Citas externas

Consideramos citas externas aquellos documentos científicos que citan algún trabajo propio, en los que ninguno de los autores del documento original coincide con ninguno de los autores o coautores del trabajo citado.

H-index: 7 (Medido a partir de la lista de citas externas contenida en este documento).

Número total de citas externas: 201

Este documento contiene una relación no exhaustiva de citas externas a las publicaciones, informes técnicos y trabajo de tesis de Arturo González Escribano.

• A.J. Dorta, A. González-Escribano, C. Rodríguez, F. de Sande
  "The OpenMP Source Code Repository",
  EuroMicro PDP'2005, 13th Euromicro Conference on Parallel, Distributed and Network-based Processing,
  Lugano - Switzerland, February 9-11, 2005
  IEEE Press, 2005
  ISSN: 1066-6192, ISBN: 0-7695-2280-7

  1. [ResearchGate] Simone Atzeni, Ganesh Gopalakrishnan, Zvonimir Rakamaric, Dong H. Ahn, Ignacio Laguna, Martin Schulz, Gregory L. Lee, Joachim Protze, Matthias S. Müller. ARCHER: Effectively Spotting Data Races in Large OpenMP Applications. IEEE International Parallel and Distributed Processing Symposium, July 2016. doi:10.1109/IPDPS.2016.68

  2. [ResearchGate] Yi Li, Aws Albarghouthi, Zachary Kincaid, Arie Gurfinkel, Marsha Chechik, Symbolic optimization with SMT solvers POPL'14 Proceedings of the 41st ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages, ACM SIGPLAN Notices - POPL'14, Volume 49 Issue 1, January 2014, Pages 607-618, doi:10.1145/2578855.2535857

  3. [ResearchGate] Prasanth Chatarasi, Jun Shirako, Martin Kong, and Vivek Sarkar, An Extended Polyhedral Model for SPMD Programs and its use in Static Data Race Detection, In Proc. LCPC 2016, Rochester, NY, September 2016.

  4. [ResearchGate] Shivani Raghav, Andrea Marongiu, Christian Pinto, Martino Ruggiero, David Atienza, Luca Benini, SIMinG-1k: A thousand-core simulator running on general-purpose graphical processing units Concurrency and Computation Practice and Experience 25(10):1443-1461, Wiley 2013, doi:10.1002/cpe.2940

  5. [ResearchGate] Shivani Raghav, Andrea Marongiu, Christian Pinto, David Atienza, Martino Ruggiero, Luca Benini, GPU Acceleration for Simulating Massively Parallel Many-Core Platforms, IEEE Transactions on Parallel and Distributed Systems 26(5):1336-1349, IEEE Press, 2014, doi:10.1109/TPDS.2014.2319092

  6. [ResearchGate] Ferruccio Bettarelli, Emanuele Ciavattini, Ariano Lattanzi, et.al., Extensions of the hArtes Tool Chain, Chapter in Hardware/Software Co-design for Heterogeneous Multi-core Platforms, pp 193-227, ISBN: 978-94-007-1405-2, Springer 2012, doi:10.1007/978-94-007-1406-9_6

  7. [ResearchGate] J. Protze, S. Atzeni, D.H. Ahn, M. Schulz, G. Gopalakrishnan, M.S. Müller, Ignacio Laguna, Zvonimir Rakamaric, and G.L. Lee, Towards providing low-overhead data race detection for large OpenMP applications, LLVM-HPC 2016, (Pendiente de publicación)

  8. [ResearchGate] L. Shen, F. Xu, Z-Y. Wang Optimization Strategies Oriented to Loop Characteristics in Software Thread Level Speculation Systems, Journal of Computer Science and Technology 31(1):60-76, Springer, 2016. doi:10.1007/s11390-016-1612-z

  9. [ResearchGate] Marco Lattuada , Christian Pilato, Fabrizio Ferrandi. Performance Estimation of Task Graphs Based on Path Profiling. International Journal of Parallel Programming, Springer, 2015. doi:10.1007/s10766-015-0372-7

  10. [ResearchGate] M. Popov, C. Akel, F. Conti, W. Jalby, P. De Oliveira Castro, PCERE: Fine-grained Parallel Benchmark Decomposition for Scalability Prediction. Proc. 29th IEEE International Parallel and Distributed Processing Symposium IPDPS 2015, (to appear).

  11. [ResearchGate] L.A.J. Marzulo, T.A.O. Alves, F.M.G. França, V.S. Costa, Couillard: Parallel programming via coarse-grained Data-flow Compilation, Parallel Computing 40(10), p. 661-680, 2014

  12. [ResearchGate] M. Kang, O. Ha, Y. Jun, Visualization Tool for Debugging Data Races in Structured Fork-join Parallel Programs, International Journal of Software Engineering and Its Applications 04/2014; 8(4):157-168. doi:10.14257/ijseia.2014.8.4.17

  13. [ResearchGate] O.-Ha, On-the-fly Race Detection for Structured Fork-join Parallel Programs, International Journal of Software Engineering and Its Applications 04/2014; 8(4):11-22. doi:10.14257/ijseia.2014.8.4.02

  14. [ResearchGate] O.-Ha, Y.-Jun, Efficient thread labeling for on-the-fly detection of races in OpenMP programs, INFORMATION, Japan 16(12):8541-8548, Dec 2013

