3 Search Results for "Schuster, Assaf"

Document
DOI: 10.4230/OASIcs.NG-RES.2025.5
SP-IMPact: A Framework for Static Partitioning Interference Mitigation and Performance Analysis

Authors: Diogo Costa, Gonçalo Moreira, Afonso Oliveira, José Martins, and Sandro Pinto

Published in: OASIcs, Volume 128, Sixth Workshop on Next Generation Real-Time Embedded Systems (NG-RES 2025)

Abstract
Modern embedded systems are evolving toward complex, heterogeneous architectures to accommodate increasingly demanding applications. Driven by industry SWAP-C (Size, Weight, Power, and Cost) constraints, this shift has led to the consolidation of multiple systems onto single hardware platforms. Static Partitioning Hypervisors (SPHs) offer a promising solution to partition hardware resources and provide spatial isolation between critical workloads. However, shared hardware resources like the Last-Level Cache (LLC) and system bus can introduce significant temporal interference between virtual machines (VMs), negatively impacting performance and predictability. Over the past decade, academia and industry have focused on developing interference mitigation techniques, such as cache partitioning and memory bandwidth reservation. Configuring these techniques, however, is complex and time-consuming. Cache partitioning requires careful balancing of cache sections across VMs, while memory bandwidth reservation requires tuning bandwidth budgets and periods. With numerous possible configurations, testing all combinations is impractical and often leads to suboptimal configurations. Moreover, there is a gap in understanding how these techniques interact, as their combined use can result in compounded or conflicting effects on system performance. Static analysis solutions that estimate worst-case execution times (WCET) and upper bounds on execution times provide some guidance for configuring interference mitigation techniques. While useful in identifying potential interference effects, these tools often fail to capture the full complexity of modern multi-core systems, as they typically focus on a limited set of shared resources and neglect other sources of contention, such as IOMMUs and interrupt controllers. To address these challenges, we introduce SP-IMPact, an open-source framework designed to analyze and guide the configuration of interference mitigation techniques, through the deployment of diverse VM configurations and setups, and assessment of hardware-level contention (leveraging SPHs). It supports two mitigation techniques: (i) cache coloring and (ii) memory bandwidth reservation, while also evaluating the interactions between these techniques and their cumulative impact on system performance. By providing insights on real hardware platforms, SP-IMPact helps to optimize the configuration of these techniques in mixed-criticality systems, ensuring both performance and predictability.
Cite as

Diogo Costa, Gonçalo Moreira, Afonso Oliveira, José Martins, and Sandro Pinto. SP-IMPact: A Framework for Static Partitioning Interference Mitigation and Performance Analysis. In Sixth Workshop on Next Generation Real-Time Embedded Systems (NG-RES 2025). Open Access Series in Informatics (OASIcs), Volume 128, pp. 5:1-5:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{costa_et_al:OASIcs.NG-RES.2025.5,
  author =	{Costa, Diogo and Moreira, Gon\c{c}alo and Oliveira, Afonso and Martins, Jos\'{e} and Pinto, Sandro},
  title =	{{SP-IMPact: A Framework for Static Partitioning Interference Mitigation and Performance Analysis}},
  booktitle =	{Sixth Workshop on Next Generation Real-Time Embedded Systems (NG-RES 2025)},
  pages =	{5:1--5:15},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-366-9},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{128},
  editor =	{Yomsi, Patrick Meumeu and Wildermann, Stefan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.NG-RES.2025.5},
  URN =		{urn:nbn:de:0030-drops-229911},
  doi =		{10.4230/OASIcs.NG-RES.2025.5},
  annote =	{Keywords: Virtualization, Contention, Multi-core Interference, Mixed-Criticality Systems, Arm}
}
Document
Survey
DOI: 10.4230/TGDK.1.1.11
How Does Knowledge Evolve in Open Knowledge Graphs?

Authors: Axel Polleres, Romana Pernisch, Angela Bonifati, Daniele Dell'Aglio, Daniil Dobriy, Stefania Dumbrava, Lorena Etcheverry, Nicolas Ferranti, Katja Hose, Ernesto Jiménez-Ruiz, Matteo Lissandrini, Ansgar Scherp, Riccardo Tommasini, and Johannes Wachs

Published in: TGDK, Volume 1, Issue 1 (2023): Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge, Volume 1, Issue 1

