitsky, D., Thomas, M., Skomski, E. (2017). Crossing the Streams: Fuzz testing with user input. Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017, 2018, 4362-4371. https:/doi.org/10.1109/BigData.2017.8258466
Berikkyzy, Z., Cox, C., Dairyko, M., Hogenson, K., Kumbhat, M., Lidický, B., Messerschmidt, K., Moss, K., Nowak, K., Palmowski, K.F., Stolee, D. (2017). (4, 2)-Choosability of Planar Graphs with Forbidden Structures. Graphs and Combinatorics, 33 (4),751-787. https:/doi.org/10.1007/s00373-017-1812-5
Kanewala, T.A., Zalewski, M., Lumsdaine, A. (2017). Families of graph algorithms: SSSP case study. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10417, 428-441. https:/doi.org/10.1007/978-3-319-64203-1_31
Tumeo, A., Ceriani, M., Palermo, G., Minutoli, M., Castellana, V.G., Ferrandi, F. (2017). Real-time considerations for rugged embedded systems. Rugged Embedded Systems: Computing in Harsh Environments, 39-56. https:/doi.org/10.1016/B978-0-12-802459-1.00003-8
Rajbhandari, S., Rastello, F., Kowalski, K., Krishnamoorthy, S., Sadayappan, P. (2017). Optimizing the four-index integral transform using data movement lower bounds analysis. Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPOPP, 327-340. https:/doi.org/10.1145/3018743.3018771
Sun, X., Cheng, G., Hu, X.H., Choi, K.S. (2017). Predicting size-dependent fracture strain of DP980. ICF 2017 - 14th International Conference on Fracture, 2 ,382-383. https:/doi.org/-
Sathanur, A.V., Choudhury, S., Joslyn, C., Purohit, S. (2017). When labels fall short: Property graph simulation via blending of network structure and vertex attributes. International Conference on Information and Knowledge Management, Proceedings, 131841, 2287-2290. https:/doi.org/10.1145/3132847.3133065
Purvine, E., Cotilla-Sanchez, E., Halappanavar, M., Huang, Z., Lin, G., Lu, S., Wang, S. (2017). Comparative study of clustering techniques for real-time dynamic model reduction. Statistical Analysis and Data Mining, 10 (5),263-276. https:/doi.org/10.1002/sam.11352
Gioiosa, R. (2017). Resilience for extreme scale computing. Rugged Embedded Systems: Computing in Harsh Environments, 123-148. https:/doi.org/10.1016/B978-0-12-802459-1.00005-1
Kassianov, E., Riley, E.A., Kleiss, J.M., Long, C.N., Riihimaki, L., Flynn, D., Flynn, C., Berg, L.K. (2017). Macrophysical properties of continental cumulus clouds from active and passive remote sensing. Proceedings of SPIE - The International Society for Optical Engineering, 10424. https:/doi.org/10.1117/12.2278029
Barker, K.J., Kerbyson, D.J. (2017). Portable methodologies for energy optimization on large-scale power-constrained systems. Exascale Scientific Applications: Scalability and Performance Portability, 1-16. https:/doi.org/10.1201/b21930
Purohit, S., Choudhury, S., Holder, L.B. (2017). Application-specific graph sampling for frequent subgraph mining and community detection. Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017, 2018, 1000-1005. https:/doi.org/10.1109/BigData.2017.8258022
Firoz, J.S., Kanewala, T.A., Zalewski, M., Barnas, M., Lumsdaine, A. (2017). Distributed Control: The Benefits of Eliminating Global Synchronization via Effective Scheduling in the Context of Graph Applications. ACM SIGPLAN Notices, 52 (8),441-442. https:/doi.org/10.1145/3018743.3019036
