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2020 – today
- 2024
[c34]Amey Agrawal, Sameer Reddy, Satwik Bhattamishra, Venkata Prabhakara Sarath Nookala, Vidushi Vashishth, Kexin Rong, Alexey Tumanov:
Inshrinkerator: Compressing Deep Learning Training Checkpoints via Dynamic Quantization. SoCC 2024: 1012-1031- [c33]Alind Khare, Animesh Agrawal, Aditya Annavajjala, Payman Behnam, Myungjin Lee, Hugo Latapie, Alexey Tumanov:
SuperFedNAS: Cost-Efficient Federated Neural Architecture Search for On-device Inference. ECCV (79) 2024: 161-179 - [c32]Payman Behnam, Uday Kamal, Ali Shafiee, Alexey Tumanov, Saibal Mukhopadhyay:
Harmonica: Hybrid Accelerator to Overcome Imperfections of Mixed-signal DNN Accelerators. IPDPS 2024: 619-630 - [c31]Amey Agrawal, Nitin Kedia, Jayashree Mohan, Ashish Panwar, Nipun Kwatra, Bhargav S. Gulavani, Ramachandran Ramjee, Alexey Tumanov:
VIDUR: A Large-Scale Simulation Framework for LLM Inference. MLSys 2024 - [c30]Amey Agrawal, Nitin Kedia, Ashish Panwar, Jayashree Mohan, Nipun Kwatra, Bhargav S. Gulavani, Alexey Tumanov, Ramachandran Ramjee:
Taming Throughput-Latency Tradeoff in LLM Inference with Sarathi-Serve. OSDI 2024: 117-134 - [i25]Amey Agrawal, Nitin Kedia, Ashish Panwar, Jayashree Mohan, Nipun Kwatra, Bhargav S. Gulavani, Alexey Tumanov, Ramachandran Ramjee:
Taming Throughput-Latency Tradeoff in LLM Inference with Sarathi-Serve. CoRR abs/2403.02310 (2024) - [i24]Amey Agrawal, Nitin Kedia, Jayashree Mohan, Ashish Panwar, Nipun Kwatra, Bhargav S. Gulavani, Ramachandran Ramjee, Alexey Tumanov:
Vidur: A Large-Scale Simulation Framework For LLM Inference. CoRR abs/2405.05465 (2024) - [i23]Aditya Annavajjala, Alind Khare, Animesh Agrawal, Igor Fedorov, Hugo Latapie, Myungjin Lee, Alexey Tumanov:
DεS: Delayed ε-Shrinking for Faster Once-For-All Training. CoRR abs/2407.06167 (2024) - [i22]Amey Agrawal, Anmol Agarwal, Nitin Kedia, Jayashree Mohan, Souvik Kundu, Nipun Kwatra, Ramachandran Ramjee, Alexey Tumanov:
Metron: Holistic Performance Evaluation Framework for LLM Inference Systems. CoRR abs/2407.07000 (2024) - [i21]Amey Agrawal, Junda Chen, Íñigo Goiri, Ramachandran Ramjee, Chaojie Zhang, Alexey Tumanov, Esha Choukse:
Mnemosyne: Parallelization Strategies for Efficiently Serving Multi-Million Context Length LLM Inference Requests Without Approximations. CoRR abs/2409.17264 (2024) - 2023
- [j3]Payman Behnam
, Jianming Tong, Alind Khare, Yangyu Chen, Yue Pan, Pranav Gadikar, Abhimanyu Bambhaniya, Tushar Krishna, Alexey Tumanov:
Hardware-Software Co-Design for Real-Time Latency-Accuracy Navigation in Tiny Machine Learning Applications. IEEE Micro 43(6): 93-101 (2023) - [c29]Yanbo Xu, Shangqing Xu, Manav Ramprassad, Alexey Tumanov, Chao Zhang:
TransEHR: Self-Supervised Transformer for Clinical Time Series Data. ML4H@NeurIPS 2023: 623-635 - [c28]Payman Behnam, Alexey Tumanov, Tushar Krishna, Pranav Gadikar, Yangyu Chen, Jianming Tong, Yue Pan, Abhimanyu Rajeshkumar Bambhaniya, Alind Khare:
Subgraph Stationary Hardware-Software Inference Co-Design. MLSys 2023 - [e1]Stefanos Laskaridis, Alexey Tumanov, Nathalie Baracaldo, Dimitrios Vytiniotis:
Proceedings of the 4th International Workshop on Distributed Machine Learning, DistributedML 2023, Paris, France, 8 December 2023. ACM 2023 [contents] - [i20]Alind Khare, Animesh Agrawal, Myungjin Lee, Alexey Tumanov:
