Francisco D. Igual

1.8k total citations
83 papers, 860 citations indexed

About

Francisco D. Igual is a scholar working on Hardware and Architecture, Computer Networks and Communications and Computer Vision and Pattern Recognition. According to data from OpenAlex, Francisco D. Igual has authored 83 papers receiving a total of 860 indexed citations (citations by other indexed papers that have themselves been cited), including 52 papers in Hardware and Architecture, 37 papers in Computer Networks and Communications and 17 papers in Computer Vision and Pattern Recognition. Recurrent topics in Francisco D. Igual's work include Parallel Computing and Optimization Techniques (50 papers), Distributed and Parallel Computing Systems (16 papers) and Advanced Data Storage Technologies (15 papers). Francisco D. Igual is often cited by papers focused on Parallel Computing and Optimization Techniques (50 papers), Distributed and Parallel Computing Systems (16 papers) and Advanced Data Storage Technologies (15 papers). Francisco D. Igual collaborates with scholars based in Spain, United States and Germany. Francisco D. Igual's co-authors include Enrique S. Quintana–Ort́ı, Robert A. Geijn, Rafael Mayo, Gregorio Quintana‐Ortí, Tyler Smith, Tze Meng Low, Maribel Castillo, Sergio Barrachina, Manuel Prieto and Manuel Ujaldón and has published in prestigious journals such as IEEE Transactions on Geoscience and Remote Sensing, IEEE Internet of Things Journal and Future Generation Computer Systems.

In The Last Decade

Francisco D. Igual

75 papers receiving 812 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Francisco D. Igual Spain 15 518 416 159 125 123 83 860
Sam S. Stone United States 9 673 1.3× 625 1.5× 195 1.2× 172 1.4× 116 0.9× 13 1.2k
Shane Ryoo United States 8 656 1.3× 608 1.5× 185 1.2× 156 1.2× 102 0.8× 12 1.1k
Akira Nukada Japan 16 584 1.1× 523 1.3× 99 0.6× 104 0.8× 155 1.3× 35 957
Erik Lindholm United States 6 814 1.6× 736 1.8× 295 1.9× 153 1.2× 218 1.8× 6 1.4k
Sara S. Baghsorkhi United States 13 955 1.8× 859 2.1× 223 1.4× 215 1.7× 159 1.3× 21 1.4k
Ronak Singhal United States 8 479 0.9× 440 1.1× 129 0.8× 134 1.1× 152 1.2× 11 858
Khaled Benkrid United Kingdom 17 410 0.8× 298 0.7× 192 1.2× 248 2.0× 233 1.9× 78 928
Ras Bodik United States 4 931 1.8× 875 2.1× 113 0.7× 154 1.2× 184 1.5× 6 1.3k
James Reinders United States 9 611 1.2× 582 1.4× 82 0.5× 121 1.0× 79 0.6× 15 917
Yuri Dotsenko United States 8 427 0.8× 367 0.9× 80 0.5× 65 0.5× 66 0.5× 14 621

Countries citing papers authored by Francisco D. Igual

Since Specialization
Citations

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

Fields of papers citing papers by Francisco D. Igual

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Francisco D. Igual. 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 Francisco D. Igual. The network helps show where Francisco D. Igual may publish in the future.

Co-authorship network of co-authors of Francisco D. Igual

This figure shows the co-authorship network connecting the top 25 collaborators of Francisco D. Igual. A scholar is included among the top collaborators of Francisco D. Igual 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 Francisco D. Igual. Francisco D. Igual 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.
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.
2.
Igual, Francisco D., et al.. (2025). Leveraging Multi-Instance GPUs through moldable task scheduling. Journal of Parallel and Distributed Computing. 204. 105128–105128. 1 indexed citations
3.
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
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.. (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
6.
7.
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
8.
Igual, Francisco D., et al.. (2023). Dynamic power budget redistribution under a power cap on multi-application environments. Sustainable Computing Informatics and Systems. 38. 100865–100865. 2 indexed citations
9.
Catalán, Sandra, et al.. (2022). Fine‐grain task‐parallel algorithms for matrix factorizations and inversion on many‐threaded CPUs. Concurrency and Computation Practice and Experience. 35(27). 1 indexed citations
10.
Catalán, Sandra, et al.. (2021). Scalable Hybrid Loop- and Task-Parallel Matrix Inversion for Multicore Processors. 679–687. 2 indexed citations
11.
Igual, Francisco D., et al.. (2021). Low precision matrix multiplication for efficient deep learning in NVIDIA Carmel processors. The Journal of Supercomputing. 77(10). 11257–11269. 2 indexed citations
12.
Zapater, Marina, et al.. (2020). Resource Management for Power-Constrained HEVC Transcoding Using Reinforcement Learning. IEEE Transactions on Parallel and Distributed Systems. 31(12). 2834–2850. 8 indexed citations
13.
Igual, Francisco D., et al.. (2019). Variable intra-task threading for power-constrained performance and energy optimization in DAG scheduling. The Journal of Supercomputing. 75(3). 1717–1731. 1 indexed citations
14.
Botella, Guillermo, et al.. (2018). Acceleration and energy consumption optimization in cascading classifiers for face detection on low‐cost ARM big. LITTLE asymmetric architectures. International Journal of Circuit Theory and Applications. 46(9). 1756–1776. 3 indexed citations
15.
Igual, Francisco D., et al.. (2017). Performance and Scalability Study of FMM Kernels on Novel Multi- and Many-core Architectures. Procedia Computer Science. 108. 2313–2317. 1 indexed citations
16.
Bernabé, Sergio, et al.. (2017). Performance-Power Evaluation of an OpenCL Implementation of the Simplex Growing Algorithm for Hyperspectral Unmixing. IEEE Geoscience and Remote Sensing Letters. 14(3). 304–308. 3 indexed citations
17.
Belloch, Jose A., Balázs Bank, Francisco D. Igual, Enrique S. Quintana–Ort́ı, & Antonio M. Vidal. (2016). Solving Weighted Least Squares (WLS) problems on ARM-based architectures. The Journal of Supercomputing. 73(1). 530–542. 4 indexed citations
18.
Alonso, Pedro, Manuel F. Dolz, Francisco D. Igual, Rafael Mayo, & Enrique S. Quintana–Ort́ı. (2012). Reducing Energy Consumption of Dense Linear Algebra Operations on Hybrid CPU-GPU Platforms. 56–62. 12 indexed citations
19.
Igual, Francisco D., et al.. (2012). Unleashing the high-performance and low-power of multi-core DSPs for general-purpose HPC. 1–11. 22 indexed citations
20.
Duato, J., Francisco D. Igual, Rafael Mayo, et al.. (2010). An efficient implementation of GPU virtualization in high performance clusters. Lecture notes in computer science. 385–394. 1 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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