Minutoli, M., Castellana, V.G., Tumeo, A., Lattuada, M., Ferrandi, F. (2017). A dynamically scheduled architecture for the synthesis of graph methods. 2016 IEEE Hot Chips 28 Symposium, HCS 2016. https:/doi.org/10.1109/HOTCHIPS.2016.7936228
Suetterlein, J., Landwehr, J., Marquez, A., Manzano, J., Barker, K.J., Gao, G.R. (2017). Verification of the extended roofline model for asynchronous many task runtimes. Proceedings of ESPM2 2017: 3rd International Workshop on Extreme Scale Programming Models and Middleware - Held in conjunction with SC 2017: The International Conference for High Performance Computing, Networking, Storage and Analysis. https:/doi.org/10.1145/3152041.3152087
Getov, V., Macduff, M., Kerbyson, D.J., Hoisie, A. (2017). Application-Specific Energy Modeling of Multi-Core Processors. Advances in Parallel Computing, 30 ,35-54. https:/doi.org/10.3233/978-1-61499-816-7-35
Prasad, S.K., Banicescu, I., Barnas, M., Giménez, D., Lumsdaine, A. (2017). Keeping up with technology: Teaching Parallel, Distributed and High-Performance Computing. Journal of Parallel and Distributed Computing, 105, 1-3. https:/doi.org/10.1016/j.jpdc.2017.03.001
Gioiosa, R., Warfel, T., Tumeo, A., Friese, R. (2017). Pushing the limits of irregular access patterns on emerging network architecture: A case study. Proceedings - IEEE International Conference on Cluster Computing, ICCC, 2017- ,874-881. https:/doi.org/10.1109/CLUSTER.2017.125
Palmer, B. (2017). Application of PGAS programming to power grid simulation. Proceedings of PAW 2016: 1st PGAS Applications Workshop - Held in conjunction with SC 2016: The International Conference for High Performance Computing, Networking, Storage and Analysis, 33-40. https:/doi.org/10.1109/PAW.2016.010
Xu, Z., Tartakovsky, A.M. (2017). Method of model reduction and multifidelity models for solute transport in random layered porous media. Physical Review E, 96 (3). https:/doi.org/10.1103/PhysRevE.96.033314
Larche, M., Prowant, M., Bruillard, P., Hagge, T., Fifield, L.S., Hughes, M., Sun, X. (2017). A comparison of different NDE signal processing techniques based on waveform entropies applied to long fiber-graphite/epoxy-plates. Proceedings of SPIE - The International Society for Optical Engineering, 10169. https:/doi.org/10.1117/12.2260490
Firoz, J.S., Kancwala, T.A., Zalewskr, M., Barnas, M., Lumsdaine, A. (2017). Distributed control: The benefits of eliminating global synchronization via effective scheduling: In the context of graph applications. Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPOPP, 441-442. https:/doi.org/10.1145/3018743.3019036
Shekar, V., Fiondella, L., Chatterjee, S., Halappanavar, M. (2017). Quantifying economic and environmental impacts of transportation network disruptions with dynamic traffic simulation. 2017 IEEE International Symposium on Technologies for Homeland Security, HST 2017. https:/doi.org/10.1109/THS.2017.7943472
Shippert, T., Gaustad, K. (2017). An architecture for consolidating multidimensional time-series data onto a common coordinate grid. Earth Science Informatics, 10 (2),247-256. https:/doi.org/10.1007/s12145-016-0285-z
Dunning, T.H. (2017). Foreword. Exascale Scientific Applications: Scalability and Performance Portability, xi-xii. https:/doi.org/10.1201/b21930
Ren, B., Krishnamoorthy, S., Agrawal, K., Kulkarni, M. (2017). Exploiting Vector and Multicore Parallelism for Recursive, Data- and Task-Parallel Programs. ACM SIGPLAN Notices, 52 (8),117-130. https:/doi.org/10.1145/3018743.3018763
