49 Search Results for "Brown, Adam"

Document
DOI: 10.4230/LIPIcs.SEA.2026.7
From Relative Compression to Hierarchical Compression

Authors: Philip Bille, Inge Li Gørtz, and Máximo Pérez-López

Published in: LIPIcs, Volume 371, 24th International Symposium on Experimental Algorithms (SEA 2026)

Abstract
We introduce a framework to use any relative compression algorithm as a subroutine for hierarchical relative compression. In a dataset consisting of n sequences, it consists of constructing a rooted tree on the sequences, using hashing and similarity techniques, and compressing the children of a node relative to their parent. We build up on previous techniques [Bille et al., 2023], and optimize them further for computational efficiency. We test our framework with three existing relative compression algorithms on six genomic datasets, and we show that in datasets that contain heterogeneous data, hierarchical relative compression improves the compression ratio by a factor 2 or more, when compared to relative compression to a single sequence. Apart from compression ratio, we also explore the trade-offs with respect to compression speed, dataset decompression speed, and average sequence decompression speed. With two of the surveyed algorithms, dataset decompression becomes faster and sequence decompression remains practical, at the cost of compression time, which remains competitive for the datasets with highest variability.
Cite as

Philip Bille, Inge Li Gørtz, and Máximo Pérez-López. From Relative Compression to Hierarchical Compression. In 24th International Symposium on Experimental Algorithms (SEA 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 371, pp. 7:1-7:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{bille_et_al:LIPIcs.SEA.2026.7,
  author =	{Bille, Philip and G{\o}rtz, Inge Li and P\'{e}rez-L\'{o}pez, M\'{a}ximo},
  title =	{{From Relative Compression to Hierarchical Compression}},
  booktitle =	{24th International Symposium on Experimental Algorithms (SEA 2026)},
  pages =	{7:1--7:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-422-2},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{371},
  editor =	{Aum\"{u}ller, Martin and Finocchi, Irene},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2026.7},
  URN =		{urn:nbn:de:0030-drops-260117},
  doi =		{10.4230/LIPIcs.SEA.2026.7},
  annote =	{Keywords: Relative compression, RLZ, string collections, compressed representation, data structures, efficient algorithms}
}
Document
DOI: 10.4230/LIPIcs.SEA.2026.20
QuadRank: Engineering a High Throughput Rank

Authors: Ragnar Groot Koerkamp

Published in: LIPIcs, Volume 371, 24th International Symposium on Experimental Algorithms (SEA 2026)

Abstract
Motivation. Given a text, a query rank(q, c) counts the number of occurrences of character c among the first q characters of the text. Space-efficient methods to answer these rank queries form an important building block in many succinct data structures. For example, the FM-index [Ferragina and Manzini, 2000] is a widely used data structure that uses rank queries to locate all occurrences of a pattern in a text. In bioinformatics applications, the goal is usually to process large inputs as fast as possible. Thus, data structures should have high throughput when used with many threads. Contributions. We first survey existing results on rank data structures. For the σ = 2 binary alphabet, we then develop BiRank, which has 3.28% space overhead. BiRank merges the central ideas of two recent papers: (1) we interleave (inline) offsets in each cache line of the underlying bit vector [Laws et al., 2024], reducing cache misses, and (2) these offsets are to the middle of each block so that only half of each needs popcounting [Gottlieb and Reinert, 2025]. In QuadRank (14.4% overhead), we extend these techniques to the σ = 4 (DNA) alphabet. Both data structures typically require only a single cache miss per query, making them highly suitable for high-throughput and memory-bound settings. To enable efficient batch-processing, we support prefetching the cache lines required to answer upcoming queries. Results. BiRank and QuadRank are around 1.5× and 2× faster than similar-overhead methods that do not use interleaving. Prefetching gives an additional 2× speedup, at which point the dual-channel DDR4 RAM bandwidth becomes a hard limit on the total throughput. With prefetching, both methods outperform all other methods apart from SPIDER [Laws et al., 2024] by 2×. When using QuadRank with prefetching in a toy count-only FM-index, QuadFm, this results in a smaller size and up to 4× speedup over Genedex, a state-of-the-art batching FM-index implementation. Conclusion. Optimizing data structures for high throughput, by minimizing cache misses and branch-misses and adding support for prefetching, can result in significant speedups when benchmarks are adjusted accordingly.
Cite as