  15. [ResearchGate, IEEEXplore] N. Chen, R.E. Johnson, JFlow: Practical refactorings for flow-based parallelism IEEE/ACM 28th International Conference on Automated Software Engineering (ASE), p. 202-212, IEEE Press 2013, doi:10.1109/ASE.2013.6693080

  16. [ResearchGate, IEEEXplore] B. Ramesh, C.J. Ribbens, S. Varadarajan, Towards Virtual Shared Memory for Non-cache-coherent Multicore Systems, IEEE 27th International Parallel and Distributed Processing Symposium Workshops & PhD Forum (IPDPSW), p. 1186-1193, IEEE Press 2013, doi:10.1109/IPDPSW.2013.73

  17. [ResearchGate, IEEEXplore] B. Ramesh, C.J. Ribbens, S. Varadarajan, Regional Consistency: Programmability and Performance for Non-Cache-Coherent Systems, IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), p. 941-948, IEEE Press 2013, doi:10.1109/TrustCom.2013.115

  18. [ResearchGate] Ryan W. Moore, Bruce R. Childers, Automatic generation of program affinity policies using machine learning, CC'13 Proceedings of the 22nd international conference on Compiler, Springer Verlag, 2013

  19. [ResearchGate,IEEEXplore] C-C. Wu, J-J. Huang, The Study of Android Parallel Programming Based on the Dual-Core Cortex-A9, Proc. 2013 Ninth International Conference on Intelligent Information Hiding and Multimedia Signal Processing, p. 477-480, IEEE 2013, doi:10.1109/IIH-MSP.2013.124

  20. [ResearchGate] P.R. Chakraborty, S. Chowdhury, A.K. Chowdhury, S. Al Hasan, A new source code repository for dynamic storing, browsing, and retrieval of source codes Proc. 2013 International Conference on Informatics, Electronics & Vision (ICIEV), p. 1-6. IEEE Press, 2013. doi:10.1109/ICIEV.2013.6572624

  21. [ResearchGate] Ok-Kyoon Ha, In-Bon Kuh, Guy Martin Tchamgoue, Yong-Kee Jun, On-the-fly detection of data races in OpenMP programs, PADTAD 2012 Proceedings of the 2012 Workshop on Parallel and Distributed Systems: Testing, Analysis, and Debugging, ACM New York 2012, p. 1-10, doi:10.1145/2338967.2336808

  22. [ResearchGate] Fang Yu, Shun-Ching Yang, Farn Wang, Guan-Cheng Chen, Che-Chang Chan, Symbolic consistency checking of OpenMp parallel programs, LCTES'12, Proceedings of the 13th ACM SIGPLAN/SIGBED International Conference on Languages, Compilers, Tools and Theory for Embedded Systems, ACM SIGPLAN Notices 47(5), p. 139-148, ACM New York 2012, doi:10.1145/2248418.2248438

  23. [ResearchGate] Shivani Raghav, Andrea Marongiu, Christian Pinto, David Atienza, Martino Ruggiero, Luca Benini, Full system simulation of many-core heterogeneous SoCs using GPU and QEMU semihosting, GPGPU-5, Proceedings of the 5th Annual Workshop on General Purpose Processing with Graphics Processing Units, ACM SIGPLAN Notices 47(5), p. 101-109, ACM New York 2012, doi:10.1145/2159430.2159442

  24. [ResearchGate] M. Lattuada, F. Ferrandi, Performance estimation of embedded software with confidence levels, Proc. 17th Asia and South Pacific Design Automation Conference (ASP-DAC), p. 573-578, IEEE Press, 2012, doi:10.1109/ASPDAC.2012.6165022

  25. [ResearchGate] H. Uchiyama, T. Tsumura, T.H. Matsuo, An Automatic Host and Device Memory Allocation Method for OpenMPC, Proc. Third International Conference on Networking and Computing (ICNC), p. 208-214, IEEE Press, 2012, doi:10.1109/ICNC.2012.39

  26. [ResearchGate] K. Khubaib, M.A. Suleman, M. Hashemi, C. Wilkerson, Y.N. Patt, MorphCore: An Energy-Efficient Microarchitecture for High Performance ILP and High Throughput TLP, Proc. 45th Annual IEEE/ACM International Symposium on Microarchitecture (MICRO), p. 305-316, IEEE Press, 2012, doi:10.1109/MICRO.2012.36

  27. [ResearchGate] Andrea Marongiu, Luca Benini, An OpenMP Compiler for Efficient Use of Distributed Scratchpad Memory in MPSoCs, IEEE Transactions on Computers 61(2), p. 222-236, IEEE press, 2012, doi:10.1109/TC.2010.199

  28. [ResearchGate] Mateus B. Rutzig, Antonio C.S. Beck, Felipe Madruga, Marco A. Alves, Henrique C. Freitas, Nicolas Maillard, Philippe O.A. Navaux, Luigi Carrol, Boosting Parallel Applications Performance on Applying DIM Technique in a Multiprocessing Environment, International Journal of Reconfigurable Computing, Volume 2011, Article ID 546962, 13 pages, Hindawi Publishing Corporation, 2011, doi:10.1155/2011/546962

  29. [Scopus] O.-Ha, Y.-Jun, Efficient thread labeling for on-the-fly race detection of programs with nested parallelism, Communications in Computer and Information Science (CCIS) v.257, p.424-436, 2011

  30. [Scopus] A. Marongiu, P. Burgio, L. Benini, Supporting OpenMP on a multi-cluster embedded MPSoC, Microprocessors and Microsystems, v.35 n.8, p.668-682, 2011

