3 Search Results for "Aldinucci, Marco"

Document
DOI: 10.4230/LIPIcs.SEA.2025.11
CluStRE: Streaming Graph Clustering with Multi-Stage Refinement

Authors: Adil Chhabra, Shai Dorian Peretz, and Christian Schulz

Published in: LIPIcs, Volume 338, 23rd International Symposium on Experimental Algorithms (SEA 2025)

Abstract
We present CluStRE, a novel streaming graph clustering algorithm that balances computational efficiency with high-quality clustering using multi-stage refinement. Unlike traditional in-memory clustering approaches, CluStRE processes graphs in a streaming setting, significantly reducing memory overhead while leveraging re-streaming and evolutionary heuristics to improve solution quality. Our method dynamically constructs a quotient graph, enabling modularity-based optimization while efficiently handling large-scale graphs. We introduce multiple configurations of CluStRE to provide trade-offs between speed, memory consumption, and clustering quality. Experimental evaluations demonstrate that CluStRE improves solution quality by 89.8%, operates 2.6× faster, and uses less than two-thirds of the memory required by the state-of-the-art streaming clustering algorithm on average. Moreover, our strongest mode enhances solution quality by up to 150% on average. With this, CluStRE achieves comparable solution quality to in-memory algorithms, i.e. over 96% of the quality of clustering approaches, including Louvain, effectively bridging the gap between streaming and traditional clustering methods.
Cite as

Adil Chhabra, Shai Dorian Peretz, and Christian Schulz. CluStRE: Streaming Graph Clustering with Multi-Stage Refinement. In 23rd International Symposium on Experimental Algorithms (SEA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 338, pp. 11:1-11:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{chhabra_et_al:LIPIcs.SEA.2025.11,
  author =	{Chhabra, Adil and Dorian Peretz, Shai and Schulz, Christian},
  title =	{{CluStRE: Streaming Graph Clustering with Multi-Stage Refinement}},
  booktitle =	{23rd International Symposium on Experimental Algorithms (SEA 2025)},
  pages =	{11:1--11:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-375-1},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{338},
  editor =	{Mutzel, Petra and Prezza, Nicola},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2025.11},
  URN =		{urn:nbn:de:0030-drops-232493},
  doi =		{10.4230/LIPIcs.SEA.2025.11},
  annote =	{Keywords: graph clustering, community, streaming, online, memetic, evolutionary}
}
Document
Invited Paper
DOI: 10.4230/OASIcs.PARMA-DITAM.2021.5
HPC Application Cloudification: The StreamFlow Toolkit (Invited Paper)

Authors: Iacopo Colonnelli, Barbara Cantalupo, Roberto Esposito, Matteo Pennisi, Concetto Spampinato, and Marco Aldinucci

Published in: OASIcs, Volume 88, 12th Workshop on Parallel Programming and Run-Time Management Techniques for Many-core Architectures and 10th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2021)

Abstract
Finding an effective way to improve accessibility to High-Performance Computing facilities, still anchored to SSH-based remote shells and queue-based job submission mechanisms, is an open problem in computer science. This work advocates a cloudification of HPC applications through a cluster-as-accelerator pattern, where computationally demanding portions of the main execution flow hosted on a Cloud Finding an effective way to improve accessibility to High-Performance Computing facilities, still anchored to SSH-based remote shells and queue-based job submission mechanisms, is an open problem in computer science. This work advocates a cloudification of HPC applications through a cluster-as-accelerator pattern, where computationally demanding portions of the main execution flow hosted on a Cloud infrastructure can be offloaded to HPC environments to speed them up. We introduce StreamFlow, a novel Workflow Management System that supports such a design pattern and makes it possible to run the steps of a standard workflow model on independent processing elements with no shared storage. We validated the proposed approach’s effectiveness on the CLAIRE COVID-19 universal pipeline, i.e. a reproducible workflow capable of automating the comparison of (possibly all) state-of-the-art pipelines for the diagnosis of COVID-19 interstitial pneumonia from CT scans images based on Deep Neural Networks (DNNs).
Cite as

