Adrián Castelló

527 total citations
45 papers, 224 citations indexed

About

Adrián Castelló is a scholar working on Hardware and Architecture, Computer Networks and Communications and Computer Vision and Pattern Recognition. According to data from OpenAlex, Adrián Castelló has authored 45 papers receiving a total of 224 indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Hardware and Architecture, 20 papers in Computer Networks and Communications and 16 papers in Computer Vision and Pattern Recognition. Recurrent topics in Adrián Castelló's work include Parallel Computing and Optimization Techniques (31 papers), Advanced Neural Network Applications (16 papers) and Advanced Data Storage Technologies (10 papers). Adrián Castelló is often cited by papers focused on Parallel Computing and Optimization Techniques (31 papers), Advanced Neural Network Applications (16 papers) and Advanced Data Storage Technologies (10 papers). Adrián Castelló collaborates with scholars based in Spain, United States and Switzerland. Adrián Castelló's co-authors include Enrique S. Quintana–Ort́ı, Manuel F. Dolz, J. Duato, Rafael Mayo, Sergio Barrachina, Antonio J. Peña, Pedro Alonso, Federico Silla, Francisco D. Igual and Carlos Reaño and has published in prestigious journals such as IEEE Transactions on Computers, IEEE Internet of Things Journal and Future Generation Computer Systems.

In The Last Decade

Adrián Castelló

42 papers receiving 217 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Adrián Castelló Spain 9 123 113 75 61 54 45 224
Yongkee Kwon South Korea 8 117 1.0× 109 1.0× 54 0.7× 44 0.7× 77 1.4× 14 188
Christina Giannoula Greece 6 130 1.1× 109 1.0× 31 0.4× 47 0.8× 99 1.8× 21 235
Benoit Steiner United States 4 121 1.0× 61 0.5× 105 1.4× 83 1.4× 37 0.7× 5 213
Ehsan Totoni United States 10 220 1.8× 207 1.8× 31 0.4× 36 0.6× 52 1.0× 21 295
Akshay Venkatesh United States 12 234 1.9× 267 2.4× 42 0.6× 42 0.7× 51 0.9× 25 344
Viktor Prasanna United States 5 64 0.5× 71 0.6× 30 0.4× 89 1.5× 32 0.6× 29 172
Danyang Zhuo United States 9 52 0.4× 195 1.7× 31 0.4× 53 0.9× 47 0.9× 29 251
Naif Tarafdar Canada 8 168 1.4× 165 1.5× 29 0.4× 62 1.0× 78 1.4× 12 258
Amedeo Sapio Italy 6 32 0.3× 250 2.2× 39 0.5× 63 1.0× 71 1.3× 12 304
Huynh Phung Huynh Singapore 11 259 2.1× 260 2.3× 58 0.8× 30 0.5× 36 0.7× 22 353

Countries citing papers authored by Adrián Castelló

Since Specialization
Citations

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

Fields of papers citing papers by Adrián Castelló

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Adrián Castelló

This figure shows the co-authorship network connecting the top 25 collaborators of Adrián Castelló. A scholar is included among the top collaborators of Adrián Castelló 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 Adrián Castelló. Adrián Castelló 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.
Catalán, Sandra, et al.. (2025). Latency-Critical Quantized Inference With Transformer Decoders on ARM and RISC-V CPUs. IEEE Internet of Things Journal. 12(13). 25676–25690. 2 indexed citations
2.
Catalán, Sandra, et al.. (2025). Characterization of quantized inference with transformer encoders on low power CPUs. The International Journal of High Performance Computing Applications. 39(6). 803–821.
3.
Castelló, Adrián, et al.. (2025). The cambrian explosion of mixed-precision matrix multiplication for quantized deep learning inference. Future Generation Computer Systems. 177. 108231–108231.
4.
Castelló, Adrián, et al.. (2024). Experience-guided, mixed-precision matrix multiplication with apache TVM for ARM processors. The Journal of Supercomputing. 81(1). 1 indexed citations
5.
Castelló, Adrián, et al.. (2024). Automatic generation of ARM NEON micro-kernels for matrix multiplication. The Journal of Supercomputing. 80(10). 13873–13899. 2 indexed citations
6.
Castelló, Adrián, et al.. (2024). Communication-Avoiding Fusion of GEMM-Based Convolutions for Deep Learning in the RISC-V GAP8 MCU. IEEE Internet of Things Journal. 11(21). 35640–35653. 1 indexed citations
7.
Castelló, Adrián, et al.. (2024). QAttn: Efficient GPU Kernels for mixed-precision Vision Transformers. Zenodo (CERN European Organization for Nuclear Research). 3648–3657. 4 indexed citations
8.
Castelló, Adrián, et al.. (2024). Parallel GEMM-based convolution for deep learning on multicore RISC-V processors. The Journal of Supercomputing. 80(9). 12623–12643. 1 indexed citations
9.
10.
Castelló, Adrián, et al.. (2023). Algorithm 1039: Automatic Generators for a Family of Matrix Multiplication Routines with Apache TVM. ACM Transactions on Mathematical Software. 50(1). 1–34. 2 indexed citations
11.
Castelló, Adrián, et al.. (2023). Experiences with nested parallelism in task-parallel applications using malleable BLAS on multicore processors. The International Journal of High Performance Computing Applications. 38(2). 55–68. 1 indexed citations
12.
Dolz, Manuel F., et al.. (2023). Efficient and portable Winograd convolutions for multi-core processors. The Journal of Supercomputing. 79(10). 10589–10610. 2 indexed citations
13.
Dolz, Manuel F., et al.. (2023). Performance–energy trade-offs of deep learning convolution algorithms on ARM processors. The Journal of Supercomputing. 79(9). 9819–9836. 3 indexed citations
14.
Castelló, Adrián, et al.. (2022). High performance and energy efficient inference for deep learning on multicore ARM processors using general optimization techniques and BLIS. Journal of Systems Architecture. 125. 102459–102459. 6 indexed citations
15.
Castelló, Adrián, et al.. (2021). Performance Modeling for Distributed Training of Convolutional Neural Networks. abs 1709 3395. 99–108. 2 indexed citations
16.
Belloch, Jose A., Adrián Castelló, & Sergio Iserte. (2018). Accessible C-programming course from scratch using a MOOC platform without limitations. RiuNet (Politechnical University of Valencia). 1 indexed citations
17.
Castelló, Adrián, et al.. (2018). On the adequacy of lightweight thread approaches for high-level parallel programming models. Future Generation Computer Systems. 84. 22–31. 3 indexed citations
18.
Iserte, Sergio, Adrián Castelló, Rafael Mayo, et al.. (2014). SLURM Support for Remote GPU Virtualization: Implementation and Performance Study. Research Portal (Queen's University Belfast). 318–325. 19 indexed citations
19.
Castelló, Adrián, J. Duato, Rafael Mayo, et al.. (2014). On the Use of Remote GPUs and Low-Power Processors for the Acceleration of Scientific Applications. 57–62. 8 indexed citations
20.
Reaño, Carlos, Federico Silla, Antonio J. Peña, et al.. (2014). POSTER: Boosting the performance of remote GPU virtualization using InfiniBand connect-IB and PCIe 3.0. RiuNet (Politechnical University of Valencia). 266–267. 2 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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2026