Ragnar Groot Koerkamp. QuadRank: Engineering a High Throughput Rank. In 24th International Symposium on Experimental Algorithms (SEA 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 371, pp. 20:1-20:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{grootkoerkamp:LIPIcs.SEA.2026.20,
  author =	{Groot Koerkamp, Ragnar},
  title =	{{QuadRank: Engineering a High Throughput Rank}},
  booktitle =	{24th International Symposium on Experimental Algorithms (SEA 2026)},
  pages =	{20:1--20:23},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-422-2},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{371},
  editor =	{Aum\"{u}ller, Martin and Finocchi, Irene},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2026.20},
  URN =		{urn:nbn:de:0030-drops-260248},
  doi =		{10.4230/LIPIcs.SEA.2026.20},
  annote =	{Keywords: Rank, Succinct Data Structures, Cache Performance, Prefetching}
}
Document
DOI: 10.4230/OASIcs.AEiC.2026.2
Discovering and Repairing Flaws in C Binaries Without Requiring Codebase and Instrumentation

Authors: Diogo Ferreira and Ibéria Medeiros

Published in: OASIcs, Volume 143, 30th Ada-Europe International Conference on Reliable Software Technologies (AEiC 2026)

Abstract
Industrial and embedded software systems frequently integrate various third-party components sourced from diverse providers into their codebases. These systems are commonly developed in C, a language known for its lack of variable bounds checking, making it vulnerable to Buffer Overflows (BOs), which, when exploited, can cause severe damage. Consequently, the binary code resulting from vulnerable C programs is also vulnerable and remains so in the final products. Fixing these software systems is challenging because only binary code is available. This paper presents PatchBin, a binary patching tool to automatically fix BO vulnerabilities and validate the effectiveness of fixes while ensuring no new flaws are introduced. The approach involves a combination of fuzzing, reverse static analysis and static rewriting techniques to, respectively, (i) identify possible malicious inputs that can trigger BOs, (ii) find their root cause by employing reverse data flow analysis, and (iii) remove them by rewriting the binary code with effective validation, thus generating a new binary without the original flaws and new ones. Experimental evaluations with synthetic and real-world applications demonstrated that PatchBin detects and fixes BO in binary programs without introducing new vulnerabilities. The results showed that PatchBin is an important aid for industrial partners, enabling them to test and fix their products, including third-party components, without access to source code, but only to binary code.
Cite as

Diogo Ferreira and Ibéria Medeiros. Discovering and Repairing Flaws in C Binaries Without Requiring Codebase and Instrumentation. In 30th Ada-Europe International Conference on Reliable Software Technologies (AEiC 2026). Open Access Series in Informatics (OASIcs), Volume 143, pp. 2:1-2:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{ferreira_et_al:OASIcs.AEiC.2026.2,
  author =	{Ferreira, Diogo and Medeiros, Ib\'{e}ria},
  title =	{{Discovering and Repairing Flaws in C Binaries Without Requiring Codebase and Instrumentation}},
  booktitle =	{30th Ada-Europe International Conference on Reliable Software Technologies (AEiC 2026)},
  pages =	{2:1--2:19},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-425-3},
  ISSN =	{2190-6807},
  year =	{2026},
  volume =	{143},
  editor =	{Filieri, Antonio and Backeman, Peter},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.AEiC.2026.2},
  URN =		{urn:nbn:de:0030-drops-259209},
  doi =		{10.4230/OASIcs.AEiC.2026.2},
  annote =	{Keywords: Buffer Overflow Vulnerabilities, Binary Patching, Reverse Engineering, Static Analysis, Software Security}
}
Document
DOI: 10.4230/LIPIcs.FORC.2026.13
Inducing Efficient and Equitable Professional Networks Through Link Recommendations

Authors: Cynthia Dwork, Chris Hays, Lunjia Hu, Nicole Immorlica, and Juan Perdomo

Published in: LIPIcs, Volume 368, 7th Symposium on Foundations of Responsible Computing (FORC 2026)

Abstract
Professional networks are a key determinant of individuals’ labor market outcomes. They may also play a role in either exacerbating or ameliorating inequality of opportunity across social groups. We initiate an investigation into the positive role that a professional networking platform can play when network members have different degrees of off-platform privilege. In a theoretical model, we show that the set of link recommendation policies that reduce costs between privileged and unprivileged individuals yield equilibria that are welfare-improving over all possible equilibria, compared to those obtained when not recommending links or recommending some smaller fraction of cross-group links. We next investigate the implications of platforms that do not intervene on the network formation process. We show that, absent intervention, inequality can increase relative to starting privilege levels even without exogenous in-group preferences, confirming and complementing existing theoretical literature. Increased inequality emerges from the differential leverage privileged and unprivileged individuals have in forming connections due to their asymmetric ex ante prospects. This is a formalization of a source of inequality in the labor market which has not been previously explored. These two findings reveal a stark reality: professional networking platforms that fail to foster integration in the link formation process risk reducing the platform’s utility to its users and exacerbating existing labor market inequality.
Cite as

