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Gabriele Mencagli
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- affiliation: University of Pisa, Italy
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2020 – today
- 2024
- [j39]Gabriele Mencagli, Massimo Torquati, Dalvan Griebler
, Alessandra Fais, Marco Danelutto:
General-purpose data stream processing on heterogeneous architectures with WindFlow. J. Parallel Distributed Comput. 184: 104782 (2024) - [j38]Alberto Ottimo, Gabriele Mencagli, Marco Danelutto:
Boosting general-purpose stream processing with reconfigurable hardware. J. Supercomput. 80(9): 13048-13078 (2024) - [j37]Gabriele Mencagli
Springald: GPU-Accelerated Window-Based Aggregates Over Out-of-Order Data Streams. IEEE Trans. Parallel Distributed Syst. 35(9): 1657-1671 (2024) - [c45]Elena Ascari
OUTFIT: Crowdsourced Data Feeding Noise Maps in Digital Twins. FRAME@HPDC 2024 - [e3]Patrizio Dazzi, Gabriele Mencagli, David K. Lowenthal, Rosa M. Badia:
Proceedings of the 33rd International Symposium on High-Performance Parallel and Distributed Computing, HPDC 2024, Pisa, Italy, June 3-7, 2024. ACM 2024, ISBN 979-8-4007-0413-0 [contents] - 2023
- [j36]Adriano Vogel
Online and transparent self-adaptation of stream parallel patterns. Computing 105(5): 1039-1057 (2023) - [j35]Nicolò Tonci, Massimo Torquati, Gabriele Mencagli, Marco Danelutto:
Distributed-Memory FastFlow Building Blocks. Int. J. Parallel Program. 51(1): 1-21 (2023) - [c44]Fausto Frasca
Accelerating Stream Processing Queries with Congestion-aware Scheduling and Real-time Linux Threads. CF 2023: 144-153 - [c43]Marco Aldinucci, Robert Birke, Antonio Brogi
A Proposal for a Continuum-aware Programming Model: From Workflows to Services Autonomously Interacting in the Compute Continuum. COMPSAC 2023: 1852-1857 - [c42]Ricardo Leonarczyk
Evaluation of Adaptive Micro-batching Techniques for GPU-Accelerated Stream Processing. Euro-Par Workshops (1) 2023: 81-92 - [c41]Alberto Ottimo, Gabriele Mencagli, Marco Danelutto:
FSP: a Framework for Data Stream Processing Applications targeting FPGAs. PDP 2023: 92-99 - [c40]Marco Danelutto, Gabriele Mencagli, Alberto Ottimo, Francesco Iannone, Paolo Palazzari
FastFlow targeting FPGAs. PDP 2023: 104-108 - [c39]William Fornaciari, Federico Reghenzani, Federico Terraneo, Davide Baroffio
RISC-V-Based Platforms for HPC: Analyzing Non-functional Properties for Future HPC and Big-Data Clusters. SAMOS 2023: 395-410 - 2022
- [c38]Gabriele Mencagli, Dalvan Griebler
Towards Parallel Data Stream Processing on System-on-Chip CPU+GPU Devices. PDP 2022: 34-38 - 2021
- [j34]Cristiana Barbosa Bentes, Felipe M. G. França
Novel parallel processing techniques for IoT-based machine learning applications. Concurr. Comput. Pract. Exp. 33(11) (2021) - [j33]Charles Michael Stein, Dinei A. Rockenbach
Latency-aware adaptive micro-batching techniques for streamed data compression on graphics processing units. Concurr. Comput. Pract. Exp. 33(11) (2021) - [j32]Júnior Löff
The NAS Parallel Benchmarks for evaluating C++ parallel programming frameworks on shared-memory architectures. Future Gener. Comput. Syst. 125: 743-757 (2021) - [j31]Marco Danelutto
Algorithmic Skeletons and Parallel Design Patterns in Mainstream Parallel Programming. Int. J. Parallel Program. 49(2): 177-198 (2021) - [j30]Gabriele Mencagli
WindFlow: High-Speed Continuous Stream Processing With Parallel Building Blocks. IEEE Trans. Parallel Distributed Syst. 32(11): 2748-2763 (2021) - [c37]Davide Bacciu, Siranush Akarmazyan, Eric Armengaud
TEACHING - Trustworthy autonomous cyber-physical applications through human-centred intelligence. COINS 2021: 1-6 - [c36]Emanuele Carlini, Lorenzo Carnevale, Massimo Coppola, Patrizio Dazzi, Gabriele Mencagli, Domenico Talia, Massimo Villari:
An Osmotic Ecosystem for Data Streaming Applications in Smart Cities. FRAME@HPDC 2021: 27-31 - [c35]Dimitris Palyvos-Giannas, Gabriele Mencagli, Marina Papatriantafilou, Vincenzo Gulisano:
