Something has to give: scaling combinatorial computing by biological agents exploring physical networks encoding NP-complete problems Article Swipe
F.C.M.J.M. van Delft
,
Giulia Ipolitti
,
Dan V. Nicolau
,
Ayyappasamy Sudalaiyadum Perumal
,
Ondřej Kašpar
,
Sara Kheireddine
,
Sebastian Wachsmann‐Hogiu
,
Dan V. Nicolau
·
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.1098/rsfs.2018.0034
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.1098/rsfs.2018.0034
On-chip network-based computation, using biological agents, is a new hardware-embedded approach which attempts to find solutions to combinatorial problems, in principle, in a shorter time than the fast, but sequential electronic computers. This analytical review starts by describing the underlying mathematical principles, presents several types of combinatorial (including NP-complete) problems and shows current implementations of proof of principle developments. Taking the subset sum problem as example for in-depth analysis, the review presents various options of computing agents, and compares several possible operation ‘run modes’ of network-based computer systems. Given the brute force approach of network-based systems for solving a problem of input size C, 2 C solutions must be visited. As this exponentially increasing workload needs to be distributed in space, time, and per computing agent, this review identifies the scaling-related key technological challenges in terms of chip fabrication, readout reliability and energy efficiency. The estimated computing time of massively parallel or combinatorially operating biological agents is then compared to that of electronic computers. Among future developments which could considerably improve network-based computing, labelling agents ‘on the fly’ and the readout of their travel history at network exits could offer promising avenues for finding hardware-embedded solutions to combinatorial problems.
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Metadata
- Type
- review
- Language
- en
- Landing Page
- https://doi.org/10.1098/rsfs.2018.0034
- https://royalsocietypublishing.org/doi/pdf/10.1098/rsfs.2018.0034
- OA Status
- hybrid
- Cited By
- 23
- References
- 79
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2898030281
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2898030281Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1098/rsfs.2018.0034Digital Object Identifier
- Title
-
Something has to give: scaling combinatorial computing by biological agents exploring physical networks encoding NP-complete problemsWork title
- Type
-
reviewOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2018Year of publication
- Publication date
-
2018-10-19Full publication date if available
- Authors
-
F.C.M.J.M. van Delft, Giulia Ipolitti, Dan V. Nicolau, Ayyappasamy Sudalaiyadum Perumal, Ondřej Kašpar, Sara Kheireddine, Sebastian Wachsmann‐Hogiu, Dan V. NicolauList of authors in order
- Landing page
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https://doi.org/10.1098/rsfs.2018.0034Publisher landing page
- PDF URL
-
https://royalsocietypublishing.org/doi/pdf/10.1098/rsfs.2018.0034Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
- OA URL
-
https://royalsocietypublishing.org/doi/pdf/10.1098/rsfs.2018.0034Direct OA link when available
- Concepts
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Computer science, Massively parallel, Workload, Computation, Implementation, Key (lock), Distributed computing, Encoding (memory), Theoretical computer science, Parallel computing, Artificial intelligence, Algorithm, Computer security, Programming language, Operating systemTop concepts (fields/topics) attached by OpenAlex
- Cited by
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23Total citation count in OpenAlex
- Citations by year (recent)
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2025: 2, 2024: 3, 2023: 4, 2022: 2, 2021: 8Per-year citation counts (last 5 years)
- References (count)
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79Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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