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Stephanie Wang

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NanoFlow: Towards Optimal Large Language Model Serving ThroughputOSDI '252025-07-07
NanoFlow splits request batches into nano-batches and duplicates per-batch operations to overlap compute, memory (KV cache), and network work within a single…
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Evolving Ray Core: Scalability, Reliability, and Compiled GraphsRay Summit 20242024-09-30
Weekly releases and structured logging reduce release latency and improve observability, streaming generators let callers consume object refs while tasks still…
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ExoFlow: A Universal Workflow System for Exactly-Once DAGsOSDI 20232023-07-10
ExoFlow implements a workflow runtime that decouples execution from recovery, providing exactly-once semantics via a separate recovery layer, task annotations…
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One beginner’s guide to XR world buildingXConf North America 20222022-07-27
Built an AR book with Unity and Vuforia using hand drawings turned into five‑star image targets, Unity Asset Store models, a few lines of C# and export via…
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Ray Internals: Object Management with the Ownership ModelRay Summit 20212021-06-22
Ray restructures object metadata by shards the master across workers so the creator of an object owns its metadata, keeping location and lineage local to…
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Ownership: A Distributed Futures System for Fine-Grained TasksNSDI ’212021-04-12
Ownership claims a decentralized runtime that shards metadata by object owner, trades global persistence for simple recovery, and achieves 1ms latency per task…
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Taming Java Dependencies in 70+ GCP Client LibrariesDevnexus 20212021-02-17
Google Cloud manages 70+ Java client libraries, each with 20+ direct dependencies, by publishing a centralized google cloud share dependencies bom and using…
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Ray Internals: A Peek at `ray.get`Ray Summit 20202020-09-30
Deep dive into what ray.get actually does: precise lifecycle of an object, how small objects stay at the owner while large objects live in a distributed store…
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Ray: A distributed system for emerging AI applicationsStrange Loop 20182018-09-26
Ray is an open source distributed system that implements task and actor abstractions for Python ML workloads, with a C++ backend, Python workers, an in‑memory…
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