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Michael Mascagni
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- affiliation: Florida State University, Tallahassee, FL, USA
- affiliation: National Institute of Standards and Technology, Gaithersburg, MD, USA
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2020 – today
- 2023
- [j46]Maryam Alsolami, Michael Mascagni:
A Metropolis random walk algorithm to estimate a lower bound of the star discrepancy. Monte Carlo Methods Appl. 29(2): 161-171 (2023) - [j45]Bolong Zhang, Michael Mascagni:
Pass-efficient randomized LU algorithms for computing low-rank matrix approximation. Monte Carlo Methods Appl. 29(3): 181-202 (2023) - 2022
- [j44]Haifa Aldossari, Michael Mascagni:
Scrambling additive lagged-Fibonacci generators. Monte Carlo Methods Appl. 28(3): 199-210 (2022) - [j43]Maryam Alsolami, Michael Mascagni:
A random walk algorithm to estimate a lower bound of the star discrepancy. Monte Carlo Methods Appl. 28(4): 341-348 (2022) - 2020
- [j42]Walid Keyrouz, Michael Mascagni:
CRE2019 Special Issue Introduction IJHPCA. Int. J. High Perform. Comput. Appl. 34(5) (2020) - [j41]Wilfredo Blanco, Paulo H. Lopes, Anderson Abner de S. Souza, Michael Mascagni:
Non-replicability circumstances in a neural network model with Hodgkin-Huxley-type neurons. J. Comput. Neurosci. 48(3): 357-363 (2020) - [j40]W. John Thrasher, Michael Mascagni:
Examining sharp restart in a Monte Carlo method for the linearized Poisson-Boltzmann equation. Monte Carlo Methods Appl. 26(3): 223-244 (2020) - [j39]Hao Ji, Michael Mascagni, Yaohang Li:
Gaussian variant of Freivalds' algorithm for efficient and reliable matrix product verification. Monte Carlo Methods Appl. 26(4): 273-284 (2020) - [i2]Bolong Zhang, Michael Mascagni:
Pass-Efficient Randomized LU Algorithms for Computing Low-Rank Matrix Approximation. CoRR abs/2002.07138 (2020)
2010 – 2019
- 2019
- [j38]Lizhen Shi, Xiandong Meng, Elizabeth Tseng, Michael Mascagni, Zhong Wang:
SpaRC: scalable sequence clustering using Apache Spark. Bioinform. 35(5): 760-768 (2019) - [j37]Michael Mascagni:
CRE2017 Special Issue Introduction IJHPCA. Int. J. High Perform. Comput. Appl. 33(5) (2019) - [j36]Manal Bayousef, Michael Mascagni:
A computational investigation of the optimal Halton sequence in QMC applications. Monte Carlo Methods Appl. 25(3): 187-207 (2019) - [j35]Preston Hamlin, W. John Thrasher, Walid Keyrouz, Michael Mascagni:
Geometry entrapment in Walk-on-Subdomains. Monte Carlo Methods Appl. 25(4): 329-340 (2019) - [j34]Bolong Zhang, Wenjian Yu, Michael Mascagni:
Revisiting Kac's method: A Monte Carlo algorithm for solving the Telegrapher's equations. Math. Comput. Simul. 156: 178-193 (2019) - [c30]Michael Mascagni:
Three Numerical Reproducibility Issues That Can Be Explained as Round-Off Error. ISC Workshops 2019: 452-462 - 2017
- [j33]Asia Aljahdali, Michael Mascagni:
Feistel-inspired scrambling improves the quality of linear congruential generators. Monte Carlo Methods Appl. 23(2): 89 (2017) - [j32]Christopher Ogden, Michael Mascagni:
The Impact of Soft Error Event Topography on the Reliability of Computer Memories. IEEE Trans. Reliab. 66(4): 966-979 (2017) - [c29]Yaohang Li, Ravi Mukkamala, Michael Mascagni:
Validating the Correctness of Outsourced Computational Tasks Using Pseudorandom Number Generators. DASC/PiCom/DataCom/CyberSciTech 2017: 391-398 - [i1]Hao Ji, Michael Mascagni, Yaohang Li:
Gaussian Variant of Freivalds' Algorithm for Efficient and Reliable Matrix Product Verification. CoRR abs/1705.10449 (2017) - 2016
