Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
A case for redundant arrays of inexpensive disks (RAID)
19881.6k citationsGarth A. Gibson, Randy H. Katz et al.profile →
A case for redundant arrays of inexpensive disks (RAID)
19881.1k citationsGarth A. Gibson, Randy H. Katz et al.profile →
Citations per year, relative to Garth A. Gibson Garth A. Gibson (= 1×)
peers
Gregory R. Ganger
Countries citing papers authored by Garth A. Gibson
Since
Specialization
Citations
This map shows the geographic impact of Garth A. Gibson'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 Garth A. Gibson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Garth A. Gibson more than expected).
This network shows the impact of papers produced by Garth A. Gibson. 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 Garth A. Gibson. The network helps show where Garth A. Gibson may publish in the future.
Co-authorship network of co-authors of Garth A. Gibson
This figure shows the co-authorship network connecting the top 25 collaborators of Garth A. Gibson.
A scholar is included among the top collaborators of Garth A. Gibson based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Garth A. Gibson. Garth A. Gibson is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Kim, Jin K., et al.. (2019). STRADS-AP: Simplifying Distributed Machine Learning Programming without Introducing a New Programming Model.. USENIX Annual Technical Conference. 207–222.2 indexed citations
3.
Nagarajan, Vaishnavh, et al.. (2018). Geriatrix: aging what you see and what you don't see a file system aging approach for modern storage systems. USENIX Annual Technical Conference. 691–703.4 indexed citations
4.
Fan, Bin, et al.. (2018). A Case for Packing and Indexing in Cloud File Systems..1 indexed citations
5.
Amvrosiadis, George, et al.. (2018). On the diversity of cluster workloads and its impact on research results. USENIX Annual Technical Conference. 533–546.51 indexed citations
6.
Ts'o, T., et al.. (2017). Evolving Ext4 for Shingled Disks.. File and Storage Technologies. 42. 105–119.13 indexed citations
Ren, Kai & Garth A. Gibson. (2013). TABLEFS: enhancing metadata efficiency in the local file system. USENIX Annual Technical Conference. 2013. 145–156.74 indexed citations
Vernon, Mary K., Garth A. Gibson, Guy Latouche, & Scott T. Leutenegger. (1998). Proceedings of the 1998 ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems.5 indexed citations
17.
Riedel, Erik, Garth A. Gibson, & Christos Faloutsos. (1998). Active Storage for Large-Scale Data Mining and Multimedia. Very Large Data Bases. 62–73.213 indexed citations
18.
Gibson, Garth A.. (1993). Tutorial: Performance and reliability in redundant disk arrays.1 indexed citations
19.
Eggers, Susan J., James R. Larus, George Taylor, et al.. (1990). Design decisions in spur. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 273–299.17 indexed citations
20.
Wood, David A., Garth A. Gibson, & Randy H. Katz. (1989). Verifying a multiprocessor cache controller using random case generation. IEEE Design & Test of Computers.16 indexed citations
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.