D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 71 Citations 15,738 337 World Ranking 789 National Ranking 476

Research.com Recognitions

Awards & Achievements

2015 - IEEE Fellow For contributions to parallel programming tools for high-performance computing

Overview

What is he best known for?

The fields of study he is best known for:

  • Operating system
  • Programming language
  • Parallel computing

His main research concerns Parallel computing, Compiler, Distributed computing, Code generation and Nested loop join. His work deals with themes such as Automatic parallelization and Stencil, which intersect with Parallel computing. His Compiler study incorporates themes from Parallelism, SIMD and Source code.

The Distributed computing study combines topics in areas such as Scheduling, Queueing theory, Scalability and Supercomputer. His Code generation research is multidisciplinary, incorporating perspectives in Tensor contraction, Computation and Computer engineering. P. Sadayappan has researched Nested loop join in several fields, including Deadlock, Loop and Affine transformation.

His most cited work include:

  • A practical automatic polyhedral parallelizer and locality optimizer (678 citations)
  • Gaining insights into multicore cache partitioning: Bridging the gap between simulation and real systems (319 citations)
  • Scalable work stealing (209 citations)

What are the main themes of his work throughout his whole career to date?

Parallel computing, Distributed computing, Computation, Algorithm and Compiler are his primary areas of study. His work carried out in the field of Parallel computing brings together such families of science as Sparse matrix and Code generation. His Code generation course of study focuses on CUDA and General-purpose computing on graphics processing units.

His research integrates issues of Scalability and Job scheduler, Scheduling, Rate-monotonic scheduling, Fair-share scheduling in his study of Distributed computing. His work in Algorithm addresses subjects such as Loop fusion, which are connected to disciplines such as Loop tiling. His biological study spans a wide range of topics, including Stencil and SIMD.

He most often published in these fields:

  • Parallel computing (58.25%)
  • Distributed computing (19.10%)
  • Computation (14.86%)

What were the highlights of his more recent work (between 2013-2021)?

  • Parallel computing (58.25%)
  • Computation (14.86%)
  • Compiler (13.68%)

In recent papers he was focusing on the following fields of study:

P. Sadayappan mainly investigates Parallel computing, Computation, Compiler, Algorithm and Sparse matrix. His Parallel computing study integrates concerns from other disciplines, such as Kernel and Stencil. P. Sadayappan combines subjects such as Computational complexity theory, Tensor representation, Representation and Affine transformation with his study of Computation.

His Compiler research includes elements of Class, Redundancy and Error detection and correction. His Algorithm research incorporates elements of Memory hierarchy, Permutation, Sequence, Bottleneck and Speedup. As a part of the same scientific family, P. Sadayappan mostly works in the field of Sparse matrix, focusing on Multiplication and, on occasion, Matrix multiplication.

Between 2013 and 2021, his most popular works were:

  • Fast sparse matrix-vector multiplication on GPUs for graph applications (106 citations)
  • Hybrid Hexagonal/Classical Tiling for GPUs (78 citations)
  • Automatic Selection of Sparse Matrix Representation on GPUs (71 citations)

In his most recent research, the most cited papers focused on:

  • Operating system
  • Programming language
  • Parallel computing

P. Sadayappan mainly investigates Parallel computing, Stencil, Computation, Code generation and Compiler. His research in Parallel computing intersects with topics in Sparse matrix and Kernel. His Stencil study combines topics in areas such as Statement, Data parallelism, Loop unrolling and Shared memory.

The study incorporates disciplines such as Degree of parallelism, Tensor representation, Fiber and Finite volume method in addition to Computation. His Code generation research incorporates themes from Scalability, Dataflow, Concurrency and Adaptive mesh refinement. His Compiler study combines topics from a wide range of disciplines, such as Retiming, Associative property, Pointer, Dependence analysis and Class.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

A practical automatic polyhedral parallelizer and locality optimizer

Uday Bondhugula;Albert Hartono;J. Ramanujam;P. Sadayappan.
programming language design and implementation (2008)

1054 Citations

Gaining insights into multicore cache partitioning: Bridging the gap between simulation and real systems

Jiang Lin;Qingda Lu;Xiaoning Ding;Zhao Zhang.
high-performance computer architecture (2008)

491 Citations

Scalable work stealing

James Dinan;D. Brian Larkins;P. Sadayappan;Sriram Krishnamoorthy.
ieee international conference on high performance computing data and analytics (2009)

343 Citations

Automatic C-to-CUDA code generation for affine programs

Muthu Manikandan Baskaran;J. Ramanujam;P. Sadayappan.
compiler construction (2010)

319 Citations

Automatic transformations for communication-minimized parallelization and locality optimization in the polyhedral model

Uday Bondhugula;Muthu Baskaran;Sriram Krishnamoorthy;J. Ramanujam.
compiler construction (2008)

300 Citations

High-performance code generation for stencil computations on GPU architectures

Justin Holewinski;Louis-Noël Pouchet;P. Sadayappan.
international conference on supercomputing (2012)

290 Citations

A compiler framework for optimization of affine loop nests for gpgpus

Muthu Manikandan Baskaran;Uday Bondhugula;Sriram Krishnamoorthy;J. Ramanujam.
international conference on supercomputing (2008)

273 Citations

Effective automatic parallelization of stencil computations

Sriram Krishnamoorthy;Muthu Baskaran;Uday Bondhugula;J. Ramanujam.
programming language design and implementation (2007)

269 Citations

Compile-time techniques for data distribution in distributed memory machines

J. Ramanujam;P. Sadayappan.
IEEE Transactions on Parallel and Distributed Systems (1991)

250 Citations

Scalable I/O forwarding framework for high-performance computing systems

Nawab Ali;Philip Carns;Kamil Iskra;Dries Kimpe.
international conference on cluster computing (2009)

242 Citations

Best Scientists Citing P. Sadayappan

Mahmut Kandemir

Mahmut Kandemir

Pennsylvania State University

Publications: 59

Jack Dongarra

Jack Dongarra

University of Tennessee at Knoxville

Publications: 48

Dhabaleswar K. Panda

Dhabaleswar K. Panda

The Ohio State University

Publications: 43

J. Ramanujam

J. Ramanujam

Louisiana State University

Publications: 42

Yves Robert

Yves Robert

École Normale Supérieure de Lyon

Publications: 40

Mary Hall

Mary Hall

University of Utah

Publications: 35

Albert Cohen

Albert Cohen

Google (United States)

Publications: 33

William Gropp

William Gropp

University of Illinois at Urbana-Champaign

Publications: 33

Vivek Sarkar

Vivek Sarkar

Georgia Institute of Technology

Publications: 33

Alok Choudhary

Alok Choudhary

Northwestern University

Publications: 32

Laxmikant V. Kale

Laxmikant V. Kale

University of Illinois at Urbana-Champaign

Publications: 32

Jingling Xue

Jingling Xue

UNSW Sydney

Publications: 31

David Padua

David Padua

University of Illinois at Urbana-Champaign

Publications: 31

Jason Cong

Jason Cong

University of California, Los Angeles

Publications: 30

Rajkumar Buyya

Rajkumar Buyya

University of Melbourne

Publications: 29

Ching-Hsien Hsu

Ching-Hsien Hsu

Asian University

Publications: 26

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.

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