  31. [Scopus] T.A.O. Alves, L.A.J. Marzulo, F.M.G. França, V.S. Costa, Trebuchet: Exploring TLP with dataflow virtualisation, International Journal of High Performance Systems Architecture, v.3 n.2-3, p.137-148, 2011

  32. [Scopus] S.-Kim, O.-Ha, Y.-Jun, Efficiency of e-NR labeling for on-the-fly race detection of programs with nested parallelism, Communications in Computer and Information Science (CCIS) v.151 n.2, p.191-200, 2011

  33. [Scopus] M.B. Rutzig, A.C.S. Beck, L. Carro, CReAMS: An embedded multiprocessor platform, LNCS 6578, p.118-124, Springer 2011

  34. [ResearchGate] M. Aater Suleman, Onur Mutlu, José A. Joao, Khubaib, Yale N. Patt, Data marshaling for multi-core architectures, ISCA'10 Proceedings of the 37th annual international symposium on Computer architecture, ACM SIGARCH Computer Architecture News 38(3), p. 441-450, ACM New York, 2010, doi:10.1145/1816038.1816020

  35. [Scopus] A. Marongiu, P. Burgio, L. Benini, Evaluating OpenMP support costs on MPSoCs, Proceedings - 13th Euromicro Conference on Digital System Design: Architectures, Methods and Tools, DSD 2010, p.191-198

  36. [Scopus] D. Becker, M. Geimer, R. Rabenseifner, F. Wolf, Synchronizing the timestamps of concurrent events in traces of hybrid MPI/OpenMP applications, Proceedings - IEEE International Conference on Cluster Computing, ICCC 2010, p.38-47

  37. [Scopus] M. Lattuada, F. Ferrandi, Performance modeling of embedded applications with zero architectural knowledge, 2010 IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis, CODES+ISSS 2010, p.277-286

  38. [Scopus] J. Joven, A. Marongiu, F. Angiolini, L. Benini, G. De Micheli, Exploring programming model-driven QoS support for NoC-based platforms, Embedded Systems Week 2010 - Proceedings of the 8th IEEE/ACM/IFIP International Conference on Compilers, Architecture and Synthesis for Embedded Systems, CODES+ISSS'2010, p.65-74

  39. [Scopus] X.-Wu, N. Obeid, W.-Hwu, Exploiting more parallelism from applications having generalized reductions on GPU architectures, Proceedings - 10th IEEE International Conference on Computer and Information Technology, CIT-2010, ICESS-2010, ScalCom-2010, p.1175-1180

  40. [Scopus] M.B. Rutzig, F. Madruga, M.A. Alves, H. Cota, A.C.S. Beck, N. Maillard, P.O.A. Navaux, L. Carro, TLP and ILP exploitation through a reconfigurable multiprocessor system, Proceedings of the 2010 IEEE International Symposium on Parallel and Distributed Processing, Workshops and Phd Forum, IPDPSW 2010

  41. [ACM/dl][Scopus] M. Aater Suleman , Onur Mutlu , Moinuddin K. Qureshi , Yale N. Patt, Accelerating critical section execution with asymmetric multi-core architectures, ACM SIGPLAN Notices, v.44 n.3, March 2009

  42. [ACM/dl] M. Aater Suleman , Moinuddin K. Qureshi , Yale N. Patt, Feedback-driven threading: power-efficient and high-performance execution of multi-threaded workloads on CMPs, ACM SIGOPS Operating Systems Review, v.42 n.2, March 2008

  43. [ACM/dl][Scopus] Giovanni Beltrame , Luca Fossati , Donatella Sciuto, Concurrency emulation and analysis of parallel applications for multi-processor system-on-chip co-design, Proceedings of the 6th IEEE/ACM/IFIP international conference on Hardware/Software codesign and system synthesis, October 19-24, 2008, Atlanta, GA, USA

  44. [ACM/dl][Scopus] Ami Marowka, Bsp2omp: A Compiler For Translating Bsp Programs To Openmp, International Journal of Parallel, Emergent and Distributed Systems, v.24 n.4, p.293-310, August 2009

  45. [ACM/dl][Scopus] Fabrizio Ferrandi , Marco Lattuada , Christian Pilato , Antonino Tumeo, Performance estimation for task graphs combining sequential path profiling and control dependence regions, Proceedings of the 7th IEEE/ACM international conference on Formal Methods and Models for Codesign, p.131-140, July 13-15, 2009, Cambridge, Massachusetts

  46. [ACM/dl][Scopus] Giovanni Beltrame , Luca Fossati , Donatella Sciuto, ReSP: a nonintrusive transaction-level reflective MPSoC simulation platform for design space exploration, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, v.28 n.12, p.1857-1869, December 2009

  47. [ACM/dl][Scopus] Marco Lattuada , Christian Pilato , Antonino Tumeo , Fabrizio Ferrandi, Performance modeling of parallel applications on MPSoCs, Proceedings of the 11th international conference on System-on-chip, p.64-67, October 05-07, 2009, Tampere, Finland

  48. [Google Scholar] M. Aater Suleman , Moinuddin K. Qureshi , Yale N. Patt, Feedback-driven threading: power-efficient and high-performance execution of multi-threaded workloads on CMPs ACM SIGPLAN Notices, ASPLOS'08 Pages: 277--286

