Paper Citation Record · LEDGER

Computational acceleration strategies for large-scale energy system optimization: a comparative study of GPU-accelerated and distributed-memory solvers

As of 10 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 0 inbound Pith citation observations for arXiv:2605.04605.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2605.04605 v2

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T14:51:05.939664Z

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

25 of 25 outbound references displayed

verified exact0
verified fuzzy0
unresolved24
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f75d3f11-7571-4e86-bdb1-1fb211f0b599 · outbound

This paper cites Formalizing best practice for ene rgy system optimization modelling.

Computational acceleration strategies for large-scale energy system optimization: a comparative study of GPU-accelerated and distributed-memory solvers Formalizing best practice for ene rgy system optimization modelling

Reference 1

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Source-reported events for the cited work

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Observation 08f08655-b7ba-49f8-b867-1689477b50b7 · outbound

This paper cites A review of approaches to uncertainty asses sment in energy system optimiza- tion models.

Computational acceleration strategies for large-scale energy system optimization: a comparative study of GPU-accelerated and distributed-memory solvers A review of approaches to uncertainty asses sment in energy system optimiza- tion models

Reference 2

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Observation d7325a34-0a48-4af0-bdba-044c837efa18 · outbound

This paper cites Chances and barriers for Germany’s low carbon transition – Quantifying uncertainties in key inﬂuential factors.

Computational acceleration strategies for large-scale energy system optimization: a comparative study of GPU-accelerated and distributed-memory solvers Chances and barriers for Germany’s low carbon transition – Quantifying uncertainties in key inﬂuential factors

Reference 3

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Observation f3a77786-16d1-4918-87ec-1de60efb3e40 · outbound

This paper cites Demand uncertainty in energy systems: scenario catalogs vs. integrated robust optimization.

Computational acceleration strategies for large-scale energy system optimization: a comparative study of GPU-accelerated and distributed-memory solvers Demand uncertainty in energy systems: scenario catalogs vs. integrated robust optimization

Reference 4

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Observation e29c2e4d-9a64-483e-b21d-6aed8545bf45 · outbound

This paper cites Sensitivity analysis of the energy tr ansition path in the Berlin-Brandenburg area to uncertainties in operational and investment costs o f diverse energy production tech- nologies.

Computational acceleration strategies for large-scale energy system optimization: a comparative study of GPU-accelerated and distributed-memory solvers Sensitivity analysis of the energy tr ansition path in the Berlin-Brandenburg area to uncertainties in operational and investment costs o f diverse energy production tech- nologies

Reference 5

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Observation 1387ce85-7002-4c7f-9a51-073834acb54c · outbound

This paper cites Progress in mathematical programming sol vers from 2001 to 2020.

Computational acceleration strategies for large-scale energy system optimization: a comparative study of GPU-accelerated and distributed-memory solvers Progress in mathematical programming sol vers from 2001 to 2020

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-02T14:51:05.864224Z

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Observation 9400c543-9485-451a-9a77-87f5efe65a36 · outbound

This paper cites Classiﬁcation and Evaluation of Concep ts for Improving the Performance of Applied Energy System Optimization Models.

Computational acceleration strategies for large-scale energy system optimization: a comparative study of GPU-accelerated and distributed-memory solvers Classiﬁcation and Evaluation of Concep ts for Improving the Performance of Applied Energy System Optimization Models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-02T14:51:05.869511Z

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Observation 3886d7b0-331e-490d-b59a-cc99b40f37af · outbound

This paper cites A modeler’s guide to handle complexity i n energy systems optimization.

Computational acceleration strategies for large-scale energy system optimization: a comparative study of GPU-accelerated and distributed-memory solvers A modeler’s guide to handle complexity i n energy systems optimization

Reference 8

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Observation 8025cedb-71eb-4af5-903c-3da90c19a8f0 · outbound

This paper cites Impact of different time series aggrega tion methods on optimal energy sys- tem design.

Computational acceleration strategies for large-scale energy system optimization: a comparative study of GPU-accelerated and distributed-memory solvers Impact of different time series aggrega tion methods on optimal energy sys- tem design

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-02T14:51:05.877351Z

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Observation 2c524c50-eba5-4e28-96d0-1e9dbe53881e · outbound

This paper cites A massively parallel interior-poin t solver for LPs with generalized ar- rowhead structure, and applications to energy system model s.

Computational acceleration strategies for large-scale energy system optimization: a comparative study of GPU-accelerated and distributed-memory solvers A massively parallel interior-poin t solver for LPs with generalized ar- rowhead structure, and applications to energy system model s

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-02T14:51:05.881924Z

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Observation 647921f6-2565-4054-a8b6-a8d1fdd03240 · outbound

This paper cites A Massively Parallel Interior-Point Method for Arrowhead Linear Programs with Local Linking Structure.

Computational acceleration strategies for large-scale energy system optimization: a comparative study of GPU-accelerated and distributed-memory solvers A Massively Parallel Interior-Point Method for Arrowhead Linear Programs with Local Linking Structure

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-02T14:51:05.885564Z

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Observation 5b1c6ba5-79a8-4dd1-ad2e-d957e3275909 · outbound

This paper cites Wetzel, K.-K.