Iacopo Colonnelli, Barbara Cantalupo, Roberto Esposito, Matteo Pennisi, Concetto Spampinato, and Marco Aldinucci. HPC Application Cloudification: The StreamFlow Toolkit (Invited Paper). In 12th Workshop on Parallel Programming and Run-Time Management Techniques for Many-core Architectures and 10th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2021). Open Access Series in Informatics (OASIcs), Volume 88, pp. 5:1-5:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{colonnelli_et_al:OASIcs.PARMA-DITAM.2021.5,
  author =	{Colonnelli, Iacopo and Cantalupo, Barbara and Esposito, Roberto and Pennisi, Matteo and Spampinato, Concetto and Aldinucci, Marco},
  title =	{{HPC Application Cloudification: The StreamFlow Toolkit}},
  booktitle =	{12th Workshop on Parallel Programming and Run-Time Management Techniques for Many-core Architectures and 10th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2021)},
  pages =	{5:1--5:13},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-181-8},
  ISSN =	{2190-6807},
  year =	{2021},
  volume =	{88},
  editor =	{Bispo, Jo\~{a}o and Cherubin, Stefano and Flich, Jos\'{e}},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.PARMA-DITAM.2021.5},
  URN =		{urn:nbn:de:0030-drops-136419},
  doi =		{10.4230/OASIcs.PARMA-DITAM.2021.5},
  annote =	{Keywords: cloud computing, distributed computing, high-performance computing, streamflow, workflow management systems}
}
Document
DOI: 10.4230/LITES-v003-i001-a003
Modeling Power Consumption and Temperature in TLM Models

Authors: Matthieu Moy, Claude Helmstetter, Tayeb Bouhadiba, and Florence Maraninchi

Published in: LITES, Volume 3, Issue 1 (2016). Leibniz Transactions on Embedded Systems, Volume 3, Issue 1

Abstract
Many techniques and tools exist to estimate the power consumption and the temperature map of a chip. These tools help the hardware designers develop power efficient chips in the presence of temperature constraints. For this task, the application can be ignored or at least abstracted by some high level scenarios; at this stage, the actual embedded software is generally not available yet.However, after the hardware is defined, the embedded software can still have a significant influence on the power consumption; i.e., two implementations of the same application can consume more or less power. Moreover, the actual software power manager ensuring the temperature constraints, usually by acting dynamically on the voltage and frequency, must itself be validated. Validating such power management policy requires a model of both actuators and sensors, hence a closed-loop simulation of the functional model with a non-functional one.In this paper, we present and compare several tools to simulate the power and thermal behavior of a chip together with its functionality. We explore several levels of abstraction and study the impact on the precision of the analysis.
Cite as

Matthieu Moy, Claude Helmstetter, Tayeb Bouhadiba, and Florence Maraninchi. Modeling Power Consumption and Temperature in TLM Models. In LITES, Volume 3, Issue 1 (2016). Leibniz Transactions on Embedded Systems, Volume 3, Issue 1, pp. 03:1-03:29, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)

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@Article{moy_et_al:LITES-v003-i001-a003,
  author =	{Moy, Matthieu and Helmstetter, Claude and Bouhadiba, Tayeb and Maraninchi, Florence},
  title =	{{Modeling Power Consumption and Temperature in TLM Models}},
  journal =	{Leibniz Transactions on Embedded Systems},
  pages =	{03:1--03:29},
  ISSN =	{2199-2002},
  year =	{2016},
  volume =	{3},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LITES-v003-i001-a003},
  URN =		{urn:nbn:de:0030-drops-192584},
  doi =		{10.4230/LITES-v003-i001-a003},
  annote =	{Keywords: Power consumption, Temperature control, Virtual prototype, SystemC, Transactional modeling}
}
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