Federico D. Sacerdoti
- Computational Theory and Mathematics top 0.5%
- Molecular Biology top 5%
- Toxicology top 5%
- Organic Chemistry top 5%
- Pharmacology top 5%
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- Advanced Data Storage Technologies 5
- Distributed and Parallel Computing Systems 4
- Distributed systems and fault tolerance 2
- Interconnection Networks and Systems 2
- Peer-to-Peer Network Technologies 1
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- Parallel Computing and Optimization Techniques 4
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- Scientific Computing and Data Management 2
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- Low-power high-performance VLSI design 1
- Co-authors
- Ron O. DrorDavid E. ShawK. J. BowersYibing ShanJohn L. KlepeisHuafeng XuIstván KolossváryMichael P. Eastwood
- Journals
- Future Generation Computer Systems (1 paper)File and Storage Technologies (1 paper)
- Partner nations
- United StatesSwitzerland
In The Last Decade
Federico D. Sacerdoti
8 papers receiving 3.2k citations
Hit Papers
Peers
Comparison fields: 5 of 144
- Computational Theory and Mathematics 824
- Molecular Biology 1.8k
- Toxicology 72
- Organic Chemistry 572
- Pharmacology 163
Countries citing papers authored by Federico D. Sacerdoti
This map shows the geographic impact of Federico D. Sacerdoti'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 Federico D. Sacerdoti with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Federico D. Sacerdoti more than expected).
Fields of papers citing papers by Federico D. Sacerdoti
This network shows the impact of papers produced by Federico D. Sacerdoti. 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 Federico D. Sacerdoti. The network helps show where Federico D. Sacerdoti may publish in the future.
Co-authorship network
The 21 scholars most cited alongside Federico D. Sacerdoti, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 18 | |
| 2 | Desmond Performance on a Cluster of Multicore Processors | 2008 | 96 |
| 3 | Molecular dynamics---Scalable algorithms for molecular dynamics simulations on commodity clustersbreakdown → | 2006 | 1925 |
| 4 | Scalable Algorithms for Molecular Dynamics Simulations on Commodity Clustersbreakdown → | 2006 | 1182 |
| 5 | 2005 | 11 | |
| 6 | 2005 | 16 | |
| 7 | 2005 | 1 | |
| 8 | 2004 | 10 |
About Federico D. Sacerdoti
Federico D. Sacerdoti is a scholar working on Hardware and Architecture, Computer Networks and Communications and Information Systems and Management, having authored 8 papers that have together received 3.3k indexed citations. Recurring topics across this work include Advanced Data Storage Technologies (5 papers), Distributed and Parallel Computing Systems (4 papers), Parallel Computing and Optimization Techniques (4 papers), Distributed systems and fault tolerance (2 papers), Interconnection Networks and Systems (2 papers), Scientific Computing and Data Management (2 papers), Low-power high-performance VLSI design (1 paper) and Peer-to-Peer Network Technologies (1 paper). The work is most often cited by research in Computational Theory and Mathematics (824 citations), Molecular Biology (1.8k citations) and Toxicology (72 citations). Federico D. Sacerdoti has collaborated with scholars based in United States and Switzerland. Frequent co-authors include Ron O. Dror, David E. Shaw, K. J. Bowers, Yibing Shan, John L. Klepeis, Huafeng Xu, István Kolossváry, Michael P. Eastwood, John K. Salmon and Brent A. Gregersen. Their work appears in journals such as Future Generation Computer Systems and File and Storage Technologies.
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.