  49. [Google Scholar] M. Aater Suleman , Moinuddin K. Qureshi , Yale N. Patt, An Asymmetric Multi-core Architecture for Accelerating Critical Sections Tech.Rep. TR-HPS-2008-003 High Performance Systems Group, Department of Electrical and Computer Engineering, The University of Texas at Austin, September 2008

  50. [Google Scholar] K. Furlinger, M. Gerndt, ompP: A profiling tool for OpenMP IWOMP, LNCS 4315, Pages: 15--23 Springer, 2008

  51. [Google Scholar][Scopus] K. Furlinger, M. Gerndt, Performance Analysis of Shared-Memory Parallel Applications Using Performance Properties High Performance Computing and Communications, LNCS 3726 Springer, 2005

  52. [Google Scholar] Alejandro Duran, Xavier Teruel, Roger Ferrer, Xavier Martorell, Eduard Ayguadé, Barcelona OpenMP Tasks Suite: A Set of Benchmarks Targeting the Exploitation of Task Parallelism in OpenMP 2009 International Conference on Parallel Processing, ICPP'09 Pages: 124--131 IEEE, 2009

  53. [Google Scholar] A. Marongiu, A. Acquaviva and L. Benini, OpenMP Support for NBTI-Induced Aging Tolerance in MPSoCs Stabilization, Safety, and Security of Distributed Systems, LNCS 5873 Pages: 547--562 Springer 2009

• Y. Torres, A. Gonzalez-Escribano, D.R. Llanos.
  Understanding the Impact of CUDA Tuning Techniques for Fermi.
  Workshop on Exploitation of Hardware Accelerators (WEHA 2011). Istanbul (Turkey), 2011.
  Proceedings IEEE Intl. Conf. on High Performance Computing and Simulation (HPCS), pag. 631-639, ISBN 978-1-61284-381-0.

  1. [ResearchGate] Lídia Kuan, Frederico Pratas, Leonel Sousa, Pedro Tomás, MrBayes sMC3: Accelerating Bayesian inference of phylogenetic trees, The International Journal of High Performance Computing Applications, SAGE Journals, First Published June 30, 2016, doi:10.1177/1094342016652461

  2. [Research Gate] Christian Obrechta, Frédéric Kuznikb, Bernard Tourancheaud, Jean-Jacques Rouxb, Efficient GPU implementation of the linearly interpolated bounce-back boundary condition, Computers & Mathematics with Applications, Volume 65, Issue 6, March 2013, Pages 936-944, Elsevier, 2013 doi:10.1016/j.camwa.2012.05.014

  3. [Research Gate] Tyler Sorensen, Alastair F. Donaldson, Mark Batty, Ganesh Gopalakrishnan, Zvonimir Rakamaric, Portable inter-workgroup barrier synchronisation for GPUs, OOPSLA 2016, Proceedings of the 2016 ACM SIGPLAN International Conference on Object-Oriented Programming, Systems, Languages, and Applications, ACM SIGPLAN Notices - OOPSLA '16, Volume 51 Issue 10, October 2016, Pages 39-58 doi:10.1145/3022671.2984032

  4. [Research Gate] Jyotsna Sharma, Maninder Singh, CUDA based Rabin-Karp Pattern Matching for Deep Packet Inspection on a Multicore GPU, International Journal of Computer Network and Information Security(IJCNIS), 7(10), MECS Publisher, Sep. 2015, doi:10.5815/ijcnis

  5. [Research Gate] Miguel Cárdenas-Montes, Miguel A. Vega-Rodríguez, Juan José Rodríguez-Vázquez, Antonio Gómez-Iglesias, Parallel evaluation of nonseparable functions by evolutionary algorithms on GPU, Concurrency and Computation, Practice and Experience, Sept 2016, Wiley, 2016 doi:10.1002/cpe.3949

  6. [Research Gate] S. Tabik, M. Peemen, N. Guil and H. Corporaal. Demystifying the 16 × 16 thread-block for stencils on the GPU. Concurrency and Computation, Practice and Experience, (Accepted for publication, already online) Wiley, 2015 doi:10.1002/cpe.3591

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  8. [Google Scholar] Understanding Outstanding Memory Request Handling Resources in GPGPUs, by Ahmad Lashgar, Ebad Salehi, Amirali Baniasadi, International symposium on Highly-Efficient Accelerators and Reconfigurable Technologies (HEART2015), Boston, June 2015

  9. [Google Scholar] Automated GPU Kernel Transformations in Large-Scale Production Stencil Applications, by Mohamed Wahib, Naoya Maruyama, HPDC'15 Proceedings of the 24th International Symposium on High-Performance Parallel and Distributed Computing, Pages 259-270, ACM Press, 2015, doi:10.1145/2749246.2749255

  10. [Google Scholar] Analysis and Optimization Techniques for Massively Parallel Processors, Wenhao Jia, PhD Thesis, Publication Number: 3665320, Princeton University, 2014

  11. [Google Scholar] Performance Optimization of GPU ELF-Codes, Fausto Artico, PhD Thesis, University of Padova, 2014

  12. [Google Scholar] High performance computing for solving large sparse systems. Optical diffraction tomography as a case of study, Gloria Ortega López, PhD Thesis, University of Almería, 2014

  13. [Google Scholar] Characterizing and improving the use of demand-fetched caches in GPUs, by Wenhao Jia, Kelly A. Shaw, Margaret Martonosi, ICS '12 Proceedings of the 26th ACM international conference on Supercomputing, Pages 15-24, ACM Press, 2012