SuperFed: Weight Shared Federated Learning. CoRR abs/2301.10879 (2023) - [i19]Amey Agrawal, Sameer Reddy, Satwik Bhattamishra, Venkata Prabhakara Sarath Nookala, Vidushi Vashishth, Kexin Rong, Alexey Tumanov:
DynaQuant: Compressing Deep Learning Training Checkpoints via Dynamic Quantization. CoRR abs/2306.11800 (2023) - [i18]Payman Behnam, Jianming Tong, Alind Khare, Yangyu Chen, Yue Pan, Pranav Gadikar, Abhimanyu Rajeshkumar Bambhaniya, Tushar Krishna, Alexey Tumanov:
Subgraph Stationary Hardware-Software Inference Co-Design. CoRR abs/2306.17266 (2023) - [i17]Debopam Sanyal, Jui-Tse Hung, Manav Agrawal, Prahlad Jasti, Shahab Nikkhoo, Somesh Jha, Tianhao Wang, Sibin Mohan, Alexey Tumanov:
Pareto-Secure Machine Learning (PSML): Fingerprinting and Securing Inference Serving Systems. CoRR abs/2307.01292 (2023) - [i16]Anshul Ahluwalia, Rohit Das, Payman Behnam, Alind Khare, Pan Li, Alexey Tumanov:
ABKD: Graph Neural Network Compression with Attention-Based Knowledge Distillation. CoRR abs/2310.15938 (2023) - [i15]Sachit Kuhar, Yash Jain, Alexey Tumanov:
Signed Binarization: Unlocking Efficiency Through Repetition-Sparsity Trade-Off. CoRR abs/2312.01581 (2023) - [i14]Alind Khare, Dhruv Garg, Sukrit Kalra, Snigdha Grandhi, Ion Stoica, Alexey Tumanov:
SuperServe: Fine-Grained Inference Serving for Unpredictable Workloads. CoRR abs/2312.16733 (2023) - 2022
- [c27]Romil Bhardwaj, Alexey Tumanov, Stephanie Wang, Richard Liaw, Philipp Moritz, Robert Nishihara, Ion Stoica:
ESCHER: expressive scheduling with ephemeral resources. SoCC 2022: 47-62 - [c26]Jun Shirako, Akihiro Hayashi, Sri Raj Paul, Alexey Tumanov, Vivek Sarkar:
Automatic Parallelization of Python Programs for Distributed Heterogeneous Computing. Euro-Par 2022: 350-366 - [c25]Yixuan Luo, Payman Behnam, Kiran Thorat, Zhuo Liu, Hongwu Peng, Shaoyi Huang, Shu Zhou, Omer Khan, Alexey Tumanov, Caiwen Ding, Tong Geng:
CoDG-ReRAM: An Algorithm-Hardware Co-design to Accelerate Semi-Structured GNNs on ReRAM. ICCD 2022: 280-289 - [c24]Yanbo Xu, Alind Khare, Glenn Matlin, Monish Ramadoss, Rishikesan Kamaleswaran, Chao Zhang, Alexey Tumanov:
UnfoldML: Cost-Aware and Uncertainty-Based Dynamic 2D Prediction for Multi-Stage Classification. NeurIPS 2022 - [i13]Jun Shirako, Akihiro Hayashi, Sri Raj Paul, Alexey Tumanov, Vivek Sarkar:
Automatic Parallelization of Python Programs for Distributed Heterogeneous Computing. CoRR abs/2203.06233 (2022) - [i12]Yanbo Xu, Alind Khare, Glenn Matlin, Monish Ramadoss, Rishikesan Kamaleswaran, Chao Zhang, Alexey Tumanov:
UnfoldML: Cost-Aware and Uncertainty-Based Dynamic 2D Prediction for Multi-Stage Classification. CoRR abs/2210.15056 (2022) - 2021
- [c23]Ujval Misra, Richard Liaw, Lisa Dunlap, Romil Bhardwaj, Kirthevasan Kandasamy, Joseph E. Gonzalez, Ion Stoica, Alexey Tumanov:
RubberBand: cloud-based hyperparameter tuning. EuroSys 2021: 327-342 - [c22]Manas Sahni, Shreya Varshini, Alind Khare, Alexey Tumanov:
CompOFA - Compound Once-For-All Networks for Faster Multi-Platform Deployment. ICLR 2021 - [i11]Manas Sahni, Shreya Varshini, Alind Khare, Alexey Tumanov:
CompOFA: Compound Once-For-All Networks for Faster Multi-Platform Deployment. CoRR abs/2104.12642 (2021) - 2020
- [j2]Vikram Sreekanti, Chenggang Wu, Xiayue Charles Lin, Johann Schleier-Smith, Joseph Gonzalez, Joseph M. Hellerstein, Alexey Tumanov:
