Data Cache for Intermittent Computing Systems with Non-Volatile Main Memory

Intermittently-operating embedded computing platforms powered by energy harvesting must frequently checkpoint their computation state. Using non-volatile memory reduces checkpoint size by eliminating the need to checkpoint volatile memory but increases checkpoint frequency to cover Write After Read (WAR) dependencies. Additionally, non-volatile memory is significantly slower to access - while consuming more energy than its volatile counterpart - suggesting the use of a data cache. Unfortunately, existing data cache solutions do not fit the challenges of intermittent computing and often require additional hardware or software to detect WARs. In this paper, we extend the data cache by integrating it with WAR detection - dropping the need for an additional memory tracker. This idea forms the basis of NACHO: a data cache tailored to intermittent computing. NACHO, on average, reduces intermittent computing runtime overhead by 54% compared to state of the art cache-based systems. It also reduces the number of non-volatile memory writes by 82% compared to a data cache-less system, and 18% on average compared to multiple state of the art cache-based systems.

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Publication Details

Published
2025-03-27
DOI
https://doi.org/10.1145/3676641.3715989
Citations
1
Primary Topic
Distributed systems and fault tolerance
Type
article
Field-Weighted Citation Impact
1.49
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Data Cache for Intermittent Computing Systems with Non-Volatile Main Memory

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article

Data Cache for Intermittent Computing Systems with Non-Volatile Main Memory

Przemysław Pawełczak, J BROEKHOFF, Saad Ahmed, Vito Kortbeek, Sourav Mohapatra, Marco Antonio van Eerden
article en
1 citations

Abstract

Intermittently-operating embedded computing platforms powered by energy harvesting must frequently checkpoint their computation state. Using non-volatile memory reduces checkpoint size by eliminating the need to checkpoint volatile memory but increases checkpoint frequency to cover Write After Read (WAR) dependencies. Additionally, non-volatile memory is significantly slower to access - while consuming more energy than its volatile counterpart - suggesting the use of a data cache. Unfortunately, existing data cache solutions do not fit the challenges of intermittent computing and often require additional hardware or software to detect WARs. In this paper, we extend the data cache by integrating it with WAR detection - dropping the need for an additional memory tracker. This idea forms the basis of NACHO: a data cache tailored to intermittent computing. NACHO, on average, reduces intermittent computing runtime overhead by 54% compared to state of the art cache-based systems. It also reduces the number of non-volatile memory writes by 82% compared to a data cache-less system, and 18% on average compared to multiple state of the art cache-based systems.

Georgia Institute of Technology (US), ARM (United Kingdom) (GB), Delft University of Technology (NL)
Openalex Percentile: Top 19%
Distributed systems and fault tolerance
1.49
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