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Learning Scheduling Algorithms for Data Processing Clusters
v1v2v3v4 (latest)

Learning Scheduling Algorithms for Data Processing Clusters

3 October 2018
Hongzi Mao
Malte Schwarzkopf
S. Venkatakrishnan
Zili Meng
Mohammad Alizadeh
    OffRL
ArXiv (abs)PDFHTML

Papers citing "Learning Scheduling Algorithms for Data Processing Clusters"

28 / 28 papers shown
Title
Towards VM Rescheduling Optimization Through Deep Reinforcement Learning
Xianzhong Ding
Yunkai Zhang
Binbin Chen
Donghao Ying
Tieying Zhang
Jianjun Chen
Lei Zhang
Alberto Cerpa
Wan Du
VLM
130
1
0
23 May 2025
Improving the Efficiency of a Deep Reinforcement Learning-Based Power Management System for HPC Clusters Using Curriculum Learning
Improving the Efficiency of a Deep Reinforcement Learning-Based Power Management System for HPC Clusters Using Curriculum Learning
Thomas Budiarjo
Santana Yuda Pradata
Kadek Gemilang Santiyuda
Muhammad Alfian Amrizal
Reza Pulungan
Hiroyuki Takizawa
85
0
0
27 Feb 2025
Is the GPU Half-Empty or Half-Full? Practical Scheduling Techniques for LLMs
Is the GPU Half-Empty or Half-Full? Practical Scheduling Techniques for LLMs
Ferdi Kossmann
Bruce Fontaine
Daya Khudia
Michael Cafarella
Samuel Madden
255
2
0
23 Oct 2024
Online Reinforcement Learning in Non-Stationary Context-Driven Environments
Online Reinforcement Learning in Non-Stationary Context-Driven Environments
Pouya Hamadanian
Arash Nasr-Esfahany
Malte Schwarzkopf
Siddartha Sen
MohammadIman Alizadeh
CLLOffRL
108
0
0
04 Feb 2023
Real-world Video Adaptation with Reinforcement Learning
Real-world Video Adaptation with Reinforcement Learning
Hongzi Mao
Shannon Chen
Drew Dimmery
Shaun Singh
Drew Blaisdell
Yuandong Tian
Mohammad Alizadeh
E. Bakshy
OffRL
110
77
0
28 Aug 2020
Learning the Travelling Salesperson Problem Requires Rethinking
  Generalization
Learning the Travelling Salesperson Problem Requires Rethinking Generalization
Chaitanya K. Joshi
Quentin Cappart
Louis-Martin Rousseau
T. Laurent
183
119
0
12 Jun 2020
Benchmarking Graph Neural Networks
Benchmarking Graph Neural Networks
Vijay Prakash Dwivedi
Chaitanya K. Joshi
Anh Tuan Luu
T. Laurent
Yoshua Bengio
Xavier Bresson
438
940
0
02 Mar 2020
Placeto: Learning Generalizable Device Placement Algorithms for
  Distributed Machine Learning
Placeto: Learning Generalizable Device Placement Algorithms for Distributed Machine Learning
Ravichandra Addanki
S. Venkatakrishnan
Shreyan Gupta
Hongzi Mao
Mohammad Alizadeh
OODOffRL
59
68
0
20 Jun 2019
Deep Reinforcement Learning for Multi-Agent Systems: A Review of
  Challenges, Solutions and Applications
Deep Reinforcement Learning for Multi-Agent Systems: A Review of Challenges, Solutions and Applications
Thanh Thi Nguyen
Ngoc Duy Nguyen
S. Nahavandi
87
786
0
31 Dec 2018
Combinatorial Optimization with Graph Convolutional Networks and Guided
  Tree Search
Combinatorial Optimization with Graph Convolutional Networks and Guided Tree Search
Zhuwen Li
Qifeng Chen
V. Koltun
GNN
94
475
0
25 Oct 2018
Model-Based Reinforcement Learning via Meta-Policy Optimization
Model-Based Reinforcement Learning via Meta-Policy Optimization
I. Clavera
Jonas Rothfuss
John Schulman
Yasuhiro Fujita
Tamim Asfour
Pieter Abbeel
74
228
0
14 Sep 2018
Variance Reduction for Reinforcement Learning in Input-Driven
  Environments
Variance Reduction for Reinforcement Learning in Input-Driven Environments