  14. [Google Scholar] Application-independent Autotuning for GPUs, by Martin Tillmann, Thomas Karcher, Carsten Dachsbacher, Walter F. Tichy, Parallel Computing: Accelerating Computational Science and Engineering (CSE), pages 626-635, ISBN: 978-1-61499-380-3, IOS Press, 2014

  15. [Google Scholar] Efficient GPU implementation of the linearly interpolated bounce-back boundary condition, by Christian Obrechta, Frédéric Kuznikb, Bernard Tourancheaud, Jean-Jacques Roux, Computers & Mathematics with Applications 65(6), March 2013, Pages 936-944, Elsevier, 2013

  16. [Google Scholar] Orchestrating Cache Management and Memory Scheduling for GPGPU Applications, by Shuai Mu, Yandong Deng, Yubei Chen, Huaiming Li, Jianming Pan, Wenjun Zhang, Zhihua Wang, IEEE Transactions on Very Large Scale Integration (VLSI) Systems 22(8), Aug, IEEE Press, 2014

  17. [Google Scholar] MRPB: Memory request prioritization for massively parallel processors, by Wenhao Jia, Kelly A. Shaw, Margaret Martonosi, 20th IEEE International Symposium on High Performance Computer Architecture, HPCA 2014, pages 272-283, IEEE Press, 2014

  18. [Google Scholar] Architectural Analysis and Performance Characterization of NVIDIA GPUs using Microbenchmarking, by Saktheesh Subramoniapillai Ajeetha, M.Sc thesis, Graduate Program in Computer Science and Engineering, The Ohio State University, 2012

  19. [Google Scholar] GPU-Based simulation of brain neuron models, by H Du Nguyen, M.Sc thesis, Computer Engineering, Delft University of Technology, 2013

  20. [Google Scholar] Realtime Deformation of Constrained Meshes Using GPU, by Alexandre Kaspar, Bailin Deng, 2013 Symposium on GPU Computing and Applications, Singapore, 2013

  21. [Google Scholar] An OpenCL Micro-Benchmark Suite for GPUs and CPUs, by Xin Yan, Xiaohua Shi, Qingyue Sun, 13th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT), 2012, pages 53-58, IEEE press, 2012

  22. [Google Scholar] Solving the Examination Timetabling Problem in GPUs, by Vasileios Kolonias, George Goulas, Christos Gogos, Panayiotis Alefragis, Efthymios Housos, Algorithms 7(3), pages 295-327, MDPI 2014

  23. [Google Scholar] Optimizations with CUDA: A Case Study on 3D Curve-Skeleton Extraction from Voxelized Models, by Jesús Jiménez, Juan Ruiz de Miras, 7th International Joint Conference, VISIGRAPP 2012, Rome, Italy, February 24-26, 2012, Revised Selected Papers, Computer Vision, Imaging and Computer Graphics. Theory and Application. Communications in Computer and Information Science Volume 359, 2013, pp 82-96, Springer 2013

  24. [Google Scholar] Video coding on multicore graphics processors (GPUs), by Bruno Alexandre de Medeiros, M.Sc thesis, Information Systems and Computer Engineering, Instituto Superior Tecnico, Universidade Tecnica de Lisboa, 2012

  25. [Google Scholar] FastSpMM: An Efficient Library for Sparse Matrix Matrix Product on GPUs, by Gloria Ortega, Francisco Vázquez, Inmaculada García, Ester M. Garzón, The Computer Journal 57(7), pages 968-979, Oxford Journals, 2013

  26. [Google Scholar] Orchestrating Thread Scheduling and Cache Management to Improve Memory System Throughput in Throughput Processors, by Dong Li, PhD Thesis, Faculty of the Graduate School, The University of Texas at Austin, 2014

  27. [Google Scholar] A Survey of techniques for managing and leveraging caches in GPUs, by Sparsh Mittal, Journal of Circuits, Systems and Computers 23(8), World Scientific, 2014

  28. [Google Scholar] Performance Optimization of GPU ELF-Codes, by Fausto Artico, Algorithms, hgpu.org, 2014

  29. [Google Scholar] M&C: A Software Solution to Reduce Errors Caused by Incoherent Caches on GPUs in Unstructured Graphic Algorithm, by Kun Wang, Rui Wang, Zhongzhi Luan, Depei Qian, 13th International Conference, ICA3PP 2013, in Algorithms and Architectures for Parallel Processing, pages 426-435, ISBN: 978-3-319-03858-2, Springer, 2013

  30. [arxiv.org] Scalability and Optimization Strategies for GPU Enhanced Neural Networks (GeNN) by Naresh Balaji, Esin Yavuz, Thomas Nowotny, arXiv:1412.0595 [cs.DC], Dec 2014

• H. Ortega-Arranz, Y. Torres, D.R. Llanos, A. Gonzalez-Escribano.
  A New GPU-based Approach to the Shortest Path Problem.
  Proceedings HPCS 2013, International Conference on High Performance Computing and Simulation, Helsinki (Finland), 2013.
  IEEE Press, ISBN 978-1-4799-0838-7, pag. 505-511.