Lachesis: a middleware for customizing OS scheduling of stream processing queries. Middleware 2021: 365-378 - [c34]Adriano Vogel
Towards On-the-fly Self-Adaptation of Stream Parallel Patterns. PDP 2021: 89-93 - [c33]Valeria Cardellini
The 4th International Workshop on Autonomic Solutions for Parallel and Distributed Data Stream Processing (Auto-DaSP 2021). ICPE 2021: 285-286 - [d2]Júnior Löff
NPB-CPP: NAS Parallel Benchmarks for evaluating C++ parallel programming frameworks on shared-memory architectures. Zenodo, 2021 - [i1]Davide Bacciu, Siranush Akarmazyan, Eric Armengaud, Manlio Bacco, George Bravos, Calogero Calandra, Emanuele Carlini, Antonio Carta, Pietro Cassarà, Massimo Coppola, Charalampos Davalas, Patrizio Dazzi, Maria Carmela De Gennaro, Daniele Di Sarli, Jürgen Dobaj, Claudio Gallicchio, Sylvain Girbal, Alberto Gotta, Riccardo Groppo, Vincenzo Lomonaco, Georg Macher, Daniele Mazzei, Gabriele Mencagli, Dimitrios Michail, Alessio Micheli, Roberta Peroglio, Salvatore Petroni, Rosaria Potenza, Farank Pourdanesh, Christos Sardianos, Konstantinos Tserpes, Fulvio Tagliabo, Jakob Valtl, Iraklis Varlamis, Omar Veledar:
TEACHING - Trustworthy autonomous cyber-physical applications through human-centred intelligence. CoRR abs/2107.06543 (2021) - 2020
- [j29]Maycon Viana Bordin, Dalvan Griebler
DSPBench: A Suite of Benchmark Applications for Distributed Data Stream Processing Systems. IEEE Access 8: 222900-222917 (2020) - [j28]Luca Rinaldi, Massimo Torquati
Improving the Performance of Actors on Multi-cores with Parallel Patterns. Int. J. Parallel Program. 48(4): 692-712 (2020) - [j27]Marco Aldinucci
Data stream processing in HPC systems: New frameworks and architectures for high-frequency streaming. Parallel Comput. 98: 102694 (2020) - [j26]José Daniel García
Challenging the abstraction penalty in parallel patterns libraries. J. Supercomput. 76(7): 5139-5159 (2020) - [c32]Luca Rinaldi, Massimo Torquati
High-throughput stream processing with actors. AGERE!@SPLASH 2020: 1-10 - [c31]Leandro A. J. Marzulo, Tiago A. O. Alves, Cristiana Bentes, Gabriele Mencagli:
Workshop 15: MPP Parallel Programming Models - Special Edition Machine Learning Performance and Security. IPDPS Workshops 2020: 838-839
2010 – 2019
- 2019
- [j25]Tiziano De Matteis
GASSER: An Auto-Tunable System for General Sliding-Window Streaming Operators on GPUs. IEEE Access 7: 48753-48769 (2019) - [j24]Gabriele Mencagli
Raising the Parallel Abstraction Level for Streaming Analytics Applications. IEEE Access 7: 131944-131961 (2019) - [j23]Massimo Torquati
Power-aware pipelining with automatic concurrency control. Concurr. Comput. Pract. Exp. 31(5) (2019) - [j22]Valeria Cardellini
New Landscapes of the Data Stream Processing in the era of Fog Computing. Future Gener. Comput. Syst. 99: 646-650 (2019) - [j21]Caio B. G. Carvalho, Victor da Cruz Ferreira, Felipe M. G. França
A dataflow runtime environment and static scheduler for edge, fog and in-situ computing. Int. J. Grid Util. Comput. 10(3): 235-247 (2019) - [j20]Gabriele Mencagli, Felipe M. G. França
Special issue on parallel applications for in-situ computing on the next-generation computing platforms. Int. J. High Perform. Comput. Appl. 33(3) (2019) - [j19]Marco Danelutto
The RePhrase Extended Pattern Set for Data Intensive Parallel Computing. Int. J. Parallel Program. 47(1): 74-93 (2019) - [j18]Massimo Torquati
On dynamic memory allocation in sliding-window parallel patterns for streaming analytics. J. Supercomput. 75(8): 4114-4131 (2019) - [c30]Marco Danelutto
Autonomic management experiences in structured parallel programming. HPCS 2019: 336-343 - [c29]Dinei A. Rockenbach
Stream Processing on Multi-cores with GPUs: Parallel Programming Models' Challenges. IPDPS Workshops 2019: 834-841 - [c28]Luca Rinaldi, Massimo Torquati