Cynthia Dwork, Chris Hays, Lunjia Hu, Nicole Immorlica, and Juan Perdomo. Inducing Efficient and Equitable Professional Networks Through Link Recommendations. In 7th Symposium on Foundations of Responsible Computing (FORC 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 368, pp. 13:1-13:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{dwork_et_al:LIPIcs.FORC.2026.13,
  author =	{Dwork, Cynthia and Hays, Chris and Hu, Lunjia and Immorlica, Nicole and Perdomo, Juan},
  title =	{{Inducing Efficient and Equitable Professional Networks Through Link Recommendations}},
  booktitle =	{7th Symposium on Foundations of Responsible Computing (FORC 2026)},
  pages =	{13:1--13:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-419-2},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{368},
  editor =	{Lin, Huijia (Rachel)},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.FORC.2026.13},
  URN =		{urn:nbn:de:0030-drops-259863},
  doi =		{10.4230/LIPIcs.FORC.2026.13},
  annote =	{Keywords: Professional networks, Inequality, Link Recommendations}
}
Document
DOI: 10.4230/LIPIcs.FORC.2026.20
Privacy, Prediction, and Allocation

Authors: Ben Jacobsen and Nitin Kohli

Published in: LIPIcs, Volume 368, 7th Symposium on Foundations of Responsible Computing (FORC 2026)

Abstract
Algorithmic predictions are increasingly used to inform the allocation of scarce resources. The promise of these methods is that, through machine learning, they can better identify the people who would benefit most from interventions. Recently, however, several works have called this assumption into question by demonstrating the existence of settings where simple, unit-level allocation strategies can meet or even exceed the performance of those based on individual-level targeting. Separately, other works have objected to individual-level targeting on privacy grounds, leading to an unusual situation where a single solution, unit-level targeting, is recommended for reasons of both privacy and utility. Motivated by the desire to fully understand the interplay of privacy and targeting levels, we initiate the study of aid allocation systems that satisfy differential privacy, synthesizing existing works on private optimization with the economic models of aid allocation used in the non-private literature. To this end, we investigate private variants of both individual and unit-level allocation strategies in both stochastic and distribution-free settings under a range of constraints on data availability. Through this analysis, we provide clean, interpretable bounds characterizing the tradeoffs between privacy, efficiency, and targeting precision in allocation.
Cite as

Ben Jacobsen and Nitin Kohli. Privacy, Prediction, and Allocation. In 7th Symposium on Foundations of Responsible Computing (FORC 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 368, pp. 20:1-20:24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{jacobsen_et_al:LIPIcs.FORC.2026.20,
  author =	{Jacobsen, Ben and Kohli, Nitin},
  title =	{{Privacy, Prediction, and Allocation}},
  booktitle =	{7th Symposium on Foundations of Responsible Computing (FORC 2026)},
  pages =	{20:1--20:24},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-419-2},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{368},
  editor =	{Lin, Huijia (Rachel)},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.FORC.2026.20},
  URN =		{urn:nbn:de:0030-drops-259935},
  doi =		{10.4230/LIPIcs.FORC.2026.20},
  annote =	{Keywords: Differential privacy, fair allocation, limits of prediction}
}
Document
DOI: 10.4230/LIPIcs.SoCG.2026.78
Mapping Chemical Space: Topological Data Analysis of Chemical Latent Space with Mapper

Authors: Dhruv Meduri, Chuan-Shen Hu, Cong Shen, Kelin Xia, and Bei Wang

Published in: LIPIcs, Volume 367, 42nd International Symposium on Computational Geometry (SoCG 2026)

Abstract
The vast chemical space, encompassing virtually innumerable molecules and materials, presents both immense opportunities and significant challenges. The design and discovery of novel drugs and functional materials may be viewed as a search within this space; however, the sheer scale of potential candidates renders exhaustive exploration infeasible. To address this, we introduce Chemical Mapper, a framework that integrates topological data analysis with deep learning to enable the visual exploration and analysis of chemical latent spaces. At its core, Chemical Mapper employs mapper, a widely used tool in topological data analysis, to investigate the organizational principles of chemical latent spaces defined by molecular representations learned by geometric deep learning models. In doing so, Chemical Mapper not only highlights groups of molecular representations but also uncovers the relationships among them through linkages and branching structures. Our results show that Chemical Mapper reveals intrinsic patterns associated with molecular scaffolds, functional groups, and chemical properties, as well as the structural and functional evolutions of the molecules.
Cite as

Dhruv Meduri, Chuan-Shen Hu, Cong Shen, Kelin Xia, and Bei Wang. Mapping Chemical Space: Topological Data Analysis of Chemical Latent Space with Mapper. In 42nd International Symposium on Computational Geometry (SoCG 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 367, pp. 78:1-78:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{meduri_et_al:LIPIcs.SoCG.2026.78,
  author =	{Meduri, Dhruv and Hu, Chuan-Shen and Shen, Cong and Xia, Kelin and Wang, Bei},
  title =	{{Mapping Chemical Space: Topological Data Analysis of Chemical Latent Space with Mapper}},
  booktitle =	{42nd International Symposium on Computational Geometry (SoCG 2026)},
  pages =	{78:1--78:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-418-5},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{367},
  editor =	{Ahn, Hee-Kap and Hoffmann, Michael and Nayyeri, Amir},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SoCG.2026.78},
  URN =		{urn:nbn:de:0030-drops-258854},
  doi =		{10.4230/LIPIcs.SoCG.2026.78},
  annote =	{Keywords: Practice of computational topology, topological data analysis, applications in chemistry, mapper algorithm, high-dimensional data analysis, chemical spaces, geometric deep learning, latent space geometry}
}
Document
DOI: 10.4230/LIPIcs.SoCG.2026.89
Approximating Convex Hulls via Range Queries