  1. [ResearchGate] Julio Toss, João Comba, Bruno Raffin, Parallel Voronoi Computation for Physics-Based Simulations, Computing in Science & Engineering ( Volume: 18, Issue: 3, May-June 2016 ), IEEE Press, doi:10.1109/MCSE.2016.52

  2. [ResearchGate] Marco Antonio Boschetti, Vittorio Maniezzo, Francesco Strappaveccia, Route Relaxations on GPU for Vehicle Routing Problems European Journal of Operational Research, Elsevier, Oct 2016, doi:10.1016/j.ejor.2016.09.050

  3. [ResearchGate] Jie Wang, Weihao Chen, MRI Image Segmentation Based on a GPU Shortest Path Algorithm, 2nd International Conference on Intelligent Computing and Cognitive Informatics, Atlantis Press, Oct 2015, doi:10.2991/icicci-15.2015.1

  4. [ResearchGate] SSSP on GPU Without Atomic Operation, by Feng Wang, Liehuang Zhu, and Changyou Zhang, Chapter in Human Centered Computing, LNCS 9567, pp.409-419. ISBN: 978-3-319-31853-0, Springer, 2016 doi:10.1007/978-3-319-31854-7_37

  5. [ResearchGate] Toward GPU-accelerated Database Optimization by Andreas Meister , Sebastian Breß, Gunter Saake. Datenbank-Spektrum 15(2), pp 131-140, Springer, 2015 doi:10.1007/s13222-015-0184-3

  6. [ResearchGate] Accelerated Steiner Tree Problem Solving on GPU with CUDA, by C. Mathieu and M. Klusch, Proc. of the 15th International Conference on Algorithms and Architectures for Parallel Processing, ACM, 2015, Link: http://www.dfki.de/lt/publication_show.php?id=7973

  7. [ResearchGate] Improving Global Performance on GPU for Algorithms with Main Loop Containing a Reduction Operation: Case of Dijkstra's Algorithm, by A. Chaiboul, O. Siel, Journal of Computer and Communications 3(8), Scientific Research, 2015 doi:10.4236/jcc.2015.38005

  8. [IEEEXplore] An efficient implementation of the Bellman-Ford algorithm for Kepler GPU architectures, by F. Busato, N. Bombieri, IEEE Transactions on Parallel and Distributed Systems, (Accepted for publication, already online) IEEE Press, 2015, doi:10.1109/TPDS.2015.2485994

  9. [Google Scholar] Collaborative Diffusion on the GPU for Path-Finding in Games, by Craig McMillan, Emma Hart, Kevin Chalmers, Proceedings 18th European Conference on Applications of Evolutionary Computation, Lecture Notes in Computer Science Volume 9028, pp 418-429, Springer, 2015, doi:10.1007/978-3-319-16549-3_34

  10. [Google Scholar] Toward GPU-accelerated Database Optimization, by Andreas Meister, Sebastian Breß, Gunter Saake, Datenbank-Spektrum, 15(2), pp 131-140, ISSN 1618-2162, Springer, 2015, doi:10.1007/s13222-015-0184-3

  11. [Google Scholar] Parallel Shortest Path Algorithm for Voronoi Diagrams with Generalized Distance Functions, by Julio Toss, João Luiz Dihl Comba, Bruno Raffin, XXVII SIBGRAPI, Conference on Graphics Patterns and Images, 2014.

  12. [Google Scholar] Customizing Driving Directions with GPUs, by Daniel Delling, Moritz Kobitzsch, Renato F. Werneck, Euro-Par 2014 Parallel Processing, LNCS Volume 8632, 2014, pp 728-739, Springer 2014

  13. [Google Scholar] Efficient Implementation of Hyperspectral Anomaly Detection Techniques on GPUs and Multicore Processors, by J.M. Molero, E.M. Garzon, I. Garcia, E.S. Quintana-Orti, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 7(6), pages 2256-2266, IEEE Press, 2014

  14. [Google Scholar] Performance Evaluations of Graph Database using CUDA and OpenMP-Compatible Libraries, by Shin Morishima, Hiroki Matsutani, Proc. International Symposium on Highly Efficient Accelerators and Reconfigurable Technologies, HEART'2014. Programming, CUDA, hgpu.org, 2014

• A. González-Escribano, A.J.C. van Gemund, V. Cardeñoso-Payo,
  "Mapping Unstructured Applications into Nested Parallelism",
  (Best Student Paper Award)
  VecPar 2002, 5th International Meeting, High Performance Computing for Computational Science,
  Porto, Portugal, June 26-28, 2002, Pag. 469-482
  J.M.L.M. Palma, Jack Dongarra, Vicente Hernández, A. Augusto Sousa (Eds.): High Performance Computing for Computational Science - VECPAR 2002, Selected Papers and Invited Talks
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• A. González Escribano, A.J.C. van Gemund,
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• A.L. Varbanescu, M. Nijhuis, A. González-Escribano, H. Sips, H. Bos, H. Bal
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• A. García-Yáguez, D.R. Llanos, A. Gonzalez-Escribano.
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• A. González-Escribano, A.J.C. van Gemund, V. Cardeñoso-Payo
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• A. González Escribano, Valentín Cardeñoso Payo, A.J.C. van Gemund,
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• H. Ortega-Arranz, Y. Torres, D.R. Llanos, A. Gonzalez-Escribano.
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• A. Gonzalez-Escribano, D.R. Llanos, D. Orden, B. Palop.
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• S. Aldea, D.R. Llanos, A. Gonzalez-Escribano.
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• S. Aldea, A. Estébanez, D.R. Llanos, A. Gonzalez-Escribano.
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  1. [ResearchGate] Jacques Henri Collet, Piotr Zajac, A. Napieralski, Mariusz Zubert, The Scalability Wall in the Multicore Paradigm (v.2), Technical Report, number: 2016, N° 16223 (reg. copyrightdepot.com), Affiliation: Laboratoire d'Analyse et d'Architecture des Systèmes du CNRS, Toulouse, Aug 2016, doi:10.13140/RG.2.2.35713.04968

