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Quanlu Zhang

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RLinf: Flexible and Efficient Large-Scale Reinforcement Learning...20th USENIX Symposium on Operating Systems Design and Implementation (OSDI '26)2026-07-13
RLinf is a distributed RL training system that implements macro-to-micro flow transformation to break high-level workflows into optimized execution flows; it…
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DynaRL: Flexible and Dynamic Scheduling of Large-Scale Reinforcement Learning Training20th USENIX Symposium on Operating Systems Design and Implementation (OSDI '26)2026-07-13
DynaRL claims a system that reclaims idle GPUs and reallocates them online using a dynamic hypergraph + a unified interrupt and migrate APIs, with three…
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Ladder: Enabling Efficient Low-Precision Deep Learning Computing through...18th USENIX Symposium on Operating Systems Design and Implementation (OSDI '24)2024-07-10
Ladder is a compiler that represents evolving low‑bit formats as a first‑class tType and exposes four concrete tensor transforms (slice/map/convert/pad) to…
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nnScaler: Constraint-Guided Parallelization Plan Generation for Deep Learning Training18th USENIX Symposium on Operating Systems Design and Implementation (OSDI '24)2024-07-10
A plan-generation framework implements three primitives op-trans, op-assign, op-order plus constraint filters so experts compose custom parallelization spaces…
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AutoSys: The Design and Operation of Learning-Augmented SystemsUSENIX ATC '202020-07-15
AutoSys is a unified framework that runs Hyperband, TPE, SMAC tuners and trial benchmarks to auto-tune five Web Search engines (selection, ranking, KV stores)…
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