H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 67 Citations 16,142 189 World Ranking 1047 National Ranking 616

Research.com Recognitions

Awards & Achievements

2011 - IEEE Fellow For contributions to compiler technologies

2008 - ACM Fellow For contributions to compilers and memory management.

2006 - ACM Distinguished Member

2006 - ACM Senior Member

Overview

What is she best known for?

The fields of study she is best known for:

  • Operating system
  • Programming language
  • Compiler

Her primary areas of investigation include Parallel computing, Java, Operating system, Programming language and Compiler. The study incorporates disciplines such as Loop fission, Loop nest optimization and Loop fusion in addition to Parallel computing. Kathryn S. McKinley combines subjects such as Pointer, Object-oriented programming, Static analysis and Garbage, Garbage collection with her study of Java.

Kathryn S. McKinley regularly links together related areas like Heap in her Garbage collection studies. In general Operating system study, her work on Memory management, Dynamic software updating, Bytecode and Web server often relates to the realm of Allocator, thereby connecting several areas of interest. Her work in the fields of Compiler, such as Dynamic compilation, intersects with other areas such as Native Image Generator.

Her most cited work include:

  • The DaCapo benchmarks: java benchmarking development and analysis (1285 citations)
  • Improving data locality with loop transformations (478 citations)
  • Hoard: a scalable memory allocator for multithreaded applications (445 citations)

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

Her main research concerns Parallel computing, Programming language, Compiler, Java and Garbage collection. Her Parallel computing research incorporates elements of Code generation and Fortran. Her study on Compiler also encompasses disciplines like

  • Instruction set which connect with Execution model,
  • Latency most often made with reference to Scheduling.

Her biological study spans a wide range of topics, including Object-oriented programming, Software and Static analysis. Her Garbage collection study integrates concerns from other disciplines, such as Pointer and Memory management. Her study explores the link between Garbage and topics such as Heap that cross with problems in Data structure, Memory leak and Database.

She most often published in these fields:

  • Parallel computing (27.50%)
  • Programming language (22.50%)
  • Compiler (22.50%)

What were the highlights of her more recent work (between 2014-2020)?

  • Software (13.75%)
  • Programming paradigm (5.00%)
  • Dram (3.33%)

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

Her primary areas of study are Software, Programming paradigm, Dram, Programming language and Garbage collection. Compiler, Reactive programming, Python and Java are among the areas of Programming language where the researcher is concentrating her efforts. Her Program optimization study, which is part of a larger body of work in Compiler, is frequently linked to Graphics pipeline, bridging the gap between disciplines.

Her research in Java intersects with topics in Debugging and Perl. Her study in Garbage collection is interdisciplinary in nature, drawing from both Scalability and Memory management. Her work deals with themes such as Parallel computing and Translation lookaside buffer, which intersect with Translation.

Between 2014 and 2020, her most popular works were:

  • Redundant memory mappings for fast access to large memories (102 citations)
  • Few-to-Many: Incremental Parallelism for Reducing Tail Latency in Interactive Services (66 citations)
  • Swayam: distributed autoscaling to meet SLAs of machine learning inference services with resource efficiency (38 citations)

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

  • Operating system
  • Programming language
  • Software

Kathryn S. McKinley mainly focuses on Latency, Parallel computing, Software, Thread and Embedded system. Her Latency study incorporates themes from Multi-core processor, Scheduling and Server. The various areas that Kathryn S. McKinley examines in her Parallel computing study include Computer architecture and Physical address.

Her Software study is concerned with the larger field of Programming language. Her research integrates issues of Job shop scheduling, Distributed computing, Work stealing and Web service in her study of Thread. Her Embedded system research integrates issues from Dram, Latency, Garbage, Garbage collection and Programming paradigm.

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

The DaCapo benchmarks: java benchmarking development and analysis

Stephen M. Blackburn;Robin Garner;Chris Hoffmann;Asjad M. Khang.
conference on object-oriented programming systems, languages, and applications (2006)

1727 Citations

Improving data locality with loop transformations

Kathryn S. McKinley;Steve Carr;Chau-Wen Tseng.
ACM Transactions on Programming Languages and Systems (1996)

705 Citations

Hoard: a scalable memory allocator for multithreaded applications

Emery D. Berger;Kathryn S. McKinley;Robert D. Blumofe;Paul R. Wilson.
architectural support for programming languages and operating systems (2000)

666 Citations

Tile size selection using cache organization and data layout

Stephanie Coleman;Kathryn S. McKinley.
programming language design and implementation (1995)

544 Citations

Scaling to the end of silicon with EDGE architectures

D. Burger;S.W. Keckler;K.S. McKinley;M. Dahlin.
IEEE Computer (2004)

500 Citations

Compiler optimizations for improving data locality

Steve Carr;Kathryn S. McKinley;Chau-Wen Tseng.
architectural support for programming languages and operating systems (1994)

405 Citations

The Jikes research virtual machine project: building an open-source research community

B. Alpern;S. Augart;S. M. Blackburn;M. Butrico.
Ibm Systems Journal (2005)

329 Citations

Maximizing Loop Parallelism and Improving Data Locality via Loop Fusion and Distribution

Ken Kennedy;Kathryn S. McKinley.
languages and compilers for parallel computing (1993)

323 Citations

Myths and realities: the performance impact of garbage collection

Stephen M. Blackburn;Perry Cheng;Kathryn S. McKinley.
measurement and modeling of computer systems (2004)

306 Citations

PACER: proportional detection of data races

Michael D. Bond;Katherine E. Coons;Kathryn S. McKinley.
programming language design and implementation (2010)

267 Citations

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Best Scientists Citing Kathryn S. McKinley

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Mahmut Kandemir

Pennsylvania State University

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Walter Binder

Walter Binder

Universita della Svizzera Italiana

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J. Ramanujam

J. Ramanujam

Louisiana State University

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Ken Kennedy

Ken Kennedy

Rice University

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Onur Mutlu

Onur Mutlu

ETH Zurich

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P. Sadayappan

P. Sadayappan

University of Utah

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Alok Choudhary

Alok Choudhary

Northwestern University

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Doug Burger

Doug Burger

Microsoft (United States)

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Michael F. P. O'Boyle

Michael F. P. O'Boyle

University of Edinburgh

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Emery D. Berger

Emery D. Berger

University of Massachusetts Amherst

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Chau-Wen Tseng

Chau-Wen Tseng

University of Maryland, College Park

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Kevin C. Gower

Kevin C. Gower

IBM (United States)

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Albert Cohen

Albert Cohen

Google (United States)

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David Atienza

David Atienza

École Polytechnique Fédérale de Lausanne

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Atanas Rountev

Atanas Rountev

The Ohio State University

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Mary Hall

Mary Hall

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