Authors: Thomas Schibler, Jie Xue, and Jiumu Zhu

Published in: LIPIcs, Volume 367, 42nd International Symposium on Computational Geometry (SoCG 2026)

Abstract
Recently, motivated by the rapid increase of the data size in various applications, Monemizadeh [APPROX'23] and Driemel, Monemizadeh, Oh, Staals, and Woodruff [SoCG'25] studied geometric problems in the setting where the only access to the input point set is via querying a range-search oracle. Algorithms in this setting are evaluated on two criteria: (i) the number of queries to the oracle and (ii) the error of the output. In this paper, we continue this line of research and investigate one of the most fundamental geometric problems in the oracle setting, i.e., the convex hull problem. Let P be an unknown set of points in [0,1]^d equipped with a range-emptiness oracle. Via querying the oracle, the algorithm is supposed to output a convex polygon C ⊆ [0,1]^d as an estimation of the convex hull CH(P) of P. The error of the output is defined as the volume of the symmetric difference C ⊕ CH(P) = (C∖CH(P)) ∪ (CH(P)∖C). We prove tight and near-tight tradeoffs between the number of queries and the error of the output for different variants of the problem, depending on the type of the range-emptiness queries and whether the queries are non-adaptive or adaptive. - Orthogonal emptiness queries in d-dimensional space: We show that the minimum error a deterministic algorithm can achieve with q queries is Θ(q^{-1/d}) if the queries are non-adaptive, and Θ(q^{-1/(d-1)}) if the queries are adaptive. In particular, in 2D, the bounds are Θ(1/√q) and Θ(1/q) for non-adaptive and adaptive queries, respectively. - Halfplane emptiness queries in 2D: We show that the minimum error a deterministic algorithm can achieve with q queries is Θ(1/√q) if the queries are non-adaptive, and Θ̃(1/q²) if the queries are adaptive. Here Θ̃(⋅) hides logarithmic factors.
Cite as

Thomas Schibler, Jie Xue, and Jiumu Zhu. Approximating Convex Hulls via Range Queries. In 42nd International Symposium on Computational Geometry (SoCG 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 367, pp. 89:1-89:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{schibler_et_al:LIPIcs.SoCG.2026.89,
  author =	{Schibler, Thomas and Xue, Jie and Zhu, Jiumu},
  title =	{{Approximating Convex Hulls via Range Queries}},
  booktitle =	{42nd International Symposium on Computational Geometry (SoCG 2026)},
  pages =	{89:1--89:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-418-5},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{367},
  editor =	{Ahn, Hee-Kap and Hoffmann, Michael and Nayyeri, Amir},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SoCG.2026.89},
  URN =		{urn:nbn:de:0030-drops-258956},
  doi =		{10.4230/LIPIcs.SoCG.2026.89},
  annote =	{Keywords: convex hull, range searching}
}
Document
DOI: 10.4230/LIPIcs.SoCG.2026.94
Mixup Barcodes: Quantifying Geometric-Topological Interactions Between Point Clouds

Authors: Hubert Wagner, Nickolas Arustamyan, Matthew Wheeler, and Peter Bubenik

Published in: LIPIcs, Volume 367, 42nd International Symposium on Computational Geometry (SoCG 2026)

Abstract
We propose a novel geometric-topological descriptor called a mixup barcode. Intuitively, it characterizes the shape of a point cloud as well as its spatial relationship with another point cloud embedded in the same ambient space. More technically, it enriches a standard persistence barcode with information on the image persistent homology. In three dimensions it captures natural spatial relationships like overlap and surrounding; in higher dimensions more intricate spatial relationships are captured. We provide a theoretical setup and a simple algorithm for mixup barcodes. As a proof of concept, we explore data arising in a geometric-topological problem from machine learning. Specifically, we take first steps towards verifying a hypothesis stating that geometric-topological relationships within intermediate point cloud representations in an artificial neural network can hinder its training. More broadly, our experiments suggest that mixup barcodes are useful for characterizing spatial relationships and spatial interactions (i.e. the evolution of spatial relationships) that are hard to directly visualize or capture using standard methods.
Cite as

