Charles Lefurgy

4.5k citations
44 papers · 3.1k indexed · 1 hit paper · h-index 27

Impact in

Papers in

Charles Lefurgy

44 papers receiving 2.8k citations

Hit Papers

Optimal power allocation in server farms 2009 · 347 citations
3472009202620142020100200300

Peers

Charles Lefurgy
Comparison fields: 5 of 60
  • Hardware and Architecture 1.8k
  • Computer Networks and Communications 2.2k
  • Information Systems 1.6k
  • Electrical and Electronic Engineering 924
  • Artificial Intelligence 322
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Citations per field
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Citations per year

Countries citing papers authored by Charles Lefurgy

Since Specialization
Citations

This map shows the geographic impact of Charles Lefurgy's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Charles Lefurgy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Charles Lefurgy more than expected).

Fields of papers citing papers by Charles Lefurgy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Charles Lefurgy. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Charles Lefurgy. The network helps show where Charles Lefurgy may publish in the future.

Co-authors

The 25 scholars most cited alongside Charles Lefurgy, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Charles Lefurgy Line = papers co-authored together Charles Lefurgy links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 201919
2 20193
3 201811
4 20151
5 201516
6 20141
7 20131
8 201145
9 20101
10 200968
11 200879
12 2007221
13
Managing Power Consumption and Performance of Computing Systems Using Reinforcement Learning
200777
14 2004120
15 2002182
16 200291
17 200232
18
Efficient Execution of Compressed Programs
200031
19 199933
20 1997166

About Charles Lefurgy

Charles Lefurgy is a scholar working on Hardware and Architecture, Computer Networks and Communications, Information Systems, Electrical and Electronic Engineering and Artificial Intelligence, having authored 44 papers that have together received 3.1k indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (31 papers), Cloud Computing and Resource Management (17 papers), Low-power high-performance VLSI design (14 papers), Embedded Systems Design Techniques (10 papers), Advanced Data Storage Technologies (8 papers), Caching and Content Delivery (6 papers), Distributed systems and fault tolerance (5 papers) and Radiation Effects in Electronics (5 papers). The work is most often cited by research in Hardware and Architecture (1.8k citations), Computer Networks and Communications (2.2k citations), Information Systems (1.6k citations), Electrical and Electronic Engineering (924 citations) and Artificial Intelligence (322 citations). Charles Lefurgy has collaborated with scholars based in United States, Switzerland and Australia. Frequent co-authors include Xiaorui Wang, Karthick Rajamani, Rajarshi Das, Malcolm Ware, Anshul Gandhi, Mor Harchol‐Balter, Trevor Mudge, Freeman L. Rawson, T. Keller and Peter L. Bird. Their work appears in journals such as ACM SIGMETRICS Performance Evaluation Review, IBM Journal of Research and Development, IEEE Micro, IEEE Transactions on Parallel and Distributed Systems and Computer.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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