Daniel Sánchez

5.3k total citations · 3 hit papers
96 papers, 3.7k citations indexed

About

Daniel Sánchez is a scholar working on Hardware and Architecture, Computer Networks and Communications and Information Systems. According to data from OpenAlex, Daniel Sánchez has authored 96 papers receiving a total of 3.7k indexed citations (citations by other indexed papers that have themselves been cited), including 79 papers in Hardware and Architecture, 75 papers in Computer Networks and Communications and 27 papers in Information Systems. Recurrent topics in Daniel Sánchez's work include Parallel Computing and Optimization Techniques (78 papers), Advanced Data Storage Technologies (45 papers) and Interconnection Networks and Systems (27 papers). Daniel Sánchez is often cited by papers focused on Parallel Computing and Optimization Techniques (78 papers), Advanced Data Storage Technologies (45 papers) and Interconnection Networks and Systems (27 papers). Daniel Sánchez collaborates with scholars based in United States, Spain and United Kingdom. Daniel Sánchez's co-authors include Christos Kozyrakis, Nathan Beckmann, Harshad Kasture, Joel Emer, Po-An Tsai, Srinivas Devadas, Anurag Mukkara, Richard M. Yoo, George Michelogiannakis and Axel Feldmann and has published in prestigious journals such as Science, Proceedings of the VLDB Endowment and ACM SIGPLAN Notices.

In The Last Decade

Daniel Sánchez

92 papers receiving 3.6k citations

Hit Papers

ZSim 2013 2026 2017 2021 2013 2020 2021 100 200 300
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.

  1. ZSim
    2013 325 citations Daniel Sánchez, Christos Kozyrakis profile →
  2. There’s plenty of room at the Top: What will drive computer performance after Moore’s law?
    2020 232 citations Charles E. Leiserson, Neil Thompson et al. Science profile →
  3. F1: A Fast and Programmable Accelerator for Fully Homomorphic Encryption
    2021 160 citations Nikola Samardzic, Axel Feldmann et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel Sánchez United States 33 2.7k 2.4k 1.2k 678 661 96 3.7k
Fabrizio Petrini United States 30 2.3k 0.8× 1.8k 0.8× 598 0.5× 432 0.6× 459 0.7× 109 2.9k
Henry Hoffmann United States 31 3.1k 1.2× 3.1k 1.3× 1.1k 0.9× 1.6k 2.3× 840 1.3× 145 4.8k
Karthikeyan Sankaralingam United States 35 3.4k 1.2× 3.8k 1.6× 585 0.5× 1.9k 2.8× 439 0.7× 117 5.0k
Bradley C. Kuszmaul United States 22 2.8k 1.0× 2.3k 1.0× 581 0.5× 412 0.6× 486 0.7× 56 3.5k
Michael Ferdman United States 23 2.3k 0.9× 2.1k 0.9× 1.1k 1.0× 893 1.3× 431 0.7× 60 3.4k
Tor M. Aamodt Canada 28 3.5k 1.3× 3.9k 1.6× 786 0.7× 1.5k 2.2× 690 1.0× 94 5.3k
Sudhakar Yalamanchili United States 29 1.9k 0.7× 1.8k 0.7× 441 0.4× 999 1.5× 258 0.4× 130 2.8k
Mattan Erez United States 34 2.4k 0.9× 2.6k 1.1× 563 0.5× 1.2k 1.8× 335 0.5× 109 3.4k
Hyesoon Kim United States 32 3.2k 1.2× 3.4k 1.4× 986 0.8× 977 1.4× 736 1.1× 152 4.5k
Alvin R. Lebeck United States 35 3.2k 1.2× 3.2k 1.3× 867 0.7× 1.2k 1.8× 297 0.4× 124 4.5k

Countries citing papers authored by Daniel Sánchez

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Sánchez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Sánchez

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

All Works

20 of 20 papers shown
1.
2.
Emer, Joel, et al.. (2024). Trapezoid: A Versatile Accelerator for Dense and Sparse Matrix Multiplications. 931–945. 10 indexed citations
3.
Feldmann, Axel, et al.. (2024). Azul: An Accelerator for Sparse Iterative Solvers Leveraging Distributed On-Chip Memory. 643–656. 1 indexed citations
4.
5.
Samardzic, Nikola, et al.. (2024). Accelerating Zero-Knowledge Proofs Through Hardware-Algorithm Co-Design. 366–379. 3 indexed citations
6.
Feldmann, Axel & Daniel Sánchez. (2023). Spatula: A Hardware Accelerator for Sparse Matrix Factorization. 91–104. 6 indexed citations
7.
Emer, Joel, et al.. (2021). Gamma: leveraging Gustavson’s algorithm to accelerate sparse matrix multiplication. 687–701. 94 indexed citations
8.
Ying, Victor A., et al.. (2020). T4: Compiling Sequential Code for Effective Speculative Parallelization in Hardware. 159–172. 18 indexed citations
9.
Sánchez, Daniel, et al.. (2020). Pipette: Improving Core Utilization on Irregular Applications through Intra-Core Pipeline Parallelism. 596–608. 19 indexed citations
10.
Leiserson, Charles E., Neil Thompson, Joel Emer, et al.. (2020). There’s plenty of room at the Top: What will drive computer performance after Moore’s law?. Science. 368(6495). 232 indexed citations breakdown →
11.
Zhang, Guowei & Daniel Sánchez. (2019). Leveraging Caches to Accelerate Hash Tables and Memoization. 440–452. 20 indexed citations
12.
Subramanian, Suvinay, et al.. (2017). Fractal. 587–599. 15 indexed citations
13.
Tsai, Po-An, Nathan Beckmann, & Daniel Sánchez. (2017). Jenga. 652–665. 46 indexed citations
14.
Mukkara, Anurag, Nathan Beckmann, & Daniel Sánchez. (2016). Whirlpool. ACM SIGARCH Computer Architecture News. 44(2). 113–127. 7 indexed citations
15.
Zhang, Guowei, et al.. (2016). Exploiting semantic commutativity in hardware speculation. International Symposium on Microarchitecture. 1–12. 7 indexed citations
16.
Kasture, Harshad & Daniel Sánchez. (2016). Tailbench: a benchmark suite and evaluation methodology for latency-critical applications. 1–10. 110 indexed citations
17.
Beckmann, Nathan & Daniel Sánchez. (2013). Jigsaw: scalable software-defined caches. International Conference on Parallel Architectures and Compilation Techniques. 213–224. 50 indexed citations
18.
Herrero, Enric, et al.. (2012). Mitigating lower layer failures with adaptive system reconfiguration. International Conference Mixed Design of Integrated Circuits and Systems. 109–114. 3 indexed citations
19.
Sánchez, Daniel & Christos Kozyrakis. (2011). Vantage. ACM SIGARCH Computer Architecture News. 39(3). 57–68. 37 indexed citations
20.
Sánchez, Daniel, Luke Yen, Mark D. Hill, & Karthikeyan Sankaralingam. (2007). Implementing Signatures for Transactional Memory. International Symposium on Microarchitecture. 123–133. 85 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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