Cloudburst: Stateful Functions-as-a-Service. Proc. VLDB Endow. 13(11): 2438-2452 (2020) - [c21]Daniel Crankshaw, Gur-Eyal Sela, Xiangxi Mo, Corey Zumar, Ion Stoica, Joseph Gonzalez, Alexey Tumanov:
InferLine: latency-aware provisioning and scaling for prediction serving pipelines. SoCC 2020: 477-491 - [c20]Shenda Hong, Yanbo Xu, Alind Khare, Satria Priambada, Kevin O. Maher, Alaa Aljiffry, Jimeng Sun, Alexey Tumanov:
HOLMES: Health OnLine Model Ensemble Serving for Deep Learning Models in Intensive Care Units. KDD 2020: 1614-1624 - [i10]Richard Liaw, Romil Bhardwaj, Lisa Dunlap, Yitian Zou, Joseph Gonzalez, Ion Stoica, Alexey Tumanov:
HyperSched: Dynamic Resource Reallocation for Model Development on a Deadline. CoRR abs/2001.02338 (2020) - [i9]Vikram Sreekanti, Chenggang Wu, Xiayue Charles Lin, Johann Schleier-Smith, Jose M. Faleiro, Joseph E. Gonzalez, Joseph M. Hellerstein, Alexey Tumanov:
Cloudburst: Stateful Functions-as-a-Service. CoRR abs/2001.04592 (2020) - [i8]Shenda Hong, Yanbo Xu, Alind Khare, Satria Priambada, Kevin O. Maher, Alaa Aljiffry, Jimeng Sun, Alexey Tumanov:
HOLMES: Health OnLine Model Ensemble Serving for Deep Learning Models in Intensive Care Units. CoRR abs/2008.04063 (2020)
2010 – 2019
- 2019
- [c19]Joseph M. Hellerstein, Jose M. Faleiro, Joseph Gonzalez, Johann Schleier-Smith, Vikram Sreekanti, Alexey Tumanov, Chenggang Wu:
Serverless Computing: One Step Forward, Two Steps Back. CIDR 2019 - [c18]João Carreira, Pedro Fonseca, Alexey Tumanov, Andrew Zhang, Randy H. Katz:
Cirrus: a Serverless Framework for End-to-end ML Workflows. SoCC 2019: 13-24 - [c17]Richard Liaw, Romil Bhardwaj, Lisa Dunlap, Yitian Zou, Joseph E. Gonzalez, Ion Stoica, Alexey Tumanov:
HyperSched: Dynamic Resource Reallocation for Model Development on a Deadline. SoCC 2019: 61-73 - [c16]Stephanie Wang, John Liagouris, Robert Nishihara, Philipp Moritz, Ujval Misra, Alexey Tumanov, Ion Stoica:
Lineage stash: fault tolerance off the critical path. SOSP 2019: 338-352 - [i7]Paras Jain, Xiangxi Mo, Ajay Jain, Harikaran Subbaraj, Rehan Sohail Durrani, Alexey Tumanov, Joseph Gonzalez, Ion Stoica:
Dynamic Space-Time Scheduling for GPU Inference. CoRR abs/1901.00041 (2019) - [i6]Paras Jain, Xiangxi Mo, Ajay Jain, Alexey Tumanov, Joseph E. Gonzalez, Ion Stoica:
The OoO VLIW JIT Compiler for GPU Inference. CoRR abs/1901.10008 (2019) - 2018
- [c15]Jun Woo Park, Alexey Tumanov, Angela H. Jiang, Michael A. Kozuch, Gregory R. Ganger:
3Sigma: distribution-based cluster scheduling for runtime uncertainty. EuroSys 2018: 2:1-2:17 - [c14]Philipp Moritz, Robert Nishihara, Stephanie Wang, Alexey Tumanov, Richard Liaw, Eric Liang, Melih Elibol, Zongheng Yang, William Paul, Michael I. Jordan, Ion Stoica:
Ray: A Distributed Framework for Emerging AI Applications. OSDI 2018: 561-577 - [c13]Xin Wang, Yujia Luo, Daniel Crankshaw, Alexey Tumanov, Fisher Yu, Joseph E. Gonzalez:
IDK Cascades: Fast Deep Learning by Learning not to Overthink. UAI 2018: 580-590 - [c12]Aaron Harlap, Andrew Chung, Alexey Tumanov, Gregory R. Ganger, Phillip B. Gibbons:
Tributary: spot-dancing for elastic services with latency SLOs. USENIX ATC 2018: 1-14 - [i5]Daniel Crankshaw, Gur-Eyal Sela, Corey Zumar, Xiangxi Mo, Joseph E. Gonzalez, Ion Stoica, Alexey Tumanov:
InferLine: ML Inference Pipeline Composition Framework. CoRR abs/1812.01776 (2018) - [i4]Joseph M. Hellerstein, Jose M. Faleiro, Joseph E. Gonzalez, Johann Schleier-Smith, Vikram Sreekanti, Alexey Tumanov, Chenggang Wu:
