Deep dive into Android Runtime memory management during ML inference — using profile-guided compilation hints, large object space pinning, and region-based allocation to eliminate GC stalls that cause frame drops when running on-device models. Covers RegionSpace tuning, CC collector behavior during tensor allocation bursts, and the JNI boundary strategies that keep native inference buffers out of managed heap pressure.
title: "ART Memory Tuning: Cut On-Device ML GC Pauses 90%"
published: true
description: "Profile-guided allocation, object pinning, and RegionSpace tuning eliminate GC stalls during on-device ML inference. Practical ART memory strategies that actually work."
tags: android, kotlin, architecture, mobile
canonical_url: https://mvpfactory.co/blog/art-memory-tuning-cut-on-device-ml-gc-pauses-90
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