- [c28]Zhezhao Xu, Wenjian Yu, Chao Zhang, Bolong Zhang, Meijuan Lu, Michael Mascagni:
A Parallel Random Walk Solver for the Capacitance Calculation Problem in Touchscreen Design. ACM Great Lakes Symposium on VLSI 2016: 99-104 - [c27]Derek Juba, Walid Keyrouz, Michael Mascagni, Mary Brady:
Acceleration and Parallelization of ZENO/Walk-on-Spheres. ICCS 2016: 269-278 - 2015
- [j31]Timothy D. Andersen, Michael Mascagni:
Memory efficient lagged-Fibonacci random number generators for GPU supercomputing. Monte Carlo Methods Appl. 21(2): 163-174 (2015) - 2014
- [j30]Michael Mascagni, Yue Qiu, Lin-Yee Hin:
High performance computing in quantitative finance: A review from the pseudo-random number generator perspective. Monte Carlo Methods Appl. 20(2): 101-120 (2014) - 2013
- [j29]Michael Mascagni, Lin-Yee Hin:
Parallel pseudo-random number generators: A derivative pricing perspective with the Heston stochastic volatility model. Monte Carlo Methods Appl. 19(2): 77-105 (2013) - [j28]Hao Ji, Michael Mascagni, Yaohang Li:
Convergence Analysis of Markov Chain Monte Carlo Linear Solvers Using Ulam-von Neumann Algorithm. SIAM J. Numer. Anal. 51(4): 2107-2122 (2013) - 2012
- [j27]Michael Mascagni, Lin-Yee Hin:
Parallel random number generators in Monte Carlo derivative pricing: An application-based test. Monte Carlo Methods Appl. 18(2): 161-179 (2012) - 2010
- [j26]Chi-Ok Hwang, Michael Mascagni, Taeyoung Won:
Monte Carlo methods for computing the capacitance of the unit cube. Math. Comput. Simul. 80(6): 1089-1095 (2010) - [j25]Abdujabor Rasulov, Gulnora Raimova, Michael Mascagni:
Monte Carlo solution of Cauchy problem for a nonlinear parabolic equation. Math. Comput. Simul. 80(6): 1118-1123 (2010)
2000 – 2009
- 2009
- [j24]Michael Mascagni, Haohai Yu:
Scrambled Soboĺ sequences via permutation. Monte Carlo Methods Appl. 15(4): 311-332 (2009) - [j23]Yaohang Li, Michael Mascagni, Andrey Gorin:
A decentralized parallel implementation for parallel tempering algorithm. Parallel Comput. 35(5): 269-283 (2009) - 2008
- [c26]Michael Mascagni:
Random Number Generation for serial, parallel, distributed, and Grid-based financial computations. IPDPS 2008: 1 - 2007
- [c25]Hongmei Chi, Michael Mascagni:
Efficient Generation of Parallel Quasirandom Faure Sequences Via Scrambling. International Conference on Computational Science (1) 2007: 723-730 - [c24]Yaohang Li, Michael Mascagni, Andrey Gorin:
Decentralized Replica Exchange Parallel Tempering: An Efficient Implementation of Parallel Tempering Using MPI and SPRNG. ICCSA (3) 2007: 507-519 - 2005
- [j22]Yaohang Li, Michael Mascagni:
Grid-based Quasi-Monte Carlo Applications. Monte Carlo Methods Appl. 11(1): 39-55 (2005) - [j21]Hongmei Chi, Michael Mascagni, T. Warnock:
On the optimal Halton sequence. Math. Comput. Simul. 70(1): 9-21 (2005) - [c23]Charles Fleming, Michael Mascagni, Nikolai A. Simonov:
An Efficient Monte Carlo Approach for Solving Linear Problems in Biomolecular Electrostatics. International Conference on Computational Science (3) 2005: 760-765 - [c22]Hongmei Chi, Peter Beerli, Deidre W. Evans, Michael Mascagni:
On the Scrambled Sobol Sequence. International Conference on Computational Science (3) 2005: 775-782 - 2004
- [j20]Aneta Karaivanova, Michael Mascagni, Nikolai A. Simonov:
Parallel Quasirandom Walks on the Boundary. Monte Carlo Methods Appl. 10(3-4): 311-319 (2004) - [j19]Michael Mascagni, Hongmei Chi:
