Manuel Prieto

2.7k total citations
145 papers, 1.6k citations indexed

About

Manuel Prieto is a scholar working on Hardware and Architecture, Computer Networks and Communications and Computer Vision and Pattern Recognition. According to data from OpenAlex, Manuel Prieto has authored 145 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 61 papers in Hardware and Architecture, 52 papers in Computer Networks and Communications and 32 papers in Computer Vision and Pattern Recognition. Recurrent topics in Manuel Prieto's work include Parallel Computing and Optimization Techniques (56 papers), Advanced Data Storage Technologies (25 papers) and Interconnection Networks and Systems (19 papers). Manuel Prieto is often cited by papers focused on Parallel Computing and Optimization Techniques (56 papers), Advanced Data Storage Technologies (25 papers) and Interconnection Networks and Systems (19 papers). Manuel Prieto collaborates with scholars based in Spain, United States and Argentina. Manuel Prieto's co-authors include Juan Carlos Sáez, Francisco Tirado, Alexandra Fedorova, Sergey Blagodurov, Carlos García, Guillermo Botella, Luís Piñuel, Christian Tenllado, Sergey Zhuravlev and Javier Setoaín and has published in prestigious journals such as SHILAP Revista de lepidopterología, Communications of the ACM and IEEE Transactions on Geoscience and Remote Sensing.

In The Last Decade

Manuel Prieto

131 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Manuel Prieto Spain 21 730 676 373 303 231 145 1.6k
Daniel Reiter Horn United States 9 1.1k 1.5× 949 1.4× 346 0.9× 220 0.7× 114 0.5× 11 1.7k
Erik Lindholm United States 6 814 1.1× 736 1.1× 295 0.8× 142 0.5× 218 0.9× 6 1.4k
Stuart F. Oberman United States 13 783 1.1× 532 0.8× 204 0.5× 147 0.5× 594 2.6× 23 1.6k
Narayanan Sundaram United States 20 690 0.9× 761 1.1× 951 2.5× 508 1.7× 165 0.7× 31 1.8k
Francisco D. Igual Spain 15 518 0.7× 416 0.6× 159 0.4× 112 0.4× 123 0.5× 83 860
Tarek El‐Ghazawi United States 21 696 1.0× 707 1.0× 180 0.5× 168 0.6× 430 1.9× 154 1.5k
Sara S. Baghsorkhi United States 13 955 1.3× 859 1.3× 223 0.6× 190 0.6× 159 0.7× 21 1.4k
Timothy G. Mattson United States 18 966 1.3× 1.1k 1.6× 179 0.5× 352 1.2× 138 0.6× 65 1.7k
D. Lee United States 11 390 0.5× 258 0.4× 166 0.4× 189 0.6× 97 0.4× 28 1.6k
Shane Ryoo United States 8 656 0.9× 608 0.9× 185 0.5× 136 0.4× 102 0.4× 12 1.1k

Countries citing papers authored by Manuel Prieto

Since Specialization
Citations

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

Fields of papers citing papers by Manuel Prieto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Manuel Prieto

This figure shows the co-authorship network connecting the top 25 collaborators of Manuel Prieto. A scholar is included among the top collaborators of Manuel Prieto 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 Manuel Prieto. Manuel Prieto 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.
Schiavone, Pasquale Davide, et al.. (2026). Increasing the Energy Efficiency of Wearables Using Low-Precision Posit Arithmetic with PHEE. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 1–11.
2.
Rucci, Enzo, et al.. (2025). Analyzing the performance portability of SYCL across CPUs, GPUs, and hybrid systems with SW sequence alignment. Future Generation Computer Systems. 170. 107838–107838.
3.
Rucci, Enzo, et al.. (2024). Assessing opportunities of SYCL for biological sequence alignment on GPU-based systems. The Journal of Supercomputing. 80(9). 12599–12622. 2 indexed citations
4.
Barrio, Alberto A. Del, et al.. (2024). Big-PERCIVAL: Exploring the Native Use of 64-Bit Posit Arithmetic in Scientific Computing. IEEE Transactions on Computers. 73(6). 1472–1485. 3 indexed citations
5.
Barrio, Alberto A. Del, et al.. (2023). PERCIVAL. 375–376. 1 indexed citations
6.
Sáez, Juan Carlos, et al.. (2023). Flexible system software scheduling for asymmetric multicore systems with PMCSched: A case for Intel Alder Lake. Concurrency and Computation Practice and Experience. 35(25). 6 indexed citations
7.
8.
Barrio, Alberto A. Del, et al.. (2022). PERCIVAL: Open-Source Posit RISC-V Core With Quire Capability. IEEE Transactions on Emerging Topics in Computing. 10(3). 1241–1252. 27 indexed citations
9.
Sáez, Juan Carlos & Manuel Prieto. (2022). Evaluation of the Intel thread director technology on an Alder Lake processor. 61–67. 8 indexed citations
10.
Botella, Guillermo, et al.. (2016). Portable real-time DCT-based steganography using OpenCL. Journal of Real-Time Image Processing. 14(1). 87–99. 14 indexed citations
11.
Rucci, Enzo, Carlos García, Guillermo Botella, et al.. (2015). Smith-Waterman Protein Search with OpenCL on an FPGA. 3. 208–213. 4 indexed citations
12.
Barrientos, Ricardo J., José Ignacio Gómez, Christian Tenllado, Manuel Prieto, & Mauricio Marı́n. (2013). Range query processing on single and multi GPU environments. Computers & Electrical Engineering. 39(8). 2656–2668. 4 indexed citations
13.
Prieto, Manuel, et al.. (2009). System-level process variability compensation on memory organizations: on the scalability of multi-mode memories. Asia and South Pacific Design Automation Conference. 254–259. 1 indexed citations
14.
Vázquez‐Medina, Rubén, et al.. (2009). Segmentación de defectos superficiales en alambrón de cobre. Computación y Sistemas. 3(2). 88–97.
15.
Castro, Fernando, Daniel Chaver, Luís Piñuel, Manuel Prieto, & Francisco Tirado. (2008). Using age registers for a simple load–store queue filtering. Journal of Systems Architecture. 55(2). 79–89. 1 indexed citations
16.
Prieto, Manuel, et al.. (2008). Combining system scenarios and configurable memories to tolerate unpredictability. ACM Transactions on Design Automation of Electronic Systems. 13(3). 1–7. 2 indexed citations
17.
Chaver, Daniel, Luís Piñuel, Manuel Prieto, Francisco Tirado, & Michael Huang. (2003). Branch prediction on demand: an energy-efficient solution [microprocessor architecture]. 390–395. 9 indexed citations
18.
Chaver, Daniel, Luís Piñuel, Manuel Prieto, Francisco Tirado, & Michael Huang. (2003). Branch prediction on demand. 390–390. 28 indexed citations
19.
Gómez, José Ignacio, D. Bruni, Luca Benini, et al.. (2002). Scenario-based SDRAM-Energy-Aware Scheduling for Dynamic Multi-Media Applications on Multi-Processor Platforms.. Data Archiving and Networked Services (DANS). 3 indexed citations
20.
Chaver, Daniel, Christian Tenllado, Luís Piñuel, Manuel Prieto, & Francisco Tirado. (2002). 2-D Wavelet Transform Enhancement on General-Purpose Microprocessors: Memory Hierarchy and SIMD Parallelism Exploitation. 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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