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• A. Gonzalez-Escribano, Y. Torres, J. Fresno, D.R. Llanos.
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  1. [ResearchGate] Feng Lu, Yusuke Sugano, Takahiro Okabe, Adaptive Linear Regression for Appearance-Based Gaze Estimation, IEEE Transactions on Pattern Analysis and Machine Intelligence, 36(10), IEEE Press, Oct 2014. doi:10.1109/TPAMI.2014.2313123

• J. Fresno, A. Gonzalez-Escribano, D.R. Llanos.
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  1. [ResearchGate] Feng Lu, Yusuke Sugano, Takahiro Okabe, Adaptive Linear Regression for Appearance-Based Gaze Estimation, IEEE Transactions on Pattern Analysis and Machine Intelligence, 36(10), IEEE Press, Oct 2014. doi:10.1109/TPAMI.2014.2313123

• J. Fresno, A. Gonzalez-Escribano, D.R. Llanos.
  Automatic Data Partitioning Applied to Multigrid PDE Solvers.
  EuroMicro PDP'2011, 19th Euromicro International Conference on Parallel Distributed and Network-based Computing.
  Ayia Napa (Chipre), 2011.
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  1. [ResearchGate] Rui Ding, Rong-Cai Zhao, Lin Han, Data Decomposition Algorithm Based on Array Life Cycle, Journal of Software 24(12):2843-2858, China Science Press, Dec 2014. doi:10.3724/SP.J.1001.2013.04405

• C. de Blas Cartón, A. Gonzalez-Escribano, D.R. Llanos.
  Effortless and Efficient Distributed Data-partitioning in Linear Algebra.
  HPCC'10, 12th IEEE International Conference on High Performance Computing and Communications.
  Melbourne (Australia), 2010. Proceedings, pag. 89-97, ISBN: 978-1-4244-8335-8, IEEE Press 2010,
  doi:10.1109/HPCC.2010.37.

  1. [ResearchGate] Tobias Fuchs, Karl Fürlinger, Expressing and Exploiting Multi-Dimensional Locality in DASH, Chapter, Software for Exascale Computing - SPPEXA 2013-2015, Lecture Notes in Computational Science and Engineering, vol. 112, pp 341-359. Springer 2016, doi:10.1007/978-3-319-40528-5_15

• A. Estébanez, D.R. Llanos, A. Gonzalez-Escribano.
  New Data Structures to Handle Speculative Parallelization at Runtime.
  International Journal of Parallel Programming, (to be published: already on-line), Springer, 2015
  doi:10.1007/s10766-014-0347-0

  1. [ResearchGate] Yaobin Wang, Hong An, Zhiqin Liu, Tao Liu, Dongmei Zhao, Parallelizing Back Propagation Neural Network on Speculative Multicores, 2016 IEEE 22nd International Conference on Parallel and Distributed Systems (ICPADS), IEEE Press, ISSN 1521-9097 doi:10.1109/ICPADS.2016.0121

  2. [ResearchGate] Jacques Henri Collet, Piotr Zajac, A. Napieralski, Mariusz Zubert, The Scalability Wall in the Multicore Paradigm (v.2), Technical Report, number: 2016, N° 16223 (reg. copyrightdepot.com), Affiliation: Laboratoire d'Analyse et d'Architecture des Systèmes du CNRS, Toulouse, Aug 2016, doi:10.13140/RG.2.2.35713.04968

• S. Aldea, A. Estébanez, D.R. Llanos, A. Gonzalez-Escribano.
  A New GCC Plugin-Based Compiler Pass to Add Support for Thread-Level Speculation into OpenMP.
  Euro-Par 2014. Porto (Portugal), 2014. Proceedings, LNCS 8632, pp.234-245, Springer, ISBN: 978-3-319-09873-9

  1. [Google Scholar] Library-based solutions for algorithms with complex patterns of parallelism, by Carlos Hugo González Vázquez, PhD Thesis, Universidade da Coruña, 2015

• A. García-Yáguez, D.R. Llanos, A. Gonzalez-Escribano.
  Exclusive Squashing for Thread-Level Speculation.
  20th International ACM Symposium on High Performance Parallel and Distributed Computing (HPDC 2011). San Jose, California (USA), 2011. Proceedings, pags 275-276, ISBN 978-1-4503-0552-5

  1. [Google Scholar] Simultaneous Inspection: Hiding the Overhead of Inspector-Executor Style Dynamic Parallelization, by Daniel Brinkers, Ronald Veldema, Michael Philippsen, Proceedings 27th International Workshop Languages and Compilers for Parallel Computing LCPC 2014, pp 101-115, Lecture Notes in Computer Science Volume 8967, 2015, pp 101-115, Springer, 2015, doi:10.1007/978-3-319-17473-0_7

• A. González Escribano, Valentín Cardeñoso Payo, A.J.C. van Gemund,
  Approximating Unstructured Task Parallelism in Series-Parallel Form,
  Proceedings of the third annual conference of the Advanced School for Computing and Imaging, ASCI'97,
  Heijen, June 1997, Pag. 76-82

  1. [CiteSeerX][Google Scholar] Task Graph Performance Bounds Through Comparison Methods by András Zoltán Salamon, Tech.Rep. 2001

• J. Fresno, A. Gonzalez-Escribano, D.R. Llanos.
  Blending Extensibility and Performance in Dense and Sparse Parallel Data Management.,
  IEEE Transactions on Parallel and Distributed Systems, 25 (10), pag. 2509-2519, IEEE Press, 2014.

