Christie Alappat
Christie Alappat, M.Sc.
Short bio
Christie Louis Alappat graduated with a Masters degree in computational engineering from Friedrich Alexander University, Erlangen. He is currently doing his PhD under the guidance of Prof. Dr. Gerhard Wellein. Research interests include performance engineering, sparse matrix algorithms, graph algorithms, stencil algorithms and eigenvalue solvers.
Research fields
List of publications
2022
Level-based Blocking for Sparse Matrices: Sparse Matrix-Power-Vector Multiplication
In: IEEE Transactions on Parallel and Distributed Systems (2022), p. 1-18
ISSN: 1045-9219
DOI: 10.1109/TPDS.2022.3223512
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2021
Execution-Cache-Memory modeling and performance tuning of sparse matrix-vector multiplication and Lattice quantum chromodynamics on A64FX
In: Concurrency and Computation-Practice & Experience (2021)
ISSN: 1532-0626
DOI: 10.1002/cpe.6512
URL: https://onlinelibrary.wiley.com/doi/full/10.1002/cpe.6512
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YaskSite: Stencil Optimization Techniques Applied to Explicit ODE Methods on Modern Architectures
19th IEEE/ACM International Symposium on Code Generation and Optimization, CGO 2021 (Virtual, Korea, KOR, 2021-02-27 - 2021-03-03)
In: Jae W. Lee, Mary Lou Soffa, Ayal Zaks (ed.): CGO 2021 - Proceedings of the 2021 IEEE/ACM International Symposium on Code Generation and Optimization 2021
DOI: 10.1109/CGO51591.2021.9370316
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Multiway p-spectral graph cuts on Grassmann manifolds
In: Machine Learning (2021)
ISSN: 0885-6125
DOI: 10.1007/s10994-021-06108-1
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2020
A Recursive Algebraic Coloring Technique for Hardware-efficient Symmetric Sparse Matrix-vector Multiplication
In: ACM Transactions on Parallel Computing 7 (2020), Article No.: 19
ISSN: 2329-4949
DOI: 10.1145/3399732
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Understanding HPC benchmark performance on intel broadwell and cascade lake processors
35th International Conference on High Performance Computing, ISC High Performance 2020 (Frankfurt, 2020-06-22 - 2020-06-25)
In: Ponnuswamy Sadayappan, Bradford L. Chamberlain, Guido Juckeland, Hatem Ltaief (ed.): Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2020
DOI: 10.1007/978-3-030-50743-5_21
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Performance Modeling of Streaming Kernels and Sparse Matrix-Vector Multiplication on A64FX
2020 IEEE/ACM Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems, PMBS 2020 (, 2020-11-12)
In: Proceedings of PMBS 2020: Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems 2020
DOI: 10.1109/PMBS51919.2020.00006
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Bridging the architecture gap: Abstracting performance-relevant properties of modern server processors
In: Supercomputing Frontiers and Innovations 7 (2020), p. 54-78
ISSN: 2409-6008
DOI: 10.14529/jsfi200204
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2018
Applicability of the ECM performance model to explicit ODE methods on current multi-core processors
Springer Verlag, 2018
ISBN: 9783319920399
DOI: 10.1007/978-3-319-92040-5_9
URL: https://link.springer.com/chapter/10.1007/978-3-319-92040-5_9
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