Michael Shebanow

1.0k total citations · 1 hit paper
20 papers, 779 citations indexed

About

Michael Shebanow is a scholar working on Computer Networks and Communications, Hardware and Architecture and Information Systems. According to data from OpenAlex, Michael Shebanow has authored 20 papers receiving a total of 779 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Computer Networks and Communications, 13 papers in Hardware and Architecture and 4 papers in Information Systems. Recurrent topics in Michael Shebanow's work include Parallel Computing and Optimization Techniques (13 papers), Distributed and Parallel Computing Systems (12 papers) and Advanced Data Storage Technologies (10 papers). Michael Shebanow is often cited by papers focused on Parallel Computing and Optimization Techniques (13 papers), Distributed and Parallel Computing Systems (12 papers) and Advanced Data Storage Technologies (10 papers). Michael Shebanow collaborates with scholars based in United States, United Kingdom and Japan. Michael Shebanow's co-authors include Yale N. Patt, Wen mei Hwu, Chang Joo Lee, Veynu Narasiman, Onur Mutlu, Michael Butler, Tse-Yu Yeh, Wen‐mei Hwu, Karthik Ramani and M. Ramaswami and has published in prestigious journals such as Computer Graphics Forum, IEEE Micro and International Symposium on Microarchitecture.

In The Last Decade

Michael Shebanow

20 papers receiving 719 citations

Hit Papers

align trajectories

What are hit papers?

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.

Improving GPU performance via large warps and two-level warp scheduling

2011 317 citations Veynu Narasiman, Michael Shebanow et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Michael Shebanow United States	10	729	645	145	114	57	20	779
Rebecca L. Stamm United States	5	958 1.3×	837 1.3×	192 1.3×	118 1.0×	45 0.8×	7	1.0k
Manoj Franklin United States	16	1.0k 1.4×	892 1.4×	239 1.6×	113 1.0×	82 1.4×	45	1.1k
Amir Hormati United States	11	613 0.8×	449 0.7×	211 1.5×	77 0.7×	62 1.1×	20	698
Jason Duell United States	7	520 0.7×	703 1.1×	71 0.5×	237 2.1×	47 0.8×	8	760
Kimming So United States	11	539 0.7×	518 0.8×	123 0.8×	66 0.6×	51 0.9×	19	679
Andrew R. Pleszkun United States	16	1.1k 1.5×	855 1.3×	352 2.4×	103 0.9×	85 1.5×	33	1.1k
Andrew Kerr United States	10	475 0.7×	438 0.7×	63 0.4×	104 0.9×	40 0.7×	11	537
I. Kadayif United States	16	697 1.0×	522 0.8×	287 2.0×	85 0.7×	30 0.5×	49	769
Santosh G. Abraham United States	16	812 1.1×	666 1.0×	148 1.0×	102 0.9×	70 1.2×	39	875
David R. Ditzel United States	13	531 0.7×	357 0.6×	173 1.2×	44 0.4×	115 2.0×	37	627

Countries citing papers authored by Michael Shebanow

Since Specialization

Citations

This map shows the geographic impact of Michael Shebanow'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 Michael Shebanow with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Shebanow more than expected).

Fields of papers citing papers by Michael Shebanow

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael Shebanow. 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 Michael Shebanow. The network helps show where Michael Shebanow may publish in the future.

Co-authorship network of co-authors of Michael Shebanow

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Shebanow. A scholar is included among the top collaborators of Michael Shebanow 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 Michael Shebanow. Michael Shebanow is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Golas, Abhinav, et al.. (2016). VBTC: GPU‐Friendly Variable Block Size Texture Encoding. Computer Graphics Forum. 35(2). 409–418. 4 indexed citations

2.

Mutlu, Onur, Thomas R. Gross, John L. Hennessy, et al.. (2016). Common Bonds: MIPS, HPS, Two-Level Branch Prediction, and Compressed Code RISC Processor. IEEE Micro. 36(4). 70–85. 4 indexed citations

3.

Narasiman, Veynu, et al.. (2011). Improving GPU performance via large warps and two-level warp scheduling. 308–317. 317 indexed citations breakdown →

4.

Shebanow, Michael. (2009). Pervasive massively multithreaded GPU processors. 227–227. 3 indexed citations

5.

Ramaswami, M., et al.. (1995). Implementation trade-offs in using a restricted data flow architecture in a high performance RISC microprocessor. 151–162. 9 indexed citations

6.

Krishnamoorthy, Ashok V., et al.. (1995). Implementation trade-offs in using a restricted data flow architecture in a high performance RISC microprocessor. ACM SIGARCH Computer Architecture News. 23(2). 151–162. 1 indexed citations

7.

Butler, Michael, et al.. (1991). Single instruction stream parallelism is greater than two. 276–286. 105 indexed citations

8.

Butler, Michael, et al.. (1991). Single instruction stream parallelism is greater than two. ACM SIGARCH Computer Architecture News. 19(3). 276–286. 13 indexed citations

9.

Shebanow, Michael, et al.. (1988). Hardware support for large atomic units in dynamically scheduled machines. International Symposium on Microarchitecture. 60–63. 53 indexed citations

10.

Shebanow, Michael, et al.. (1988). Hardware Support For Large Atomic Units in Dynamically Scheduled Machines. 60–63. 30 indexed citations

11.

Despain, Alvin M., Yale N. Patt, William R. Bush, et al.. (1987). Aquarius. ACM SIGARCH Computer Architecture News. 15(1). 22–34. 2 indexed citations

12.

Shebanow, Michael, et al.. (1987). On tuning the microarchitecture of an HPS implementation of the VAX. 162–167. 3 indexed citations

13.

Shebanow, Michael, et al.. (1986). C COMPILER FOR HPS I, A HIGHLY PARALLEL EXECUTION ENGINE.. 190. 520–528. 6 indexed citations

14.

Patt, Yale N., et al.. (1986). EXPERIMENTS WITH HPS, A RESTRICTED DATA FLOW MICROARCHITECTURE FOR HIGH PERFORMANCE COMPUTERS.. 37(4). 254–258. 3 indexed citations

15.

Patt, Yale N., et al.. (1986). Run-time generation of HPS microinstructions from a VAX instruction stream. 75–81. 7 indexed citations

16.

Patt, Yale N., et al.. (1986). Run-time generation of HPS microinstructions from a VAX instruction stream. ACM SIGMICRO newsletter/SIGMICRO newsletter/SIGMICRO, TCMICRO newsletter. 17(4). 75–81. 5 indexed citations

17.

Patt, Yale N., Wen mei Hwu, & Michael Shebanow. (1985). HPS, a new microarchitecture: rationale and introduction. ACM SIGMICRO newsletter/SIGMICRO newsletter/SIGMICRO, TCMICRO newsletter. 16(4). 103–108. 66 indexed citations

18.

Patt, Yale N., Wen mei Hwu, & Michael Shebanow. (1985). HPS, a new microarchitecture: rationale and introduction. 103–108. 81 indexed citations

19.

Patt, Yale N., et al.. (1985). Critical issues regarding HPS, a high performance microarchitecture. ACM SIGMICRO newsletter/SIGMICRO newsletter/SIGMICRO, TCMICRO newsletter. 16(4). 109–116. 31 indexed citations

20.

Patt, Yale N., et al.. (1985). Critical issues regarding HPS, a high performance microarchitecture. 109–116. 36 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.

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