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D-Index & Metrics

Computer Science

D-Index
45
Citations
8066
World Ranking
7214
National Ranking
3150

Overview

Rudolf Eigenmann is affiliated with the University of Delaware in the United States. The primary area of research falls within Computer Science, featuring 22 publications, with significant focus on subfields such as Hardware and Architecture, Computer Networks and Communications, Information Systems, Information Systems and Management, and Atomic and Molecular Physics, and Optics.

The scientist's work involves various topics, including:

  • Parallel Computing and Optimization Techniques
  • Distributed and Parallel Computing Systems
  • Cloud Computing and Resource Management
  • Scientific Computing and Data Management
  • Embedded Systems Design Techniques
  • Advanced Data Storage Technologies
  • Software Engineering Research

Eigenmann has contributed to multiple recent papers, addressing diverse aspects of computing and optimization. These include:

  • Automatic and Interactive Program Parallelization Using the Cetus Source to Source Compiler Infrastructure v2.0, 2022, Electronics
  • Portal for high-precision atomic data and computation, 2025, Computer Physics Communications
  • Should AI Optimize Your Code? A Comparative Study of Classical Optimizing Compilers Versus Current Large Language Models, 2024, arXiv (Cornell University)
  • Exchanging Best Practices for Supporting Computational and Data-Intensive Research, The Xpert Network, 2022, Practice and Experience in Advanced Research Computing
  • Exchanging Best Practices and Tools for Supporting Computational and Data-Intensive Research, The Xpert Network, 2021, arXiv (Cornell University)

Frequent publication venues include:

  • arXiv (Cornell University)
  • Electronics
  • Computer Physics Communications
  • Practice and Experience in Advanced Research Computing
  • Zenodo (CERN European Organization for Nuclear Research)

Eigenmann has collaborated extensively with several coauthors. The most frequent include:

  • Parinaz Barakhshan
  • Akshay Bhosale
  • Bindiya Arora
  • M. S. Safronova
  • Miguel Romero Rosas

Best Publications

  • OpenMP to GPGPU: a compiler framework for automatic translation and optimization

    Seyong Lee;Seung-Jai Min;Rudolf Eigenmann

  • Parallel programming with Polaris

    W. Blume;R. Doallo;R. Doallo;R. Doallo;R. Eigenmann;R. Eigenmann;J. Grout

  • Automatic program parallelization

    U. Banerjee;R. Eigenmann;A. Nicolau;D.A. Padua

  • OpenMPC: Extended OpenMP Programming and Tuning for GPUs

    Seyong Lee;Rudolf Eigenmann

  • SPEComp: A New Benchmark Suite for Measuring Parallel Computer Performance

    Vishal Aslot;Max J. Domeika;Rudolf Eigenmann;Greg Gaertner

  • Cetus: A Source-to-Source Compiler Infrastructure for Multicores

    C. Dave;Hansang Bae;Seung-Jai Min;Seyong Lee

  • Cetus – An Extensible Compiler Infrastructure for Source-to-Source Transformation

    Sang Ik Lee;Troy A. Johnson;Rudolf Eigenmann

  • Fast and Effective Orchestration of Compiler Optimizations for Automatic Performance Tuning

    Zhelong Pan;Rudolf Eigenmann

  • Performance analysis pf parallelizing compilers on the Perfect Benchmarks programs

    W. Blume;R. Eigenmann

  • The range test: a dependence test for symbolic, non-linear expressions

    William Blume;Rudolf Eigenmann

  • Experience in the Automatic Parallelization of Four Perfect-Benchmark Programs

    Rudolf Eigenmann;Jay Hoeflinger;Z. Li;David A. Padua

  • Polaris: The Next Generation in Parallelizing Compilers

    Bill Blume;Rudolf Eigenmann;Keith Faigin;John Grout

  • On the automatic parallelization of the Perfect Benchmarks(R)

    R. Eigenmann;J. Hoeflinger;D. Padua

  • Min-cut program decomposition for thread-level speculation

    Troy A. Johnson;Rudolf Eigenmann;T. N. Vijaykumar

  • Idiom recognition in the Polaris parallelizing compiler

    Bill Pottenger;Rudolf Eigenmann

  • Automatic Detection of Parallelism: A grand challenge for high performance computing

    W. Blume;R. Eigenmann;J. Hoeflinger;D. Padua

  • Symbolic range propagation

    W. Blume;R. Eigenmann

  • McrEngine: a scalable checkpointing system using data-aware aggregation and compression

    Tanzima Zerin Islam;Kathryn Mohror;Saurabh Bagchi;Adam Moody

  • Towards automatic translation of OpenMP to MPI

    Ayon Basumallik;Rudolf Eigenmann

  • Polaris: Improving the Effectiveness of Parallelizing Compilers

    William Blume;Rudolf Eigenmann;Keith Faigin;John Grout

  • Automatic program parallelization : Languages and compilers

    Uptal Banerjee;R. Eigenmann;A. Nicolau;D. A. Padua

Frequent Co-Authors

David Padua
David Padua University of Illinois at Urbana-Champaign
José A. B. Fortes
José A. B. Fortes University of Florida
Samuel P. Midkiff
Samuel P. Midkiff Purdue University West Lafayette
Saurabh Bagchi
Saurabh Bagchi Purdue University West Lafayette
Lawrence Rauchwerger
Lawrence Rauchwerger University of Illinois at Urbana-Champaign
T. N. Vijaykumar
T. N. Vijaykumar Purdue University West Lafayette
Alok Choudhary
Alok Choudhary Northwestern University
Howard Jay Siegel
Howard Jay Siegel Colorado State University
Anthony A. Maciejewski
Anthony A. Maciejewski Colorado State University
Babak Falsafi
Babak Falsafi École Polytechnique Fédérale de Lausanne

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