SafeSU-2L: An Advanced Multicore Interference Statistics Unit for a RISC-V Space SoC

Multicores for critical real-time embedded systems (CRTES) may experience interference across tasks running in different cores when accessing shared hardware resources such as shared caches and memory controllers. Precise interference diagnostics (e.g., what task interferes what other task and how much) are key for the optimization and validation of safety-related real-time applications during development, and to diagnose overruns during operation. The SafeSU statistics unit has been proposed recently for that purpose, and proven successful for systems-on-chip (SoCs) where interference can occur at a single centralized locations (e.g., a bus). However, it is unable to monitor interference in multiple-level interconnects, especially if request ownership is not available. This paper extends the SafeSU to 2-level interconnects (SafeSU-2 L), where interference can occur in the bus connecting the cores with a shared second level cache (L2C), and in the DDR4 memory controller serving L2C misses, with the latter losing track of the actual core issuing each DDR4 request. In particular, the SafeSU-2 L monitors some additional signals from the buses and caches to infer what core interferes what other core in any of the shared resources. Moreover, the SafeSU-2 L is integrated and tested on a 4-core version of the commercial CAES Gaisler NOEL-XCKU-EX space SoC.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Aerospace and Electronic Systems
Published
2025-04-16
DOI
https://doi.org/10.1109/taes.2025.3561732
Primary Topic
Embedded Systems Design Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

SafeSU-2L: An Advanced Multicore Interference Statistics Unit for a RISC-V Space SoC

Francisco Bas, Jaume Abella, Ramón Canal, Sergi Alcaide et al.
IEEE Transactions on Aerospace and Electronic Systems
Embedded Systems Design Techniques
article

SafeSU-2L: An Advanced Multicore Interference Statistics Unit for a RISC-V Space SoC

Francisco Bas, Jaume Abella, Ramón Canal, Sergi Alcaide, Juan Carlos Rodríguez, Francisco Fuentes, Pedro Benedicte, Guillem Cabo, Ilham Lasfar, Chang Feng
article en

Abstract

Multicores for critical real-time embedded systems (CRTES) may experience interference across tasks running in different cores when accessing shared hardware resources such as shared caches and memory controllers. Precise interference diagnostics (e.g., what task interferes what other task and how much) are key for the optimization and validation of safety-related real-time applications during development, and to diagnose overruns during operation. The SafeSU statistics unit has been proposed recently for that purpose, and proven successful for systems-on-chip (SoCs) where interference can occur at a single centralized locations (e.g., a bus). However, it is unable to monitor interference in multiple-level interconnects, especially if request ownership is not available. This paper extends the SafeSU to 2-level interconnects (SafeSU-2 L), where interference can occur in the bus connecting the cores with a shared second level cache (L2C), and in the DDR4 memory controller serving L2C misses, with the latter losing track of the actual core issuing each DDR4 request. In particular, the SafeSU-2 L monitors some additional signals from the buses and caches to infer what core interferes what other core in any of the shared resources. Moreover, the SafeSU-2 L is integrated and tested on a 4-core version of the commercial CAES Gaisler NOEL-XCKU-EX space SoC.

IEEE Transactions on Aerospace and Electronic SystemsVol. 61(4)
Prudential Financial (United States) (US), Barcelona Supercomputing Center (ES), Graphcore (United Kingdom) (GB), University of Gothenburg (SE), Universitat Politècnica de Catalunya (ES)
Openalex Percentile: Top 94%
Embedded Systems Design 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.