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Miquel Guiot

dblp:373/1506 · DBLP profile ↗
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3ranked-venue papers
0as first author
3since 2021 · last 2026
0009-0006-3187-2321ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Security and privacy · 2 · 2 since 2021Systems, architecture and hardware · 1 · 1 since 2021Theory of computation · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Memory systems · 80% Storage systems · 20%
Network and information security
1 paper
Cryptographic protocols and secure computation · 100%

Topics — the 8 heaviest of 8, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Cryptographic protocols and secure computation › secret sharing › access structure
general access structures
1.012026
Traceable Secret Sharing Schemes for General Access Structures · EUROCRYPT 2026
Cryptographic protocols and secure computation
secret sharing
1.012026
Traceable Secret Sharing Schemes for General Access Structures · EUROCRYPT 2026
Cryptographic protocols and secure computation › secret sharing
traceable secret sharing
1.012026
Traceable Secret Sharing Schemes for General Access Structures · EUROCRYPT 2026
Memory systems
DRAM
0.812024
$\mathcal{O}(n)$O(n) Key-Value Sort With Active Compute Memory · IEEE Trans. Computers 2024
Storage systems
key-value storage
0.812024
$\mathcal{O}(n)$O(n) Key-Value Sort With Active Compute Memory · IEEE Trans. Computers 2024
Memory systems › processing-in-memory
near-memory processing
0.812024
$\mathcal{O}(n)$O(n) Key-Value Sort With Active Compute Memory · IEEE Trans. Computers 2024
Memory systems
processing-in-memory
0.812024
$\mathcal{O}(n)$O(n) Key-Value Sort With Active Compute Memory · IEEE Trans. Computers 2024
Memory systems › processing-in-memory
processing-using-DRAM
0.812024
$\mathcal{O}(n)$O(n) Key-Value Sort With Active Compute Memory · IEEE Trans. Computers 2024
YearPublicationVenuePosition
2026 Traceable Secret Sharing Schemes for General Access Structures
Oriol Farràs, Miquel Guiot
EUROCRYPT2
2024 Reducing the Share Size of Weighted Threshold Secret Sharing Schemes via Chow Parameters Approximation
Oriol Farràs, Miquel Guiot
TCC (4)2
2024 $\mathcal{O}(n)$O(n) Key-Value Sort With Active Compute Memory
abstract
We propose the Active Compute Memory (ACM), a near-memory-processing architecture capable of performing key–value sort directly in the DRAM. In the ACM architecture, sort is merely the writing of data into memory with one addressing protocol (perspective) and reading it back with different perspective. The first perspective is conventional, based on the data address; the second perspective is the sorted order. The ACM requires additional tables to store the meta-data and moderate control logic enhancements that can be implemented directly in the DRAM silicon. By these modest enhancements to DRAM, ACM exploits the parallelism inherently available in the row buffer to enable sort with$O(n)$complexity. This leads to an order of magnitude improvement in ACM performance and energy compared to conventional$O(n\log{}n)$CPU-centric sort algorithms. The ACM also shows superior performance compared to other near-memory sort accelerators. This is because the ACM processing is done near the row buffer and it exploits much lower memory access latency, higher bandwidth and wider parallel processing. The sort operation covered in this paper is just an example of an address management operation that can be efficiently implemented directly in the DRAM silicon. We release as an open source the simulation infrastructure for the ACM performance and energy modeling. We would encourage the community to use it, adapt it to other PIM proposals, and share their own evaluations.
Pouya Esmaili-Dokht, Miquel Guiot, Petar Radojkovic, Xavier Martorell, Eduard Ayguadé, Jesús Labarta, Jason Adlard, Paolo Amato, Marco Sforzin
IEEE Trans. Computers2