H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 60 Citations 15,341 201 World Ranking 1582 National Ranking 881

Research.com Recognitions

Awards & Achievements

2011 - ACM Fellow For contributions to parallel computing.

Overview

What is he best known for?

The fields of study he is best known for:

  • Programming language
  • Algorithm
  • Operating system

Guy E. Blelloch mostly deals with Parallel computing, Parallel algorithm, Theoretical computer science, NESL and Programming language. In general Parallel computing, his work in Cache is often linked to Sparse matrix linking many areas of study. The Parallel algorithm study combines topics in areas such as Parallel programming model and Bowyer–Watson algorithm, Delaunay triangulation.

His study in Theoretical computer science is interdisciplinary in nature, drawing from both Graph, Data structure, Graph and Computation. In his study, Computer programming is inextricably linked to Parallel language, which falls within the broad field of NESL. His work on Software portability, Programming paradigm and Programmer as part of his general Programming language study is frequently connected to Key, thereby bridging the divide between different branches of science.

His most cited work include:

  • GraphChi: large-scale graph computation on just a PC (799 citations)
  • Ligra: a lightweight graph processing framework for shared memory (520 citations)
  • Vector models for data-parallel computing (453 citations)

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

His primary areas of investigation include Parallel computing, Parallel algorithm, Algorithm, Theoretical computer science and Data structure. In his research on the topic of Parallel computing, Distributed computing is strongly related with Scheduling. His research investigates the connection between Parallel algorithm and topics such as Combinatorics that intersect with problems in Sequential algorithm.

His Algorithm study combines topics from a wide range of disciplines, such as Graph and Binary number. Guy E. Blelloch interconnects Programming language, Data type, Algorithm design, Correctness and Set in the investigation of issues within Theoretical computer science. His Data structure research integrates issues from Discrete mathematics, Binary logarithm, Tree structure and Concurrency.

He most often published in these fields:

  • Parallel computing (38.25%)
  • Parallel algorithm (27.37%)
  • Algorithm (23.51%)

What were the highlights of his more recent work (between 2017-2021)?

  • Data structure (17.89%)
  • Parallel algorithm (27.37%)
  • Parallel computing (38.25%)

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

Guy E. Blelloch mainly focuses on Data structure, Parallel algorithm, Parallel computing, Theoretical computer science and Algorithm. His biological study spans a wide range of topics, including Tree structure, Speedup and Concurrency. His Parallel algorithm study combines topics in areas such as Binary logarithm, Sorting, Connectivity, Auxiliary memory and Intersection.

His Parallel computing research includes elements of Scalability, Computational geometry and State. His Theoretical computer science research incorporates themes from Algorithm design and Set. He has included themes like Graph and Parallelism in his Algorithm study.

Between 2017 and 2021, his most popular works were:

  • Theoretically Efficient Parallel Graph Algorithms Can Be Fast and Scalable (43 citations)
  • Low-latency graph streaming using compressed purely-functional trees (18 citations)
  • Delay-Free Concurrency on Faulty Persistent Memory (17 citations)

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

  • Programming language
  • Algorithm
  • Operating system

Parallel algorithm, Parallel computing, Data structure, Graph and Binary logarithm are his primary areas of study. His research integrates issues of Overhead, Sorting, Connectivity, Auxiliary memory and Intersection in his study of Parallel algorithm. His Parallel computing study incorporates themes from Scalability and Process.

His studies in Data structure integrate themes in fields like Tree, Set, Range tree and Binary tree. He combines subjects such as Search tree and Purely functional with his study of Graph. His work in Concurrency addresses subjects such as Isolation, which are connected to disciplines such as Theoretical computer science.

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.

Top Publications

GraphChi: large-scale graph computation on just a PC

Aapo Kyrola;Guy Blelloch;Carlos Guestrin.
operating systems design and implementation (2012)

1169 Citations

Vector models for data-parallel computing

Guy E. Blelloch.
(1990)

820 Citations

Scans as primitive parallel operations

G.E. Blelloch.
IEEE Transactions on Computers (1989)

721 Citations

Ligra: a lightweight graph processing framework for shared memory

Julian Shun;Guy E. Blelloch.
acm sigplan symposium on principles and practice of parallel programming (2013)

700 Citations

Programming parallel algorithms

Guy E. Blelloch.
Communications of The ACM (1996)

586 Citations

Prefix sums and their applications

Guy E. Blelloch.
(2004)

537 Citations

Implementation of a portable nested data-parallel language

Guy E. Blelloch;Jonathan C. Hardwick;Jay Sipelstein;Marco Zagha.
Journal of Parallel and Distributed Computing (1994)

518 Citations

A comparison of sorting algorithms for the connection machine CM-2

Guy E. Blelloch;Charles E. Leiserson;Bruce M. Maggs;C. Greg Plaxton.
acm symposium on parallel algorithms and architectures (1991)

466 Citations

The data locality of work stealing

Umut A. Acar;Guy E. Blelloch;Robert D. Blumofe.
acm symposium on parallel algorithms and architectures (2000)

368 Citations

NESL: A Nested Data-Parallel Language

Guy E. Blelloch.
(1992)

360 Citations

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

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