Siva Rajamanickam

Siva Rajamanickam

Researcher

Sandia National Laboratories

Siva Rajamanickam is a distinguished member of technical staff at Sandia National Laboratories. His interest is broadly in the areas of high performance computing, specifically in machine learning for science, performance portable algorithms, codesign of algorithms and architectures and combinatorial scientific computing. Most of his works are in the intersection of these areas where interesting opportunities lie to solve problems that are of importance to computational science use cases.

Interests
  • High Performance Computing
  • Machine Learning for Science
  • Performance Portable Algorithms
  • Codesign of Algorithms and Architectures
  • Combinatorial Scientific Computing
Education
  • PhD in Computer Science and Engineering, 2009

    University of Florida

  • BE in Computer Science and Engineering, 1999

    Madurai Kamaraj University

Recent Publications

(2023). TenSQL: An SQL Database Built on GraphBLAS. 2023 IEEE High Performance extreme Computing Conference (HPEC).

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(2023). A Comparison of Spectral and Spatial Graph Convolutional Neural Network Kernels Using GraphSAGE-Sparse. 2023 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW).

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(2023). An Experimental Study of Two-level Schwarz Domain-Decomposition Preconditioners on GPUs. 2023 IEEE International Parallel and Distributed Processing Symposium (IPDPS).

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(2023). Performance Portable Batched Sparse Linear Solvers. IEEE Transactions on Parallel and Distributed Systems.

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(2022). High-Performance GMRES Multi-Precision Benchmark: Design, Performance, and Challenges. 2022 IEEE/ACM International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS).

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Projects

Instead of listing all the funded projects that I lead, this is a summary of all the areas I am interested in. All my projects fall into one or more of these areas.

Software

Instead of listing all the software projects that I am involved with, this is a summary of large frameworks that I contribute to.

Contact