Myeongjae Jeon
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| title | conference | date |
|---|---|---|
| Metis: Fast Automatic Distributed Training on Heterogeneous GPUs | USENIX ATC 2024 | 2024-07-10 |
Metis automatically finds parallelism plans for training across mixed GPU types by profiling each GPU, estimating cost, and using a planner that prunes skewed… | ||
| Sponge: Fast Reactive Scaling for Stream Processing with Serverless Frameworks | USENIX ATC '23 | 2023-07-10 |
Sponge is a stream-processing runtime that pre-inserts router, transient and merge operators at compile time to avoid runtime state migration, redirects bursty… | ||
| EnvPipe: Performance-preserving DNN Training Framework for Saving Energy | USENIX ATC '23 | 2023-07-10 |
EnvPipe is a PyTorch library that profiles each pipeline stage, reschedules pipeline units to expose usable pipeline bubbles, and selectively lowers GPU SM… | ||
| Sibylla: To Retry or Not To Retry on Deep Learning Job Failure | USENIX ATC '22 | 2022-07-11 |
Sibylla classifies DL job failures as deterministic or nondeterministic by training RNN models (GRU/LSTM-like) on stdout/stderr logs and updating online with… | ||
| Memory Harvesting in Multi-GPU Systems with Hierarchical Unified Virtual Memory | USENIX ATC '22 | 2022-07-11 |
Implements a hierarchical unified virtual memory (HUVM) that spills GPU pages to neighbor GPUs over NVLink instead of host PCIe, and ships a centralized memory… | ||
| Zico: Efficient GPU Memory Sharing for Concurrent DNN Training | USENIX ATC '21 | 2021-07-14 |
Zico builds a shared GPU memory pool plus a memory manager that uses CUDA events and an in‑flight kernel counter to safely reclaim and limit allocations, and a… | ||
| Analysis of Large-Scale Multi-Tenant GPU Clusters for DNN Training Workloads | USENIX ATC '19 | 2019-07-10 |
Analysis uses a 75‑day trace from Microsoft Philly (shared by 14 production groups) combining scheduler logs, hardware counters and AI‑engine logs to profile… | ||
| Tiresias: A GPU Cluster Manager for Distributed Deep Learning | NSDI 2019 | 2019-02-26 |
Tiresias is a GPU cluster manager that actually implements two age‑based schedulers — Discretized Two‑Dimensional Gittins index (needs a prior distribution)… | ||
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