World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
35
Citations
4943
World Ranking
11739
National Ranking
4807

David Nellans publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where David Nellans sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 61 publications — 1st percentile

1% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

David Nellans D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where David Nellans sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 35 D-Index — 20th percentile

20% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

David Nellans is affiliated with Nvidia in the United States. Their research output spans multiple domains within computer science and engineering, focusing largely on topics related to advanced computing architectures and optimization techniques.

They have contributed to several recent publications, including:

  • "GPU Domain Specialization via Composable On-Package Architecture," 2021, ACM Transactions on Architecture and Code Optimization
  • "The Architectural Implications of Distributed Reinforcement Learning on CPU-GPU Systems," 2020, arXiv (Cornell University)
  • "GPU Domain Specialization via Composable On-Package Architecture," 2021, arXiv (Cornell University)
  • "Architectural Support for Optimizing Huge Page Selection Within the OS," 2023, Zenodo (CERN European Organization for Nuclear Research)

Their frequent co-authors include:

  • Yaosheng Fu
  • Evgeny Bolotin
  • Niladrish Chatterjee
  • Stephen W. Keckler
  • Ahmet Inci

David Nellans has contributed to publications most often appearing in the following venues:

  • arXiv (Cornell University)
  • ACM Transactions on Architecture and Code Optimization
  • Zenodo (CERN European Organization for Nuclear Research)

Their main fields of study are:

  • Computer Science
  • Engineering

More specialized subfields in their research are:

  • Electrical and Electronic Engineering
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Hardware and Architecture
  • Signal Processing

Key topics covered in their work include:

  • Advanced Memory and Neural Computing
  • Ferroelectric and Negative Capacitance Devices
  • Advanced Neural Network Applications
  • Reinforcement Learning in Robotics
  • Evolutionary Algorithms and Applications
  • Parallel Computing and Optimization Techniques
  • Advanced Malware Detection Techniques

Best Publications

  • Object-based memory storage

    Anirudh Badam;David Nellans;Robert Wipfel

  • Micro-pages: increasing DRAM efficiency with locality-aware data placement

    Kshitij Sudan;Niladrish Chatterjee;David Nellans;Manu Awasthi

  • Linux block IO: introducing multi-queue SSD access on multi-core systems

    Matias Bjørling;Jens Axboe;David Nellans;Philippe Bonnet

  • Apparatus, system, and method for managing eviction of data

    David Nellans;David Atkisson;Jim Peterson;Jeremy Garff

  • Beyond block I/O: Rethinking traditional storage primitives

    Xiangyong Ouyang;David Nellans;Robert Wipfel;David Flynn

  • MCM-GPU: Multi-Chip-Module GPUs for Continued Performance Scalability

    Akhil Arunkumar;Evgeny Bolotin;Benjamin Cho;Ugljesa Milic

  • Systems and methods for atomic storage

    David Flynn;Robert Wipfel;David Nellans;John Strasser

  • Apparatus, system, and method for application direct virtual memory management

    David Nellans;Robert Wipfel

  • Handling the problems and opportunities posed by multiple on-chip memory controllers

    Manu Awasthi;David W. Nellans;Kshitij Sudan;Rajeev Balasubramonian

  • Preserving data of a volatile memory

    David Flynn;David Nellans;John Strasser;James G. Peterson

  • Page Placement Strategies for GPUs within Heterogeneous Memory Systems

    Neha Agarwal;David Nellans;Mark Stephenson;Mike O'Connor

  • Scaling the power wall: a path to exascale

    Oreste Villa;Daniel R. Johnson;Mike O'Connor;Evgeny Bolotin

  • Systems and methods for persistent address space management

    David Atkisson;David Nellans;David Flynn;Jens Axboe

  • NVBit: A Dynamic Binary Instrumentation Framework for NVIDIA GPUs

    Oreste Villa;Mark Stephenson;David Nellans;Stephen W. Keckler

  • Apparatus, system, and method for conditional and atomic storage operations

    David Flynn;David Nellans;Xiangyong Shangyong Ouyang

  • Towards high performance paged memory for GPUs

    Tianhao Zheng;David Nellans;Arslan Zulfiqar;Mark Stephenson

  • Nimble Page Management for Tiered Memory Systems

    Zi Yan;Daniel Lustig;David Nellans;Abhishek Bhattacharjee

  • Flexible software profiling of GPU architectures

    Mark Stephenson;Siva Kumar Sastry Hari;Yunsup Lee;Eiman Ebrahimi

  • Non-volatile memory interface

    David Nellans;Robert Wipfel

  • Unlocking bandwidth for GPUs in CC-NUMA systems

    Neha Agarwal;David Nellans;Mike O'Connor;Stephen W. Keckler

Frequent Co-Authors

Stephen W. Keckler
Stephen W. Keckler Nvidia (United States)
Rajeev Balasubramonian
Rajeev Balasubramonian University of Utah
Thomas F. Wenisch
Thomas F. Wenisch University of Michigan–Ann Arbor
Aamer Jaleel
Aamer Jaleel Nvidia (United States)
Mattan Erez
Mattan Erez The University of Texas at Austin
Carole-Jean Wu
Carole-Jean Wu Meta Platforms, Inc.
Puneet Gupta
Puneet Gupta University of California, Los Angeles
Diana Marculescu
Diana Marculescu The University of Texas at Austin
William J. Dally
William J. Dally Nvidia (United Kingdom)

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