On the Scrambled Halton Sequence. Monte Carlo Methods Appl. 10(3-4): 435-442 (2004) - [j18]Abdujabor Rasulov, Aneta Karaivanova, Michael Mascagni:
Quasirandom Sequences in Branching Random Walks. Monte Carlo Methods Appl. 10(3-4): 551-558 (2004) - [j17]Nikolai A. Simonov, Michael Mascagni:
Random Walk Algorithms for Estimating Effective Properties of Digitized Porous Media. Monte Carlo Methods Appl. 10(3-4): 599-608 (2004) - [j16]Yaohang Li, Michael Mascagni, Robert A. van Engelen, Qin Cai:
A Grid Workflow-based Monte Carlo Simultation Environment. Neural Parallel Sci. Comput. 12(3): 439-454 (2004) - [j15]Michael Mascagni, Ashok Srinivasan:
Parameterizing parallel multiplicative lagged-Fibonacci generators. Parallel Comput. 30(5-6): 899-916 (2004) - [j14]Michael Mascagni, Hongmei Chi:
Parallel linear congruential generators with Sophie-Germain moduli. Parallel Comput. 30(11): 1217-1231 (2004) - [j13]Michael Mascagni, Nikolai A. Simonov:
Monte Carlo Methods for Calculating Some Physical Properties of Large Molecules. SIAM J. Sci. Comput. 26(1): 339-357 (2004) - 2003
- [j12]Yaohang Li, Michael Mascagni:
Analysis of Large-Scale Grid-Based Monte Carlo Applications. Int. J. High Perform. Comput. Appl. 17(4): 369-382 (2003) - [j11]Chi-Ok Hwang, Michael Mascagni, James A. Given:
A Feynman-Kac path-integral implementation for Poisson's equation using an h-conditioned Green's function. Math. Comput. Simul. 62(3-6): 347-355 (2003) - [j10]Michael Mascagni, Chi-Ok Hwang:
epsilon-Shell error analysis for "Walk On Spheres" algorithms. Math. Comput. Simul. 63(2): 93-104 (2003) - [j9]Chi-Ok Hwang, Michael Mascagni:
Analysis and comparison of Green's function first-passage algorithms with "Walk on Spheres" algorithms. Math. Comput. Simul. 63(6): 605-613 (2003) - [j8]Ashok Srinivasan, Michael Mascagni, David Ceperley:
Testing parallel random number generators. Parallel Comput. 29(1): 69-94 (2003) - [c21]Yaohang Li, Michael Mascagni:
Improving Performance via Computational Replication on a Large-Scale Computational Grid. CCGRID 2003: 442-448 - [c20]Yaohang Li, Michael Mascagni, Michael H. Peter:
Grid-based Nonequilibrium Multiple-Time Scale Molecular Dynamics/Brownian Dynamics Simulations of Ligand-Receptor Interactions in Structured Protein Systems. CCGRID 2003: 568-573 - [c19]Michael Mascagni, Nikolai A. Simonov:
Monte Carlo Method for Calculating the Electrostatic Energy of a Molecule. International Conference on Computational Science 2003: 63-74 - [c18]Michael Mascagni, Yaohang Li:
Computational Infrastructure for Parallel, Distributed, and Grid-Based Monte Carlo Computations. LSSC 2003: 39-52 - [c17]Aneta Karaivanova, Michael Mascagni, Nikolai A. Simonov:
Solving BVPs Using Quasirandom Walks on the Boundary. LSSC 2003: 162-169 - [c16]Yaohang Li, Michael Mascagni, Robert van Engelen:
GCIMCA: A Globus and SPRNG Implementation of a Grid-Computing Infrastructure for Monte Carlo Applications. PDPTA 2003: 71-76 - 2002
- [c15]Yaohang Li, Michael Mascagni:
Grid-Based Monte Carlo Application. GRID 2002: 13-24 - [c14]Michael Mascagni, Aneta Karaivanova:
A Parallel Quasi-Monte Carlo Method for Solving Systems of Linear Equations. International Conference on Computational Science (2) 2002: 598-608 - [c13]Ashok Srinivasan, Michael Mascagni:
Monte Carlo Techniques for Estimating the Fiedler Vector in Graph Applications. International Conference on Computational Science (2) 2002: 635-645 - [c12]Michael Mascagni, Aneta Karaivanova:
A Monte Carlo Approach for Finding More than One Eigenpair. Numerical Methods and Application 2002: 123-131 - 2001
