Multicore Implementation of ML-KEM on Embedded Devices

This paper introduces a cost-effective function-selection procedure, anchored in Amdahl’s Law, to orchestrate selective parallelization of Module-Lattice-Based Key-Encapsulation Mechanism Standard (ML-KEM) scheme on a dual-core ESP32 microcontroller. The procedure quantifies each function’s single-core runtime and the overhead of parallel execution to isolate routines whose concurrent execution yields net time savings, while excluding low-latency tasks. The resulting ESP32 implementation eliminates separate single- and dual-core code paths, simplifies development, and achieves substantial reductions in overall runtime. Experimental evaluation on a dual-core ESP32 microcontroller of ML-KEM confirms the procedure’s suitability for latency-critical applications.

Authors

Institutions

Publication Details

Published
2025-09-01
DOI
https://doi.org/10.5753/sbseg.2025.9783
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Multicore Implementation of ML-KEM on Embedded Devices

Moisés V. Ribeiro, Vinícius Lagrota, Beatriz L. Azevedo
Parallel Computing and Optimization Techniques
article

Multicore Implementation of ML-KEM on Embedded Devices

Moisés V. Ribeiro, Vinícius Lagrota, Beatriz L. Azevedo
article en

Abstract

This paper introduces a cost-effective function-selection procedure, anchored in Amdahl’s Law, to orchestrate selective parallelization of Module-Lattice-Based Key-Encapsulation Mechanism Standard (ML-KEM) scheme on a dual-core ESP32 microcontroller. The procedure quantifies each function’s single-core runtime and the overhead of parallel execution to isolate routines whose concurrent execution yields net time savings, while excluding low-latency tasks. The resulting ESP32 implementation eliminates separate single- and dual-core code paths, simplifies development, and achieves substantial reductions in overall runtime. Experimental evaluation on a dual-core ESP32 microcontroller of ML-KEM confirms the procedure’s suitability for latency-critical applications.

Universidade Federal de Juiz de Fora (BR), Centro de Estudos e Pesquisa em Saúde Coletiva (BR)
Openalex Percentile: Top 74%
Parallel Computing and Optimization Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.