Hongzi Mao
S. Venkatakrishnan
Malte Schwarzkopf
Mohammad Alizadeh
OffRL
80
95
0
06 Jul 2018
Relational inductive biases, deep learning, and graph networks
Relational inductive biases, deep learning, and graph networks
Peter W. Battaglia
Jessica B. Hamrick
V. Bapst
Alvaro Sanchez-Gonzalez
V. Zambaldi
...
Pushmeet Kohli
M. Botvinick
Oriol Vinyals
Yujia Li
Razvan Pascanu
AI4CENAI
761
3,129
0
04 Jun 2018
Device Placement Optimization with Reinforcement Learning
Device Placement Optimization with Reinforcement Learning
Azalia Mirhoseini
Hieu H. Pham
Quoc V. Le
Benoit Steiner
Rasmus Larsen
Yuefeng Zhou
Naveen Kumar
Mohammad Norouzi
Samy Bengio
J. Dean
85
440
0
13 Jun 2017
Constrained Policy Optimization
Constrained Policy Optimization
Joshua Achiam
David Held
Aviv Tamar
Pieter Abbeel
113
1,328
0
30 May 2017
Learning Combinatorial Optimization Algorithms over Graphs
Learning Combinatorial Optimization Algorithms over Graphs
H. Dai
Elias Boutros Khalil
Yuyu Zhang
B. Dilkina
Le Song
114
1,472
0
05 Apr 2017
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn
Pieter Abbeel
Sergey Levine
OOD
823
11,937
0
09 Mar 2017
Robust Adversarial Reinforcement Learning
Robust Adversarial Reinforcement Learning
Lerrel Pinto
James Davidson
Rahul Sukthankar
Abhinav Gupta
OOD
98
859
0
08 Mar 2017
RL$^2$: Fast Reinforcement Learning via Slow Reinforcement Learning
RL2^22: Fast Reinforcement Learning via Slow Reinforcement Learning
Yan Duan
John Schulman
Xi Chen
Peter L. Bartlett
Ilya Sutskever
Pieter Abbeel
OffRL
99
1,019
0
09 Nov 2016
Semi-Supervised Classification with Graph Convolutional Networks
Semi-Supervised Classification with Graph Convolutional Networks
Thomas Kipf
Max Welling
GNNSSL
644
29,076
0
09 Sep 2016
Convolutional Neural Networks on Graphs with Fast Localized Spectral
  Filtering
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering
M. Defferrard
Xavier Bresson
P. Vandergheynst
GNN
353
7,669
0
30 Jun 2016
TensorFlow: A system for large-scale machine learning
TensorFlow: A system for large-scale machine learning
Martín Abadi
P. Barham
Jianmin Chen
Zhiwen Chen
Andy Davis
...
Vijay Vasudevan
Pete Warden
Martin Wicke
Yuan Yu
Xiaoqiang Zhang
GNNAI4CE
433
18,361
0
27 May 2016
Asynchronous Methods for Deep Reinforcement Learning
Asynchronous Methods for Deep Reinforcement Learning
Volodymyr Mnih
Adria Puigdomenech Badia
M. Berk Mirza
Alex Graves
Timothy Lillicrap
Tim Harley
David Silver
Koray Kavukcuoglu
202
8,875
0
04 Feb 2016
Continuous control with deep reinforcement learning
Continuous control with deep reinforcement learning
Timothy Lillicrap
Jonathan J. Hunt
Alexander Pritzel
N. Heess
Tom Erez
Yuval Tassa
David Silver
Daan Wierstra
323
13,272
0
09 Sep 2015
Trust Region Policy Optimization
Trust Region Policy Optimization
John Schulman
Sergey Levine
Philipp Moritz
Michael I. Jordan
Pieter Abbeel
277
6,793
0
19 Feb 2015
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
1.9K
150,260
0
22 Dec 2014
PEGASUS: A Policy Search Method for Large MDPs and POMDPs
PEGASUS: A Policy Search Method for Large MDPs and POMDPs
A. Ng
Michael I. Jordan
110
496
0
16 Jan 2013
The Optimal Reward Baseline for Gradient-Based Reinforcement Learning
The Optimal Reward Baseline for Gradient-Based Reinforcement Learning
Lex Weaver
Nigel Tao
119
248
0
10 Jan 2013
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