  1. [Research Gate] Integrating frequent pattern clustering and branch-and-bound approaches for data partitioning Yin-Fu Huang, , Chen-Ju Lai, Information Sciences, Volume 328, Pages 288-301, Elsevier, 2015

• A. González-Escribano, D.R. Llanos
  Trasgo: A Nested-Parallel Programming System,
  The Journal of Supercomputing,
  Springer, doi:10.1007/s11227-009-0367-5
  ISSN: 0920-8542

  1. [Google Scholar] Data-Driven Tasks and their Implementation Sagnak Tasirlar, Vivek Sarkar, International Conference on Parallel Processing (ICPP) 2011, pages 652-661, IEEE Press, 2011

• H. Ortega-Arranz, D. R. Llanos, and A. Gonzalez-Escribano
  The shortest-path problem: Analysis and comparison of methods
  Synthesis Lectures on Theoretical Computer Science, pag. 1-87
  Morgan & Claypool Publishers, 2014. ISBN: 9781627055390

  1. [ResearchGate] Ali Malik, Benjamin Aziz, Mo Adda, Chih-Heng Ke. Optimisation Methods for Fast Restoration of Software-Defined Networks. IEEE Access. Volume 5. pp 16111-16123. IEEE 2017. doi:10.1109/ACCESS.2017.2736949.

• H. Ortega-Arranz, Y. Torres, A. Gonzalez-Escribano, D.R. Llanos.
  Comprehensive Evaluation of a New GPU-based Approach to the Shortest Path Problem.
  International Journal of Parallel Programming, 43 (5),
  pag. 918-938,
  Springer, 2015.

  1. [ACMdl] J. Kovanen, T. Sarjakosk, Tilewise Accumulated Cost Surface Computation with Graphics Processing Units, ACM Transactions on Spatial Algorithms and Systems 1(2), Article No. 8, ACM, 2015, doi:10.1145/2803172

• H. Ortega-Arranz, D.R. Llanos, A. Gonzalez-Escribano,
  The Shortest-Path Problem: Analysis and Comparison of Methods,
  Book: Synthesis Lectures on Theoretical Computer Science,
  pag. 1-87, ISBN: 9781627055390
  Morgan & Claypool Publishers, 2014.

  1. [ResearchGate] Johnathan Votion, Yongcan Cao, Multi-Objective Cooperative Search of Spatially Diverse Routes in Uncertain Environments, arXiv:1703.04881 [cs.SY], Mar 2017

• A.J. Dorta, A. González-Escribano, C. Rodríguez, F. de Sande
  The OpenMP Source Code Repository: an Infrastructure to Contribute to the Development of OpenMP,
  EWOMP'04, Sixth European Workshop on OpenMP, Estocolmo (Suecia), 2004.
  Proceedings, pag. 57-62.

  1. [Google Scholar] Method and apparatus for detection and optimization of presumably parallel program regions, by Leon Schwartz, US Patent: US 8645933 B2, 2008

• A. González-Escribano, A.J.C. van Gemund, V. Cardeñoso-Payo, H-X. Lin, A. Vaca-Díez,
  Expressiveness versus Optimizability in Coordinating Parallelism,
  Parallel Computing (ParCo)'99,
  Delft, The Netherlands, August 17-20 1999
  Parallel Computing, Fundamentals & Applications (Proceedings of the International Conference ParCo99)
  Editors: D'Hollander, Joubert, Peters, Sips
  Imperial College Press
  ISBN: 1-86094-235-0
  Pag. 526-533

  1. [CiteSeerX][Google Scholar] Task Graph Performance Bounds Through Comparison Methods by András Zoltán Salamon, Tech.Rep. 2001

• H. Ortega-Arranz, Y. Torres, A. Gonzalez-Escribano, D.R. Llanos.
  TuCCompi: A Multi-layer Model for Distributed Heterogeneous Computing with Tuning Capabilities.
  International Journal of Parallel Programming, 43 (5), pag. 939-960, Springer, 2015. JCR 3º-quarter

  1. [ResearchGate] Yong Ma, Yujiao Zhao, Jiantao Diao, Langxiong Gan, Huaxiong Bi, Jingming Zhao, Design of Sail-Assisted Unmanned Surface Vehicle Intelligent Control System Mathematical Problems in Engineering, Volume 2016, Article ID 2958240, 13 pages doi:10.1155/2016/2958240

• A. Gonzalez-Escribano, A.J.C. van Gemund, V. Cardeñoso-Payo,
  An XML Structured Representation for Nested-Parallel Programming Languages,
  Proc. CPC 2004, 11th International Workshop on Compilers for Parallel Computers,
  pag. 149-160,
  2004

  1. [Google Scholar] M. Nijhuis, H. Bos, H.E. Bal, Supporting Reconfigurable Parallel Multimedia Applications, Proc. Euro-Par 2006 Parallel Processing, Volume 4128 of the series Lecture Notes in Computer Science, pp 765-776, Springer-Verlag, 2004

2017: 2
2016: 17
2015: 32
2014: 42
2013: 22
2012: 33