Hubert Wagner, Nickolas Arustamyan, Matthew Wheeler, and Peter Bubenik. Mixup Barcodes: Quantifying Geometric-Topological Interactions Between Point Clouds. In 42nd International Symposium on Computational Geometry (SoCG 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 367, pp. 94:1-94:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{wagner_et_al:LIPIcs.SoCG.2026.94,
  author =	{Wagner, Hubert and Arustamyan, Nickolas and Wheeler, Matthew and Bubenik, Peter},
  title =	{{Mixup Barcodes: Quantifying Geometric-Topological Interactions Between Point Clouds}},
  booktitle =	{42nd International Symposium on Computational Geometry (SoCG 2026)},
  pages =	{94:1--94:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-418-5},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{367},
  editor =	{Ahn, Hee-Kap and Hoffmann, Michael and Nayyeri, Amir},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SoCG.2026.94},
  URN =		{urn:nbn:de:0030-drops-259009},
  doi =		{10.4230/LIPIcs.SoCG.2026.94},
  annote =	{Keywords: mixup barcode, persistent homology, persistence barcode, persistence diagram, image persistent homology, image persistence, deep learning, multilayer perceptron, topology of neural network embeddings, disentanglement}
}
Document
DOI: 10.4230/OASIcs.PARMA-DITAM.2026.3
High Performance Visualization with VisIVO Across Cloud and HPC

Authors: Umer Arshad, Eva Sciacca, Nicola Tuccari, Fabio Pitari, and Giuseppa Muscianisi

Published in: OASIcs, Volume 141, 17th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 15th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2026)

Abstract
The rapid growth of data in Astrophysics and Cosmology creates significant challenges that require scalable computing and advanced visualization solutions. Cineca is Italy’s largest supercomputing center and a leading global provider of high-performance computing (HPC) services. This paper shows that the integration of the VisIVO scientific visualization framework is with the cloud-based InterActive Computing (IAC) service at Cineca. This integration enables GPU-accelerated, real-time visualization on HPC resources via a Jupyter interface in their browser. A new dedicated Python wrapper and a custom Jupyter kernel enable VisIVO to run smoothly from interactive notebooks, avoid command-line operations, and visualize data directly on HPC compute nodes. Furthermore, we enabled cloud-oriented RESTful APIs, built with the Flask framework, to perform VisIVO operations remotely via simple web services. This setup hides the backend’s complexity and simplifies connections with other applications. Our framework increases system accessibility, ensures reproducibility of results, and supports rapid data exploration for large astrophysical simulations. The system was evaluated using real-world cases, including visual analysis of cosmological simulations generated using the OpenGadget3 code. Results indicate that the system is scalable and reliable, and that it facilitates interactive scientific discovery on high-performance computing (HPC) infrastructures.
Cite as

Umer Arshad, Eva Sciacca, Nicola Tuccari, Fabio Pitari, and Giuseppa Muscianisi. High Performance Visualization with VisIVO Across Cloud and HPC. In 17th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 15th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2026). Open Access Series in Informatics (OASIcs), Volume 141, pp. 3:1-3:11, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{arshad_et_al:OASIcs.PARMA-DITAM.2026.3,
  author =	{Arshad, Umer and Sciacca, Eva and Tuccari, Nicola and Pitari, Fabio and Muscianisi, Giuseppa},
  title =	{{High Performance Visualization with VisIVO Across Cloud and HPC}},
  booktitle =	{17th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 15th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2026)},
  pages =	{3:1--3:11},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-416-1},
  ISSN =	{2190-6807},
  year =	{2026},
  volume =	{141},
  editor =	{Baroffio, Davide and Busia, Paola and Denisov, Lev and Shukla, Nitin},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.PARMA-DITAM.2026.3},
  URN =		{urn:nbn:de:0030-drops-256700},
  doi =		{10.4230/OASIcs.PARMA-DITAM.2026.3},
  annote =	{Keywords: High-performance computing, HPC, VisIVO, Scientific visualization, Interactive visualization, Cloud computing, Jupyter, Flask, REST API}
}
Document
Survey
DOI: 10.4230/TGDK.4.1.2
Temporal Modelling in Cultural Heritage Knowledge Graphs: Use Cases, Requirements, Evaluation, and Decision Support

Authors: Oleksandra Bruns, Jörg Waitelonis, Jeff Z. Pan, and Harald Sack

Published in: TGDK, Volume 4, Issue 1 (2026). Transactions on Graph Data and Knowledge, Volume 4, Issue 1

