Local Memory Requirements in Embedded NUMA Architectures

Document Type

Conference Paper

Publication Date

2025

Publication Title

2025 27TH INTERNATIONAL SYMPOSIUM ON SYMBOLIC AND NUMERIC ALGORITHMS FOR SCIENTIFIC COMPUTING, SYNASC

Abstract

During the last years, real-time applications have increasingly employed multicore architectures, in response to the continuous growth in the complexity of the problems they are approaching. A large variety of structures have been proposed, leading to significantly different approaches.

NUMA (Non-Uniform Memory Access) architectures are widely used, which comes as no surprise since, from a historical point of view, many embedded systems have been using local memories. While the use of local memories is key to increasing performance, the asymmetry of the access times raises difficult questions regarding the efficient management of the available resources, especially when shared variables are present. The issue is even more obvious in automotive systems, where the large amount of information involved pushes the size of reallife problems to the limits of intractability and thus requires innovative approaches.

A recent example is [1], which is approaching the allocation of the jobs' data and code to the processors in a NUMA system. As the problem is intractable for common automotive applications, the idea is to decompose it into smaller subproblems, to be dealt with sequentially. Nevertheless, because multiple phases rely on Integer Linear Programming (ILP), tractability is still a matter of concern.

This paper proposes an alternative to the existing solution, based on the same principles. A rethinking of the decomposition into subproblems allows a simpler (non-ILP) solution to one phase, while for another one the ILP is simplified. Experimental results show that, while the new approach is not necessarily more efficient, it is comparable to the existing one, to a degree that justifies the gain in simplicity.

Comments

Meeting: 27th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing-SYNASC
Location:Timisoara, ROMANIA
Date: SEP 22-25, 2025

DOI

10.1109/SYNASC69064.2025.00021

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