- [j7]Chi-Ok Hwang, Michael Mascagni, James A. Given:
Rapid Diffusion Monte Carlo Algorithms for Fluid Dynamic Permeability. Monte Carlo Methods Appl. 7(3-4): 213-222 (2001) - [j6]Michael Mascagni, Aneta Karaivanova, Yaohang Li:
A Quasi-Monte Carlo Method for Elliptic Boundary Value Problems. Monte Carlo Methods Appl. 7(3-4): 283-294 (2001) - [c11]Chi-Ok Hwang, Michael Mascagni:
A Feynman-Kac Path-Integral Implementation for Poisson's Equation. International Conference on Computational Science (1) 2001: 1282-1288 - [c10]James A. Given, Michael Mascagni, Chi-Ok Hwang:
Continuous Path Brownian Trajectories for Diffusion Monte Carlo via First- and Last-Passage Distributions. LSSC 2001: 46-57 - 2000
- [j5]Michael Mascagni, Ashok Srinivasan:
Algorithm 806: SPRNG: a scalable library for pseudorandom number generation. ACM Trans. Math. Softw. 26(3): 436-461 (2000) - [j4]Michael Mascagni, Ashok Srinivasan:
Corrigendum: Algorithm 806: SPRNG: a scalable library for pseudorandom number generation. ACM Trans. Math. Softw. 26(4): 618-619 (2000) - [c9]Mike Zhou, Michael Mascagni:
The Cycle Server: A Web Platform for Running Parallel Monte Carlo Applications on a Heterogeneous Condor Pool of Workstations. ICPP Workshops 2000: 111-118 - [c8]Michael Mascagni, Aneta Karaivanova:
Matrix Computations Using Quasirandom Sequences. NAA 2000: 552-559
1990 – 1999
- 1999
- [c7]Muhammad Z. Hydari, David Ceperley, Ashok Srinivasan, Michael Mascagni:
Classical Monte Carlo with a Fast High-Quality Pseudo Random Number Library in Java. PP 1999 - [c6]Michael Mascagni:
SPRNG: A Scalable Library for Pseudorandom Number Generation. PP 1999 - 1998
- [j3]Michael Mascagni:
Parallel Linear Congruential Generators with Prime Moduli. Parallel Comput. 24(5-6): 923-936 (1998) - 1996
- [p1]Michael Mascagni:
Parallel Weiner Integral Methods for Elliptic BVPs: A Tale of Two Architectures. Applications on Advanced Architecture Computers 1996: 27-33 - 1995
- [c5]Steven A. Cuccaro, Michael Mascagni, Daniel V. Pryor:
Techniques for Testing the Quality of Parallel Pseudorandom Number Generators. PP 1995: 279-284 - [c4]Josep Lluís Larriba-Pey, Michael Mascagni, Angel Jorba, Juan J. Navarro:
An Analysis of the Parallel Computation of Arbitrarily Branched Cable Neuron Models. PP 1995: 373-378 - [e1]David H. Bailey, Petter E. Bjørstad, John R. Gilbert, Michael Mascagni, Robert S. Schreiber, Horst D. Simon, Virginia Torczon, Layne T. Watson:
Proceedings of the Seventh SIAM Conference on Parallel Processing for Scientific Computing, PP 1995, San Francisco, California, USA, February 15-17, 1995. SIAM 1995, ISBN 0-89871-344-7 [contents] - 1994
- [j2]Arthur Sherman, Michael Mascagni:
A Gradient Random Walk Method for Two-Dimensional Reaction-Diffusion Equations. SIAM J. Sci. Comput. 15(6): 1280-1293 (1994) - [c3]Daniel V. Pryor, Steven A. Cuccaro, Michael Mascagni, M. L. Robinson:
Implementation of a portable and reproducible parallel pseudorandom number generator. SC 1994: 311-319 - 1993
- [c2]Michael Mascagni, Steven A. Cuccaro, Daniel V. Pryor, M. L. Robinson:
Recent Developments in Parallel Pseudorandom Number Generation. PPSC 1993: 524-529
1980 – 1989
- 1985
- [j1]Michael Mascagni, Willard L. Miranker:
Arithmetically improved algorithmic performance. Computing 35(2): 153-175 (1985) - [c1]Willard L. Miranker, Michael Mascagni, Siegfried M. Rump:
Case Studies for Augmented Floating-Point. Accurate Scientific Computations 1985: 86-118
Coauthor Index
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