Abstract
Openly available, collaboratively edited Knowledge Graphs (KGs) are key platforms for the collective management of evolving knowledge. The present work aims t o provide an analysis of the obstacles related to investigating and processing specifically this central aspect of evolution in KGs. To this end, we discuss (i) the dimensions of evolution in KGs, (ii) the observability of evolution in existing, open, collaboratively constructed Knowledge Graphs over time, and (iii) possible metrics to analyse this evolution. We provide an overview of relevant state-of-the-art research, ranging from metrics developed for Knowledge Graphs specifically to potential methods from related fields such as network science. Additionally, we discuss technical approaches - and their current limitations - related to storing, analysing and processing large and evolving KGs in terms of handling typical KG downstream tasks.
Cite as

Axel Polleres, Romana Pernisch, Angela Bonifati, Daniele Dell'Aglio, Daniil Dobriy, Stefania Dumbrava, Lorena Etcheverry, Nicolas Ferranti, Katja Hose, Ernesto Jiménez-Ruiz, Matteo Lissandrini, Ansgar Scherp, Riccardo Tommasini, and Johannes Wachs. How Does Knowledge Evolve in Open Knowledge Graphs?. In Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge (TGDK), Volume 1, Issue 1, pp. 11:1-11:59, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@Article{polleres_et_al:TGDK.1.1.11,
  author =	{Polleres, Axel and Pernisch, Romana and Bonifati, Angela and Dell'Aglio, Daniele and Dobriy, Daniil and Dumbrava, Stefania and Etcheverry, Lorena and Ferranti, Nicolas and Hose, Katja and Jim\'{e}nez-Ruiz, Ernesto and Lissandrini, Matteo and Scherp, Ansgar and Tommasini, Riccardo and Wachs, Johannes},
  title =	{{How Does Knowledge Evolve in Open Knowledge Graphs?}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{11:1--11:59},
  year =	{2023},
  volume =	{1},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.1.1.11},
  URN =		{urn:nbn:de:0030-drops-194855},
  doi =		{10.4230/TGDK.1.1.11},
  annote =	{Keywords: KG evolution, temporal KG, versioned KG, dynamic KG}
}
Document
DOI: 10.4230/LIPIcs.ITCS.2022.65
Pseudorandom Self-Reductions for NP-Complete Problems

Authors: Reyad Abed Elrazik, Robert Robere, Assaf Schuster, and Gal Yehuda

Published in: LIPIcs, Volume 215, 13th Innovations in Theoretical Computer Science Conference (ITCS 2022)

Abstract
A language L is random-self-reducible if deciding membership in L can be reduced (in polynomial time) to deciding membership in L for uniformly random instances. It is known that several "number theoretic" languages (such as computing the permanent of a matrix) admit random self-reductions. Feigenbaum and Fortnow showed that NP-complete languages are not non-adaptively random-self-reducible unless the polynomial-time hierarchy collapses, giving suggestive evidence that NP may not admit random self-reductions. Hirahara and Santhanam introduced a weakening of random self-reductions that they called pseudorandom self-reductions, in which a language L is reduced to a distribution that is computationally indistinguishable from the uniform distribution. They then showed that the Minimum Circuit Size Problem (MCSP) admits a non-adaptive pseudorandom self-reduction, and suggested that this gave further evidence that distinguished MCSP from standard NP-Complete problems. We show that, in fact, the Clique problem admits a non-adaptive pseudorandom self-reduction, assuming the planted clique conjecture. More generally we show the following. Call a property of graphs π hereditary if G ∈ π implies H ∈ π for every induced subgraph of G. We show that for any infinite hereditary property π, the problem of finding a maximum induced subgraph H ∈ π of a given graph G admits a non-adaptive pseudorandom self-reduction.
Cite as

Reyad Abed Elrazik, Robert Robere, Assaf Schuster, and Gal Yehuda. Pseudorandom Self-Reductions for NP-Complete Problems. In 13th Innovations in Theoretical Computer Science Conference (ITCS 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 215, pp. 65:1-65:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{elrazik_et_al:LIPIcs.ITCS.2022.65,
  author =	{Elrazik, Reyad Abed and Robere, Robert and Schuster, Assaf and Yehuda, Gal},
  title =	{{Pseudorandom Self-Reductions for NP-Complete Problems}},
  booktitle =	{13th Innovations in Theoretical Computer Science Conference (ITCS 2022)},
  pages =	{65:1--65:12},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-217-4},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{215},
  editor =	{Braverman, Mark},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITCS.2022.65},
  URN =		{urn:nbn:de:0030-drops-156615},
  doi =		{10.4230/LIPIcs.ITCS.2022.65},
  annote =	{Keywords: computational complexity, pseudorandomness, worst-case to average-case, self reductions, planted clique, hereditary graph family}
}
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