Abstract
Our culture, history and world are in constant motion, continuously shaped by the flow of time, evolving narratives, and shifting relationships. Capturing this temporal complexity within cultural heritage (CH) knowledge graphs is essential for preserving the dynamic nature of human heritage. However, standard RDF predicates fail to effectively model the temporal aspects of cultural data, such as changing facts, evolving relationships, and temporal concepts. Over the past two decades, a variety of RDF-based approaches have been proposed to address this limitation, yet guidance is missing on which method best suits specific CH contexts. This paper presents a systematic evaluation of temporal RDF modelling approaches from a CH perspective. Based on an analysis of real-world CH use cases, core temporal requirements are identified that reflect both modelling expressivity and practical concerns. Six prominent approaches - RDF*, tRDF, Named Graphs, Singleton Property, N-ary Relations, and 4D Fluents - are assessed across these requirements. Our findings reveal that no single solution fits all scenarios, but suitable approaches can be selected based on project-specific priorities. To support practitioners, a decision-support tool is introduced to guide them in selecting the most suitable extension for their specific needs. This work provides practical guidance for CH modelling and contributes to the broader development of temporally aware Linked Data.
Cite as

Oleksandra Bruns, Jörg Waitelonis, Jeff Z. Pan, and Harald Sack. Temporal Modelling in Cultural Heritage Knowledge Graphs: Use Cases, Requirements, Evaluation, and Decision Support. In Transactions on Graph Data and Knowledge (TGDK), Volume 4, Issue 1, pp. 2:1-2:46, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@Article{bruns_et_al:TGDK.4.1.2,
  author =	{Bruns, Oleksandra and Waitelonis, J\"{o}rg and Pan, Jeff Z. and Sack, Harald},
  title =	{{Temporal Modelling in Cultural Heritage Knowledge Graphs: Use Cases, Requirements, Evaluation, and Decision Support}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{2:1--2:46},
  ISSN =	{2942-7517},
  year =	{2026},
  volume =	{4},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.4.1.2},
  URN =		{urn:nbn:de:0030-drops-256871},
  doi =		{10.4230/TGDK.4.1.2},
  annote =	{Keywords: Temporal Data Representation, RDF Extensions, Cultural Heritage, Knowledge Graphs}
}
Document
DOI: 10.4230/OASIcs.NINeS.2026.8
Contracts: A Unified Lens on Congestion Control Robustness, Fairness, Congestion, and Generality

Authors: Anup Agarwal, Venkat Arun, and Srinivasan Seshan

Published in: OASIcs, Volume 139, 1st New Ideas in Networked Systems (NINeS 2026)

Abstract
Congestion control algorithms (CCAs) operate in partially observable environments. They cannot directly observe link capacities or competing flows. To share network resources fairly, CCAs (implicitly) communicate fair shares through observable signals. For instance, Reno encodes the fair share as ∝ 1/√{loss rate}. We call such communication mechanisms as contracts. We find that the choice of contract fixes key steady-state performance metrics, including (1) robustness to errors in congestion signals, (2) fairness, (3) amount of congestion (e.g., delay, loss), and (4) generality (e.g., range of supported link rates). This leads to fundamental tradeoffs between these metrics. Further, we show that many contracts lead to starvation (extreme unfairness), and must be avoided. Hence, contracts are a powerful way to analyze tradeoffs and avoid pitfalls in CCA design and analysis. We empirically validate our findings and discuss their implications on CCA design and network measurement.
Cite as

Anup Agarwal, Venkat Arun, and Srinivasan Seshan. Contracts: A Unified Lens on Congestion Control Robustness, Fairness, Congestion, and Generality. In 1st New Ideas in Networked Systems (NINeS 2026). Open Access Series in Informatics (OASIcs), Volume 139, pp. 8:1-8:30, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{agarwal_et_al:OASIcs.NINeS.2026.8,
  author =	{Agarwal, Anup and Arun, Venkat and Seshan, Srinivasan},
  title =	{{Contracts: A Unified Lens on Congestion Control Robustness, Fairness, Congestion, and Generality}},
  booktitle =	{1st New Ideas in Networked Systems (NINeS 2026)},
  pages =	{8:1--8:30},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-414-7},
  ISSN =	{2190-6807},
  year =	{2026},
  volume =	{139},
  editor =	{Argyraki, Katerina and Panda, Aurojit},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.NINeS.2026.8},
  URN =		{urn:nbn:de:0030-drops-255933},
  doi =		{10.4230/OASIcs.NINeS.2026.8},
  annote =	{Keywords: Transport Protocols, Congestion Control, Fairness}
}
Document
DOI: 10.4230/OASIcs.NINeS.2026.24
SwiftQueue: Optimizing Low-Latency Applications with Swift Packet Queuing

Authors: Siddhant Ray, Xi Jiang, Jack Luo, Nick Feamster, and Junchen Jiang

Published in: OASIcs, Volume 139, 1st New Ideas in Networked Systems (NINeS 2026)

