Viewing Allocators as Bin Packing Solvers Demystifies Fragmentation
Christos P. Lamprakos, Sotirios Xydis, Francky Catthoor, Dimitrios, Soudris

TL;DR
This paper introduces a trace-based simulation method using 2D rectangular bin packing to analyze allocator fragmentation and its impact on peak resident set size, providing a new perspective on memory management efficiency.
Contribution
It models workload-allocator interactions as 2DBP instances, creating a compact, event-focused data structure that links fragmentation metrics to peak RSS across multiple allocators.
Findings
Fragmentation metric correlates with peak RSS reduction by 9-30%.
Better 2DBP placements lead to smaller peak RSS in half of the workloads.
The approach is scalable, handling 80 million requests in 350 MiB memory.
Abstract
This paper presents a trace-based simulation methodology for constructing representations of workload-allocator interaction. We use two-dimensional rectangular bin packing (2DBP) as our foundation. Classical 2DBP algorithms minimize their products' makespan, but virtual memory systems employing demand paging deem such a criterion inappropriate. We view an allocator's placement decisions as a solution to a 2DBP instance, optimizing some unknown criterion particular to that allocator's policy. Our end product is a compact data structure that fits e.g. the simulation of 80 million requests in a 350 MiB file. By design, it is concerned with events residing entirely in virtual memory; no information on memory accesses, indexing costs or any other factor is kept. We bootstrap our contribution's significance by exploring its relationship to maximum resident set size (RSS). Our baseline is…
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Taxonomy
TopicsOptimization and Search Problems · Interconnection Networks and Systems · Distributed systems and fault tolerance