Computational acceleration strategies for large-scale energy system optimization: a comparative study of GPU-accelerated and distributed-memory solvers Wetzel, K.-K

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-02T14:51:05.889734Z

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Observation fbbc4a71-3b51-4c8e-8991-259e841127a0 · outbound

This paper cites High-Performance Robust Energy System P lanning with Storage: A Single- LP Approach.

Computational acceleration strategies for large-scale energy system optimization: a comparative study of GPU-accelerated and distributed-memory solvers High-Performance Robust Energy System P lanning with Storage: A Single- LP Approach

Reference 13

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Observation dd6eb38e-0a6d-41f6-be82-b1badfb11c56 · outbound

This paper cites PDLP: A Practical First-Order Meth od for Large-Scale Linear Pro- gramming.

Computational acceleration strategies for large-scale energy system optimization: a comparative study of GPU-accelerated and distributed-memory solvers PDLP: A Practical First-Order Meth od for Large-Scale Linear Pro- gramming

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-02T14:51:05.897426Z

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Observation 688e29f0-fb26-4947-ae7f-d2fbae932618 · outbound

This paper cites HPR-LP: An implementation of an HPR metho d for solving linear program- ming.

Computational acceleration strategies for large-scale energy system optimization: a comparative study of GPU-accelerated and distributed-memory solvers HPR-LP: An implementation of an HPR metho d for solving linear program- ming

Reference 15

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Observation 4844ee0a-c9c0-46be-bc61-5e679d04eafe · outbound

This paper cites Solving Large Multicommodity Network Flow Problems on GPUs.

Computational acceleration strategies for large-scale energy system optimization: a comparative study of GPU-accelerated and distributed-memory solvers Solving Large Multicommodity Network Flow Problems on GPUs

Reference 16

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Observation 465fe754-84f1-4152-8b91-fc355abef0e5 · outbound

This paper cites Low-precision ﬁrst-order me thod-based ﬁx-and-propagate heuristics for large-scale mixed-integer linear optimization.

Computational acceleration strategies for large-scale energy system optimization: a comparative study of GPU-accelerated and distributed-memory solvers Low-precision ﬁrst-order me thod-based ﬁx-and-propagate heuristics for large-scale mixed-integer linear optimization

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-02T14:51:05.909519Z

Source-reported events for the cited work

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Observation f5e9c01a-0896-4bc9-98d3-969192023b95 · outbound

This paper cites Parallelizing the dual revised s implex method.

Computational acceleration strategies for large-scale energy system optimization: a comparative study of GPU-accelerated and distributed-memory solvers Parallelizing the dual revised s implex method

Reference 18

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Observation 807995ec-0579-4319-9b69-a989570aa8fb · outbound

This paper cites Available at https://github.com/NVIDIA/cuopt, [accessed 26.03.2026].

Computational acceleration strategies for large-scale energy system optimization: a comparative study of GPU-accelerated and distributed-memory solvers Available at https://github.com/NVIDIA/cuopt, [accessed 26.03.2026]

Reference 19

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Observation ee476d3a-1dc4-4a1e-904e-2ab0b45948bb · outbound

This paper cites The Ubiquity Generator Framework: 7 Y ears of Progress in Parallelizing Branch- and-Bound.

Computational acceleration strategies for large-scale energy system optimization: a comparative study of GPU-accelerated and distributed-memory solvers The Ubiquity Generator Framework: 7 Y ears of Progress in Parallelizing Branch- and-Bound

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-02T14:51:05.921156Z

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Observation a00fe85c-9793-4131-8cfe-87c0f6006136 · outbound

This paper cites Zittel et al.

Computational acceleration strategies for large-scale energy system optimization: a comparative study of GPU-accelerated and distributed-memory solvers Zittel et al

Reference 21

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Observation 78bbf564-cbf1-483f-b796-b1d5b812dbd2 · outbound

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Computational acceleration strategies for large-scale energy system optimization: a comparative study of GPU-accelerated and distributed-memory solvers Unresolved cited work

Reference 22

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Observation ff65bf14-5505-4ee2-94d1-32b44619e8f3 · outbound

This paper cites Scalable high-quality hypergr aph partitioning.

Computational acceleration strategies for large-scale energy system optimization: a comparative study of GPU-accelerated and distributed-memory solvers Scalable high-quality hypergr aph partitioning

Reference 23

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Observation 40c27db9-e1fd-47c1-8a68-69a4ed316e64 · outbound

This paper cites Solving unsymmetric sparse systems of linear equations with PARDISO.

Computational acceleration strategies for large-scale energy system optimization: a comparative study of GPU-accelerated and distributed-memory solvers Solving unsymmetric sparse systems of linear equations with PARDISO

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-02T14:51:05.935810Z

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Observation 79131e79-39bf-41e8-8b0d-cd63131ca2ad · outbound

This paper cites MA57—a code for the solution of sparse symme tric deﬁnite and indeﬁnite sys- tems.

Computational acceleration strategies for large-scale energy system optimization: a comparative study of GPU-accelerated and distributed-memory solvers MA57—a code for the solution of sparse symme tric deﬁnite and indeﬁnite sys- tems

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-02T14:51:05.939664Z

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Pith citing papers

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