Abstract
Low Latency, Low Loss, and Scalable Throughput (L4S), as an emerging router-queue management technique, has seen steady deployment in the industry. An L4S-enabled router assigns each packet to the queue based on the packet header marking. Currently, L4S employs per-flow queue selection, i.e., all packets of a flow are marked the same way and thus use the same queues, even though each packet is marked separately. However, this may hurt tail latency and latency-sensitive applications because transient congestion and queue buildups may only affect a fraction of packets in a flow. We present SwiftQueue, a new L4S queue-selection strategy in which a sender uses a novel per-packet latency predictor to pinpoint which packets likely have latency spikes or drops. The insight is that many packet-level latency variations result from complex interactions among recent packets at shared router queues. Yet, these intricate packet-level latency patterns are hard to learn efficiently by traditional models. Instead, SwiftQueue uses a custom Transformer, which is well-studied for its expressiveness on sequential patterns, to predict the next packet’s latency based on the latencies of recently received ACKs. Based on the predicted latency of each outgoing packet, SwiftQueue’s sender dynamically marks the L4S packet header to assign packets to potentially different queues, even within the same flow. Using real network traces, we show that SwiftQueue is 45-65% more accurate in predicting latency and its variations than state-of-art methods. Based on its latency prediction, SwiftQueue reduces the tail latency for L4S-enabled flows by 36-45%, compared with the existing L4S queue-selection method.
Cite as

Siddhant Ray, Xi Jiang, Jack Luo, Nick Feamster, and Junchen Jiang. SwiftQueue: Optimizing Low-Latency Applications with Swift Packet Queuing. In 1st New Ideas in Networked Systems (NINeS 2026). Open Access Series in Informatics (OASIcs), Volume 139, pp. 24:1-24:29, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{ray_et_al:OASIcs.NINeS.2026.24,
  author =	{Ray, Siddhant and Jiang, Xi and Luo, Jack and Feamster, Nick and Jiang, Junchen},
  title =	{{SwiftQueue: Optimizing Low-Latency Applications with Swift Packet Queuing}},
  booktitle =	{1st New Ideas in Networked Systems (NINeS 2026)},
  pages =	{24:1--24:29},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-414-7},
  ISSN =	{2190-6807},
  year =	{2026},
  volume =	{139},
  editor =	{Argyraki, Katerina and Panda, Aurojit},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.NINeS.2026.24},
  URN =		{urn:nbn:de:0030-drops-256093},
  doi =		{10.4230/OASIcs.NINeS.2026.24},
  annote =	{Keywords: Latency prediction, L4S Queue Management}
}
Document
DOI: 10.4230/OASIcs.NINeS.2026.5
OrbitalBrain: A Distributed Framework for Training ML Models in Space

Authors: Om Chabra, Chenning Li, Kevin Hsieh, Santiago Segarra, Behnaz Arzani, Peder Olsen, and Ranveer Chandra

Published in: OASIcs, Volume 139, 1st New Ideas in Networked Systems (NINeS 2026)

Abstract
Earth observation nanosatellites capture high-resolution photos of the Earth in near real-time. These images increasingly support ML applications that are critical for safety and response, such as forest fire and flood detection. However, the downlink bandwidth is limited, resulting in days or weeks of delay from image capture to training. In this work, we propose OrbitalBrain, an efficient in-space distributed ML training framework that leverages limited and predictable satellite compute, bandwidth, and power to intelligently balance data transfer, model aggregation, and local training. Our evaluations demonstrate that OrbitalBrain achieves 1.52×-12.4× speedup in time-to-accuracy while always reaching a higher final model accuracy compared to state-of-the-art ground-based or federated learning baselines. Furthermore, our approach is complementary to satellite imagery capturing and downloading, enhancing the overall efficiency of satellite-based applications.
Cite as

Om Chabra, Chenning Li, Kevin Hsieh, Santiago Segarra, Behnaz Arzani, Peder Olsen, and Ranveer Chandra. OrbitalBrain: A Distributed Framework for Training ML Models in Space. In 1st New Ideas in Networked Systems (NINeS 2026). Open Access Series in Informatics (OASIcs), Volume 139, pp. 5:1-5:32, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{chabra_et_al:OASIcs.NINeS.2026.5,
  author =	{Chabra, Om and Li, Chenning and Hsieh, Kevin and Segarra, Santiago and Arzani, Behnaz and Olsen, Peder and Chandra, Ranveer},
  title =	{{OrbitalBrain: A Distributed Framework for Training ML Models in Space}},
  booktitle =	{1st New Ideas in Networked Systems (NINeS 2026)},
  pages =	{5:1--5:32},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-414-7},
  ISSN =	{2190-6807},
  year =	{2026},
  volume =	{139},
  editor =	{Argyraki, Katerina and Panda, Aurojit},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.NINeS.2026.5},
  URN =		{urn:nbn:de:0030-drops-255907},
  doi =		{10.4230/OASIcs.NINeS.2026.5},
  annote =	{Keywords: Satellite networks, Distributed machine learning, Federated learning, Earth observation, In-orbit computing}
}
Document
DOI: 10.4230/LIPIcs.ITCS.2026.57
Anti-Concentration for the Unitary Haar Measure and Applications to Random Quantum Circuits

