| Automatic Parallelization of Python Programs for Distributed Heterogeneous Computing | 0 | 0.34 | 2022 |
| CompOFA – Compound Once-For-All Networks for Faster Multi-Platform Deployment | 0 | 0.34 | 2021 |
| RubberBand: cloud-based hyperparameter tuning | 1 | 0.35 | 2021 |
| Cloudburst: Stateful Functions-as-a-Service. | 0 | 0.34 | 2020 |
| Cloudburst: Stateful Functions-as-a-Service. | 11 | 0.65 | 2020 |
| InferLine: latency-aware provisioning and scaling for prediction serving pipelines | 2 | 0.37 | 2020 |
| HOLMES: Health OnLine Model Ensemble Serving for Deep Learning Models in Intensive Care Units | 0 | 0.34 | 2020 |
| Serverless Computing: One Step Forward, Two Steps Back. | 0 | 0.34 | 2019 |
| Cirrus - a Serverless Framework for End-to-end ML Workflows. | 7 | 0.48 | 2019 |
| The OoO VLIW JIT Compiler for GPU Inference. | 0 | 0.34 | 2019 |
| Dynamic Space-Time Scheduling for GPU Inference. | 2 | 0.37 | 2019 |
| Lineage stash: fault tolerance off the critical path | 2 | 0.36 | 2019 |
| HyperSched - Dynamic Resource Reallocation for Model Development on a Deadline. | 1 | 0.36 | 2019 |
| 3Sigma: distribution-based cluster scheduling for runtime uncertainty | 5 | 0.41 | 2018 |
| InferLine: ML Inference Pipeline Composition Framework. | 2 | 0.36 | 2018 |
| Idk Cascades: Fast Deep Learning By Learning Not To Overthink | 5 | 0.39 | 2018 |
| Proteus: agile ML elasticity through tiered reliability in dynamic resource markets. | 17 | 0.58 | 2017 |
| Real-Time Machine Learning: The Missing Pieces. | 7 | 0.47 | 2017 |
| Morpheus: Towards Automated SLOs for Enterprise Clusters. | 21 | 0.72 | 2016 |
| TetriSched: global rescheduling with adaptive plan-ahead in dynamic heterogeneous clusters. | 29 | 0.83 | 2016 |
| Agility and Performance in Elastic Distributed Storage | 2 | 0.39 | 2014 |
| SpringFS: bridging agility and performance in elastic distributed storage | 11 | 0.63 | 2014 |
| Exploiting iterative-ness for parallel ML computations | 4 | 0.48 | 2014 |
| PriorityMeister: Tail Latency QoS for Shared Networked Storage | 29 | 0.84 | 2014 |
| Heterogeneity and dynamicity of clouds at scale: Google trace analysis | 349 | 10.70 | 2012 |
| alsched: algebraic scheduling of mixed workloads in heterogeneous clouds | 19 | 1.41 | 2012 |
| Kaleidoscope: cloud micro-elasticity via VM state coloring | 24 | 0.94 | 2011 |
| Variability-Aware Latency Amelioration in Distributed Environments | 4 | 0.48 | 2007 |
