Wei Lin
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| title | conference | date |
|---|---|---|
| Tessera: A Holistic Pipeline Parallelism Framework for Trillion-Parameter Heterogeneous | 20th USENIX Symposium on Operating Systems Design and Implementation (OSDI '26) | 2026-07-13 |
Tessera is a pipeline-parallel framework that profiles fine-grained, per-pair overlap schedules and uses those measured post-overlap costs to cut stages, then… | ||
| Evolution of Aegis: Fault Diagnosis for AI Model Training Service in Production | NSDI '25 | 2025-04-28 |
Aegis is a production fault diagnosis system for AI model training that evolves from enhanced legacy tools to a customized collective communication library… | ||
| Llumnix: Dynamic Scheduling for Large Language Model Serving | 18th USENIX Symposium on Operating Systems Design and Implementation (OSDI '24) | 2024-07-10 |
Llumnix implements live migration of per-request KV caches to reschedule running LLM inferences across instances with near-zero downtime, using a distributed… | ||
| MonoNN: Enabling a New Monolithic Optimization Space for Neural Network Inference... | 18th USENIX Symposium on Operating Systems Design and Implementation (OSDI '24) | 2024-07-10 |
MonoNN compiles an entire static neural network into a monolithic kernel on a single GPU to slash CPU-to-GPU launch and off‑chip traffic, empirically… | ||
| Deploying User-space TCP at Cloud Scale with LUNA | USENIX ATC '23 | 2023-07-10 |
LUNA is a user-space TCP libOS built with DPDK and SR-IOV/flow-steering that runs on a run-to-completion model (batch and inline r2c), a user-space… | ||
| Whale: Efficient Giant Model Training over Heterogeneous GPUs | USENIX ATC '22 | 2022-07-11 |
Whale is a distributed training framework that adds two model-annotation primitives, replicate and split, to transform a local DAG into a distributed plan and… | ||
| MLaaS in the Wild: Workload Analysis and Scheduling in Large-Scale Heterogeneous GPU... | 19th USENIX Symposium on Networked Systems Design and Implementation (NSDI '22) | 2022-04-04 |
A two-month Alibaba MLaaS trace covers over 6,700 GPUs across ~1,800 nodes with 1.2M tasks, 7.5M instances and shows concrete pain points: 85% gang-scheduled… | ||
| On Design and Enhancement of Smart Grid Honeypot System for Practical Collection... | 13th USENIX Workshop on Cyber Security Experimentation and Test (CSET '20) | 2020-08-10 |
A virtual smart‑grid honeypot is built that emulates a substation and control‑center network (SCADA/HMI, historian, VPNs, IEDs, gateway) and is hardened… | ||
| Panel: Women in Security | OWASP AppSec California 2016 | 2016-01-25 |
Panelists give concrete numbers and fixes not platitudes They cite 35% in 1985 to 17% in 2011 for CS degrees and tie that to attrition at every career stage… | ||
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