Accelerating Actor-Based Applications with Parallel Patterns. PDP 2019: 140-147 - [e2]Gabriele Mencagli, Dora B. Heras, Valeria Cardellini, Emiliano Casalicchio, Emmanuel Jeannot, Felix Wolf, Antonio Salis
Euro-Par 2018: Parallel Processing Workshops - Euro-Par 2018 International Workshops, Turin, Italy, August 27-28, 2018, Revised Selected Papers. Lecture Notes in Computer Science 11339, Springer 2019, ISBN 978-3-030-10548-8 [contents] - 2018
- [j17]Gabriele Mencagli
Elastic-PPQ: A two-level autonomic system for spatial preference query processing over dynamic data streams. Future Gener. Comput. Syst. 79: 862-877 (2018) - [j16]Gabriele Mencagli
The home-forwarding mechanism to reduce the cache coherence overhead in next-generation CMPs. Future Gener. Comput. Syst. 82: 493-509 (2018) - [j15]Marco Danelutto
State access patterns in stream parallel computations. Int. J. High Perform. Comput. Appl. 32(6) (2018) - [j14]Gabriele Mencagli
Harnessing sliding-window execution semantics for parallel stream processing. J. Parallel Distributed Comput. 116: 74-88 (2018) - [j13]Marco Danelutto
Data stream processing via code annotations. J. Supercomput. 74(11): 5659-5673 (2018) - [c27]Leandro A. J. Marzulo, Felipe Maia Galvão França
Introduction to MPP 2018. IPDPS Workshops 2018: 1229-1230 - [c26]Gabriele Mencagli, Patrizio Dazzi
SpinStreams: a Static Optimization Tool for Data Stream Processing Applications. Middleware 2018: 66-79 - [c25]Massimo Torquati
Reducing Message Latency and CPU Utilization in the CAF Actor Framework. PDP 2018: 145-153 - [c24]Dalvan Griebler
Efficient NAS Benchmark Kernels with C++ Parallel Programming. PDP 2018: 733-740 - [c23]Adriano Vogel
Parallel Stream Processing with MPI for Video Analytics and Data Visualization. WSCAD (Selected Papers) 2018: 102-116 - [e1]Dora Blanco Heras, Luc Bougé
Euro-Par 2017: Parallel Processing Workshops - Euro-Par 2017 International Workshops, Santiago de Compostela, Spain, August 28-29, 2017, Revised Selected Papers. Lecture Notes in Computer Science 10659, Springer 2018, ISBN 978-3-319-75177-1 [contents] - [d1]Dalvan Griebler, Junior Loff, Gabriele Mencagli, Marco Danelutto
Efficient NAS Benchmark Kernels with C++ Parallel Programming Frameworks for Multi-Cores. Zenodo, 2018 - 2017
- [j12]Tiziano De Matteis
Parallel Patterns for Window-Based Stateful Operators on Data Streams: An Algorithmic Skeleton Approach. Int. J. Parallel Program. 45(2): 382-401 (2017) - [j11]Tiziano De Matteis
Proactive elasticity and energy awareness in data stream processing. J. Syst. Softw. 127: 302-319 (2017) - [j10]Daniele De Sensi
Bringing Parallel Patterns Out of the Corner: The P3 ARSEC Benchmark Suite. ACM Trans. Archit. Code Optim. 14(4): 33:1-33:26 (2017) - [j9]Gabriele Mencagli
Parallel Continuous Preference Queries over Out-of-Order and Bursty Data Streams. IEEE Trans. Parallel Distributed Syst. 28(9): 2608-2624 (2017) - [c22]Antonio Brogi
Container-Based Support for Autonomic Data Stream Processing Through the Fog. Euro-Par Workshops 2017: 17-28 - [c21]Tiziano De Matteis
Elastic Scaling for Distributed Latency-Sensitive Data Stream Operators. PDP 2017: 61-68 - [c20]Marco Danelutto
P3ARSEC: towards parallel patterns benchmarking. SAC 2017: 1582-1589 - 2016
- [j8]Gabriele Mencagli
Adaptive model predictive control of autonomic distributed parallel computations with variable horizons and switching costs. Concurr. Comput. Pract. Exp. 28(7): 2187-2212 (2016) - [j7]Tiziano De Matteis
Continuous skyline queries on multicore architectures. Concurr. Comput. Pract. Exp. 28(12): 3503-3522 (2016) - [j6]Gabriele Mencagli
A Game-Theoretic Approach for Elastic Distributed Data Stream Processing. ACM Trans. Auton. Adapt. Syst. 11(2): 13:1-13:34 (2016) - [c19]Marco Danelutto
A divide-and-conquer parallel pattern implementation for multicores. SEPS@SPLASH 2016: 10-19 - [c18]Tiziano De Matteis
Keep calm and react with foresight: strategies for low-latency and energy-efficient elastic data stream processing. PPoPP 2016: 13:1-13:12 - [c17]Marco Danelutto
