Virtual Garbage Collector (VGC): A Zone-Based Garbage Collection Architecture for Python's Parallel Runtime
Fuente:
arXiv
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866918268339486720 |
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| author | M, Abdulla |
| author_facet | M, Abdulla |
| contents | The Virtual Garbage Collector (VGC) proposes a zone-based memory management architecture aimed at improving execution predictability and memory behavior in Python runtimes. The design explores a dual-layer model consisting of an Active VGC, responsible for managing runtime object lifecycles, and a Passive VGC, intended as a compile-time optimization layer for static allocation planning. Rather than relying on traditional heap traversal or generational heuristics, VGC introduces memory zoning and checkpoint-based state evaluation to reduce allocation churn and constrain garbage collection scope. Execution partitioning is experimentally evaluated to isolate workloads and localize memory pressure, enabling more deterministic behavior under loop-intensive, recursive, and compute-heavy workloads. This work presents the architectural principles, execution model, and experimental observations of VGC within a partition-aware runtime context. While the full realization of the dual-layer design is an ongoing effort, the results indicate that zone-based allocation and partitioned execution provide a viable foundation for improving scalability and memory predictability in Python-oriented systems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_23768 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Virtual Garbage Collector (VGC): A Zone-Based Garbage Collection Architecture for Python's Parallel Runtime M, Abdulla Programming Languages Distributed, Parallel, and Cluster Computing The Virtual Garbage Collector (VGC) proposes a zone-based memory management architecture aimed at improving execution predictability and memory behavior in Python runtimes. The design explores a dual-layer model consisting of an Active VGC, responsible for managing runtime object lifecycles, and a Passive VGC, intended as a compile-time optimization layer for static allocation planning. Rather than relying on traditional heap traversal or generational heuristics, VGC introduces memory zoning and checkpoint-based state evaluation to reduce allocation churn and constrain garbage collection scope. Execution partitioning is experimentally evaluated to isolate workloads and localize memory pressure, enabling more deterministic behavior under loop-intensive, recursive, and compute-heavy workloads. This work presents the architectural principles, execution model, and experimental observations of VGC within a partition-aware runtime context. While the full realization of the dual-layer design is an ongoing effort, the results indicate that zone-based allocation and partitioned execution provide a viable foundation for improving scalability and memory predictability in Python-oriented systems. |
| title | Virtual Garbage Collector (VGC): A Zone-Based Garbage Collection Architecture for Python's Parallel Runtime |
| topic | Programming Languages Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2512.23768 |