Tumeo, A., Halappanavar, M., Feo, J. (2017). GraML 17 first workshop on the intersection of graph algorithms and machine learning. Proceedings - 2017 IEEE 31st International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017, 1529-1530. https:/doi.org/10.1109/IPDPSW.2017.217
Tumeo, A., Feo, J., Villa, O. (2017). Foreword. Proceedings of IA3 2016 - 6th Workshop on Irregular Applications: Architectures and Algorithms, Held in conjunction with SC 2016: The International Conference for High Performance Computing, Networking, Storage and Analysis, v-vi. https:/doi.org/10.1109/IA3.2016.004
Castellana, V.G., Tumeo, A., Minutoli, M., Lattuada, M., Ferrandi, F. (2017). Considerations on the use of custom accelerators for big data analytics. Big Data Management and Processing ,279-296. https:/doi.org/10.1201/9781315154008
Lifflander, J., Krishnamoorthy, S. (2017). Cache locality optimization for recursive programs. ACM SIGPLAN Notices, 52 (6),1-16. https:/doi.org/10.1145/3062341.3062385
Rajbhandari, S., Rastello, F., Kowalski, K., Krishnamoorthy, S., Sadayappan, P. (2017). Optimizing the Four-Index Integral Transform Using Data Movement Lower Bounds Analysis. ACM SIGPLAN Notices, 52 (8),327-340. https:/doi.org/10.1145/3018743.3018771
2016
Bulgac, A., Magierski, P., Roche, K.J., Stetcu, I. (2016). Induced Fission of Pu 240 within a Real-Time Microscopic Framework. Physical Review Letters, 116 (12). https:/doi.org/10.1103/PhysRevLett.116.122504
Yang, X., Mehmani, Y., Perkins, W.A., Pasquali, A., Schönherr, M., Kim, K., Perego, M., Parks, M.L., Trask, N., Balhoff, M.T., Richmond, M.C., Geier, M., Krafczyk, M., Luo, L.-S., Tartakovsky, A.M., Scheibe, T.D. (2016). Intercomparison of 3D pore-scale flow and solute transport simulation methods. Advances in Water Resources, 95, 176-189. https:/doi.org/10.1016/j.advwatres.2015.09.015
Tartakovsky, A.M., Panchenko, A. (2016). Pairwise Force Smoothed Particle Hydrodynamics model for multiphase flow: Surface tension and contact line dynamics. Journal of Computational Physics, 305, 1119-1146. https:/doi.org/10.1016/j.jcp.2015.08.037
Tartakovsky, A.M., Trask, N., Pan, K., Jones, B., Pan, W., Williams, J.R. (2016). Smoothed particle hydrodynamics and its applications for multiphase flow and reactive transport in porous media. Computational Geosciences, 20 (4),807-834. https:/doi.org/10.1007/s10596-015-9468-9
Cheng, G., Choi, K.S., Hu, X., Sun, X. (2016). Determining individual phase properties in a multi-phase Q&P steel using multi-scale indentation tests. Materials Science and Engineering A, 652, 384-395. https:/doi.org/10.1016/j.msea.2015.11.072
Willow, S.Y., Zeng, X.C., Xantheas, S.S., Kim, K.S., Hirata, S. (2016). Why Is MP2-Water ''Cooler'' and ''Denser'' than DFT-Water?. Journal of Physical Chemistry Letters, 7 (4),680-684. https:/doi.org/10.1021/acs.jpclett.5b02430
Miliordos, E., Xantheas, S.S. (2016). The origin of the reactivity of the criegee intermediate: Implications for atmospheric particle growth. Angewandte Chemie - International Edition, 55 (3),1015-1019. https:/doi.org/10.1002/anie.201509685
Dunning, T.H., Xu, L.T., Takeshita, T.Y., Lindquist, B.A. (2016). Insights into the Electronic Structure of Molecules from Generalized Valence Bond Theory. Journal of Physical Chemistry A, 120 (11),1763-1778. https:/doi.org/10.1021/acs.jpca.5b12335
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