Efficient Dynamic Memory Allocation in Data Stream Processing Programs. UIC/ATC/ScalCom/CBDCom/IoP/SmartWorld 2016: 1181-1188 - 2015
- [c16]Tiziano De Matteis
A Multicore Parallelization of Continuous Skyline Queries on Data Streams. Euro-Par 2015: 402-413 - [c15]Marco Danelutto
Parallelizing High-Frequency Trading Applications by Using C++11 Attributes. TrustCom/BigDataSE/ISPA (3) 2015: 140-147 - 2014
- [j5]Gabriele Mencagli
Towards a systematic approach to the dynamic adaptation of structured parallel computations using model predictive control. Clust. Comput. 17(4): 1443-1463 (2014) - [j4]Daniele Buono, Gabriele Mencagli
Performance analysis and structured parallelisation of the space-time adaptive processing computational kernel on multi-core architectures. Int. J. Parallel Emergent Distributed Syst. 29(5): 460-498 (2014) - [j3]Gabriele Mencagli
A Cooperative Predictive Control Approach to Improve the Reconfiguration Stability of Adaptive Distributed Parallel Applications. ACM Trans. Auton. Adapt. Syst. 9(1): 2:1-2:27 (2014) - [c14]Daniele Buono, Gabriele Mencagli
Run-time mechanisms for fine-grained parallelism on network processors: The TILEPro64 experience. HPCS 2014: 55-64 - [c13]Daniele Buono, Tiziano De Matteis
A High-Throughput and Low-Latency Parallelization of Window-Based Stream Joins on Multicores. ISPA 2014: 117-126 - [c12]Daniele Buono, Tiziano De Matteis
Optimizing Message-Passing on Multicore Architectures Using Hardware Multi-threading. PDP 2014: 262-270 - 2013
- [c11]Gabriele Mencagli
Reconfiguration Stability of Adaptive Distributed Parallel Applications through a Cooperative Predictive Control Approach. Euro-Par 2013: 329-340 - [c10]Gabriele Mencagli
Analysis of control-theoretic predictive strategies for the adaptation of distributed parallel computations. ORMaCloud 2013: 33-40 - [c9]Gabriele Mencagli
Control-theoretic adaptation strategies for autonomic reconfigurable parallel applications on cloud environments. HPCS 2013: 11-18 - 2012
- [b1]Gabriele Mencagli:
A Control-Theoretic Methodology for Adaptive Structured Parallel Computations. University of Pisa, Italy, 2012 - 2011
- [c8]Gabriele Mencagli
QoS-control of Structured Parallel Computations: A Predictive Control Approach. CloudCom 2011: 296-303 - [c7]Carlo Bertolli, Gabriele Mencagli, Marco Vanneschi:
Consistent Rollback Protocols for Autonomic ASSISTANT Applications. Euro-Par Workshops (1) 2011: 139-148 - [c6]Carlo Bertolli, Gabriele Mencagli
Consistent reconfiguration protocols for adaptive high-performance applications. IWCMC 2011: 2121-2126 - 2010
- [j2]Carlo Bertolli, Daniele Buono, Gabriele Mencagli, Marco Vanneschi:
An Approach to Mobile Grid Platforms for the Development and Support of Complex Ubiquitous Applications. Int. J. Adv. Pervasive Ubiquitous Comput. 2(4): 24-38 (2010) - [c5]Carlo Bertolli, Gabriele Mencagli
A cost model for autonomic reconfigurations in high-performance pervasive applications. CASEMANS@Ubicomp 2010: 20-29 - [c4]Carlo Bertolli, Daniele Buono, Gabriele Mencagli
Resource discovery support for time-critical adaptive applications. IWCMC 2010: 504-508 - [c3]Carlo Bertolli, Gabriele Mencagli
Analyzing Memory Requirements for Pervasive Grid Applications. PDP 2010: 297-301
2000 – 2009
- 2009
- [j1]Romano Fantacci
Next generation grids and wireless communication networks: towards a novel integrated approach. Wirel. Commun. Mob. Comput. 9(4): 445-467 (2009) - [c2]Carlo Bertolli, Daniele Buono, Gabriele Mencagli
Expressing Adaptivity and Context Awareness in the ASSISTANT Programming Model. Autonomics 2009: 32-47 - [c1]Carlo Bertolli, Gabriele Mencagli
Adaptivity in Risk and Emergency Management Applications on Pervasive Grids. ISPAN 2009: 550-555
Coauthor Index
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last updated on 2024-12-10 21:46 CET by the dblp team
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