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D-Index & Metrics

Computer Science

D-Index
69
Citations
19049
World Ranking
1975
National Ranking
998

Overview

Brad Calder is affiliated with Google in the United States, contributing to the fields of Computer Science, particularly focusing on Information Systems, Computer Networks and Communications, and Artificial Intelligence.

Their research encompasses a range of topics including Cloud Data Security Solutions, Security and Verification in Computing, Digital and Cyber Forensics, Cloud Computing and Resource Management, IoT and Edge/Fog Computing, and Software System Performance and Reliability.

Brad Calder has published work in several venues, most notably:

  • arXiv (Cornell University)
  • ACM Computing Surveys

Recent papers include:

  • Architectures for Protecting Cloud Data Planes, 2022, arXiv (Cornell University)
  • Deployment Archetypes for Cloud Applications, 2022, ACM Computing Surveys

Frequent coauthors are:

  • Grant Dasher
  • Ines Envid
  • Anna Berenberg

Best Publications

  • Automatically characterizing large scale program behavior

    Timothy Sherwood;Erez Perelman;Greg Hamerly;Brad Calder

  • Erasure coding in windows azure storage

    Cheng Huang;Huseyin Simitci;Yikang Xu;Aaron Ogus

  • Windows Azure Storage: a highly available cloud storage service with strong consistency

    Brad Calder;Ju Wang;Aaron Ogus;Niranjan Nilakantan

  • Basic Block Distribution Analysis to Find Periodic Behavior and Simulation Points in Applications

    Timothy Sherwood;Erez Perelman;Brad Calder

  • Phase tracking and prediction

    Timothy Sherwood;Suleyman Sair;Brad Calder

  • Deterministic memory-efficient string matching algorithms for intrusion detection

    N. Tuck;T. Sherwood;B. Calder;G. Varghese

  • Entropia: architecture and performance of an enterprise desktop grid system

    Andrew Chien;Brad Calder;Stephen Elbert;Karan Bhatia

  • SimPoint 3.0: Faster and More Flexible Program Phase Analysis

    Greg Hamerly;Erez Perelman;Jeremy Lau;Brad Calder

  • BugNet: Continuously Recording Program Execution for Deterministic Replay Debugging

    Satish Narayanasamy;Gilles Pokam;Brad Calder

  • Using SimPoint for accurate and efficient simulation

    Erez Perelman;Greg Hamerly;Michael Van Biesbrouck;Timothy Sherwood

  • Cache-conscious data placement

    Brad Calder;Chandra Krintz;Simmi John;Todd Austin

  • Discovering and exploiting program phases

    T. Sherwood;E. Perelman;G. Hamerly;S. Sair

  • Selective value prediction

    Brad Calder;Glenn Reinman;Dean M. Tullsen

  • Picking statistically valid and early simulation points

    Erez Perelman;Greg Hamerly;Brad Calder

  • Predictive sequential associative cache

    B. Calder;D. Grunwald;J. Emer

  • Automatically classifying benign and harmful data races using replay analysis

    Satish Narayanasamy;Zhenghao Wang;Jordan Tigani;Andrew Edwards

  • Value profiling

    Brad Calder;Peter Feller;Alan Eustace

  • Reducing indirect function call overhead in C++ programs

    Brad Calder;Dirk Grunwald

  • Quantifying Behavioral Differences Between C and C++ Programs

    Brad Calder;Dirk Grunwald;Benjamin Zorn

  • Procedure placement using temporal ordering information

    Nikolas Gloy;Trevor Blackwell;Michael D. Smith;Brad Calder

Frequent Co-Authors

Timothy Sherwood
Timothy Sherwood University of California, Santa Barbara
Dirk Grunwald
Dirk Grunwald University of Colorado Boulder
Dean M. Tullsen
Dean M. Tullsen University of California, San Diego
Satish Narayanasamy
Satish Narayanasamy University of Michigan–Ann Arbor
Glenn Reinman
Glenn Reinman University of California, Los Angeles
Andrew A. Chien
Andrew A. Chien University of Chicago
Todd Austin
Todd Austin University of Michigan–Ann Arbor
Lieven Eeckhout
Lieven Eeckhout Ghent University
Benjamin G. Zorn
Benjamin G. Zorn Microsoft (United States)
Jeanne Ferrante
Jeanne Ferrante University of California, San Diego

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