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Utilities for analyzing object references and memory usage in distributed clusters.
Distinguishing note: Specifically targets cluster-wide object reference analysis for leak detection.
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Ray is a distributed computing framework designed to scale Python and Java applications across clusters by abstracting task scheduling and resource management. It functions as a resource-aware execution engine that manages task dependencies, placement, and fault tolerance across networked compute nodes. At its core, the system provides a stateful actor model, allowing developers to define classes that run in dedicated processes to maintain and mutate internal state across remote method calls. The framework distinguishes itself through a robust cross-language interoperability layer, enabling f
Enables analyzing object references held in a cluster to identify memory leaks or high usage.