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Rudolf Eigenmann
Researcher at University of Delaware
Publications - 187
Citations - 6116
Rudolf Eigenmann is an academic researcher from University of Delaware. The author has contributed to research in topics: Compiler & Automatic parallelization. The author has an hindex of 40, co-authored 183 publications receiving 5914 citations. Previous affiliations of Rudolf Eigenmann include Lawrence Livermore National Laboratory & Purdue University.
Papers
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Proceedings ArticleDOI
OpenMP to GPGPU: a compiler framework for automatic translation and optimization
TL;DR: This paper presents a compiler framework for automatic source-to-source translation of standard OpenMP applications into CUDA-based GPGPU applications, and identifies several key transformation techniques, which enable efficient GPU global memory access, to achieve high performance.
Journal ArticleDOI
Parallel programming with Polaris
William Blume,Ramón Doallo,Ramón Doallo,Ramón Doallo,Rudolf Eigenmann,Rudolf Eigenmann,John Grout,Jay Hoeflinger,Thomas R. Lawrence +8 more
TL;DR: Polaris, an experimental translator of conventional Fortran programs that target machines such as the Cray T3D, is discussed, which would liberate programmers from the complexities of explicit, machine oriented parallel programming.
Journal ArticleDOI
Automatic program parallelization
TL;DR: An overview of automatic program parallelization techniques is presented, which covers dependence analysis techniques, followed by a discussion of program transformations, including straight-line code parallelization, do-loop transformations, and parallelization of recursive routines.
Proceedings ArticleDOI
OpenMPC: Extended OpenMP Programming and Tuning for GPUs
Seyong Lee,Rudolf Eigenmann +1 more
TL;DR: This paper has developed a fully automatic compilation and user-assisted tuning system supporting OpenMPC, which builds on OpenMP to provide an abstraction of the complex CUDA programming model and offers high-level controls of the involved parameters and optimizations.
Book ChapterDOI
SPEComp: A New Benchmark Suite for Measuring Parallel Computer Performance
TL;DR: An overview of a new benchmark suite for parallel computers, SPEComp, which targets mid-size parallel servers and includes a number of science/engineering and data processing applications, is presented.