Authors: Bill Fefferman, Soumik Ghosh, and Wei Zhan

Published in: LIPIcs, Volume 362, 17th Innovations in Theoretical Computer Science Conference (ITCS 2026)

Abstract
We prove a Carbery-Wright style anti-concentration inequality for the unitary Haar measure, by showing that the probability of a polynomial in the entries of a random unitary falling into an ε range is at most a polynomial in ε. Using it, we show that the scrambling speed of a random quantum circuit is lower bounded: Namely, every input qubit has an influence that is at least inverse exponential in depth, on any output qubit touched by its lightcone. Our result on scrambling speed works with high probability over the choice of a circuit from an ensemble, as opposed to just working in expectation. As an application, we give the first polynomial-time algorithm for learning log-depth random quantum circuits with Haar random gates up to polynomially small diamond distance, given oracle access to the circuit. Other applications of this new scrambling speed lower bound include: - An optimal Ω(log ε^{-1}) depth lower bound for ε-approximate unitary designs on any circuit architecture; - A polynomial-time quantum algorithm that computes the depth of a bounded-depth circuit, given oracle access to the circuit. Our learning and depth-testing algorithms apply to architectures defined over any geometric dimension, and can be generalized to a wide class of architectures with good lightcone properties.
Cite as

Bill Fefferman, Soumik Ghosh, and Wei Zhan. Anti-Concentration for the Unitary Haar Measure and Applications to Random Quantum Circuits. In 17th Innovations in Theoretical Computer Science Conference (ITCS 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 362, pp. 57:1-57:24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{fefferman_et_al:LIPIcs.ITCS.2026.57,
  author =	{Fefferman, Bill and Ghosh, Soumik and Zhan, Wei},
  title =	{{Anti-Concentration for the Unitary Haar Measure and Applications to Random Quantum Circuits}},
  booktitle =	{17th Innovations in Theoretical Computer Science Conference (ITCS 2026)},
  pages =	{57:1--57:24},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-410-9},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{362},
  editor =	{Saraf, Shubhangi},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITCS.2026.57},
  URN =		{urn:nbn:de:0030-drops-253443},
  doi =		{10.4230/LIPIcs.ITCS.2026.57},
  annote =	{Keywords: Haar measure, anti-concentration, random quanytum circuit, learning}
}
Document
DOI: 10.4230/LIPIcs.ITCS.2026.24
Unitary Complexity and the Uhlmann Transformation Problem

Authors: John Bostanci, Yuval Efron, Tony Metger, Alexander Poremba, Luowen Qian, and Henry Yuen

Published in: LIPIcs, Volume 362, 17th Innovations in Theoretical Computer Science Conference (ITCS 2026)

Abstract
State transformation problems such as compressing quantum information or breaking quantum commitments are fundamental quantum tasks. However, their computational difficulty cannot easily be characterized using traditional complexity theory, which focuses on tasks with classical inputs and outputs. To study the complexity of such state transformation tasks, we introduce a framework for unitary synthesis problems, including notions of reductions and unitary complexity classes. We use this framework to study the complexity of transforming one entangled state into another via local operations. We formalize this as the Uhlmann Transformation Problem, an algorithmic version of Uhlmann’s theorem. Then, we prove structural results relating the complexity of the Uhlmann Transformation Problem, polynomial space quantum computation, and zero knowledge protocols. The Uhlmann Transformation Problem allows us to characterize the complexity of a variety of tasks in quantum information processing, including decoding noisy quantum channels, breaking falsifiable quantum cryptographic assumptions, implementing optimal prover strategies in quantum interactive proofs, and decoding the Hawking radiation of black holes. Our framework for unitary complexity thus provides new avenues for studying the computational complexity of many natural quantum information processing tasks.
Cite as

John Bostanci, Yuval Efron, Tony Metger, Alexander Poremba, Luowen Qian, and Henry Yuen. Unitary Complexity and the Uhlmann Transformation Problem. In 17th Innovations in Theoretical Computer Science Conference (ITCS 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 362, pp. 24:1-24:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{bostanci_et_al:LIPIcs.ITCS.2026.24,
  author =	{Bostanci, John and Efron, Yuval and Metger, Tony and Poremba, Alexander and Qian, Luowen and Yuen, Henry},
  title =	{{Unitary Complexity and the Uhlmann Transformation Problem}},
  booktitle =	{17th Innovations in Theoretical Computer Science Conference (ITCS 2026)},
  pages =	{24:1--24:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-410-9},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{362},
  editor =	{Saraf, Shubhangi},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITCS.2026.24},
  URN =		{urn:nbn:de:0030-drops-253111},
  doi =		{10.4230/LIPIcs.ITCS.2026.24},
  annote =	{Keywords: Uhlmann’s theorem, unitary complexity theory}
}
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