Serverless Computing: One Step Forward, Two Steps Back. CoRR abs/1812.03651 (2018) - 2017
- [c11]Aaron Harlap, Alexey Tumanov, Andrew Chung, Gregory R. Ganger, Phillip B. Gibbons:
Proteus: agile ML elasticity through tiered reliability in dynamic resource markets. EuroSys 2017: 589-604 - [c10]Robert Nishihara, Philipp Moritz, Stephanie Wang, Alexey Tumanov, William Paul, Johann Schleier-Smith, Richard Liaw, Mehrdad Niknami, Michael I. Jordan, Ion Stoica:
Real-Time Machine Learning: The Missing Pieces. HotOS 2017: 106-110 - [i3]Robert Nishihara, Philipp Moritz, Stephanie Wang, Alexey Tumanov, William Paul, Johann Schleier-Smith, Richard Liaw, Michael I. Jordan, Ion Stoica:
Real-Time Machine Learning: The Missing Pieces. CoRR abs/1703.03924 (2017) - [i2]Xin Wang, Yujia Luo, Daniel Crankshaw, Alexey Tumanov, Joseph E. Gonzalez:
IDK Cascades: Fast Deep Learning by Learning not to Overthink. CoRR abs/1706.00885 (2017) - [i1]Philipp Moritz, Robert Nishihara, Stephanie Wang, Alexey Tumanov, Richard Liaw, Eric Liang, William Paul, Michael I. Jordan, Ion Stoica:
Ray: A Distributed Framework for Emerging AI Applications. CoRR abs/1712.05889 (2017) - 2016
- [b1]Alexey Tumanov:
Scheduling with Space-Time Soft Constraints In Heterogeneous Cloud Datacenters. Carnegie Mellon University, USA, 2016 - [c9]Alexey Tumanov, Timothy Zhu, Jun Woo Park, Michael A. Kozuch, Mor Harchol-Balter, Gregory R. Ganger:
TetriSched: global rescheduling with adaptive plan-ahead in dynamic heterogeneous clusters. EuroSys 2016: 35:1-35:16 - [c8]Sangeetha Abdu Jyothi, Carlo Curino, Ishai Menache, Shravan Matthur Narayanamurthy, Alexey Tumanov, Jonathan Yaniv, Ruslan Mavlyutov, Iñigo Goiri, Subru Krishnan, Janardhan Kulkarni, Sriram Rao:
Morpheus: Towards Automated SLOs for Enterprise Clusters. OSDI 2016: 117-134 - 2014
- [j1]Lianghong Xu, James Cipar, Elie Krevat, Alexey Tumanov, Nitin Gupta, Michael A. Kozuch, Gregory R. Ganger:
Agility and Performance in Elastic Distributed Storage. ACM Trans. Storage 10(4): 16:1-16:27 (2014) - [c7]Henggang Cui, Alexey Tumanov, Jinliang Wei, Lianghong Xu, Wei Dai, Jesse Haber-Kucharsky, Qirong Ho, Gregory R. Ganger, Phillip B. Gibbons, Garth A. Gibson, Eric P. Xing:
Exploiting iterative-ness for parallel ML computations. SoCC 2014: 5:1-5:14 - [c6]Timothy Zhu, Alexey Tumanov, Michael A. Kozuch, Mor Harchol-Balter, Gregory R. Ganger:
PriorityMeister: Tail Latency QoS for Shared Networked Storage. SoCC 2014: 29:1-29:14 - [c5]Lianghong Xu, James Cipar, Elie Krevat, Alexey Tumanov, Nitin Gupta, Michael A. Kozuch, Gregory R. Ganger:
SpringFS: bridging agility and performance in elastic distributed storage. FAST 2014: 243-255 - 2012
- [c4]Charles Reiss, Alexey Tumanov, Gregory R. Ganger, Randy H. Katz, Michael A. Kozuch:
Heterogeneity and dynamicity of clouds at scale: Google trace analysis. SoCC 2012: 7 - [c3]Alexey Tumanov, James Cipar, Gregory R. Ganger, Michael A. Kozuch:
alsched: algebraic scheduling of mixed workloads in heterogeneous clouds. SoCC 2012: 25 - 2011
- [c2]Roy Bryant, Alexey Tumanov, Olga Irzak, Adin Scannell, Kaustubh R. Joshi, Matti A. Hiltunen, H. Andrés Lagar-Cavilla, Eyal de Lara:
Kaleidoscope: cloud micro-elasticity via VM state coloring. EuroSys 2011: 273-286
2000 – 2009
- 2007
- [c1]Alexey Tumanov, Robert S. Allison, Wolfgang Stürzlinger:
Variability-Aware Latency Amelioration in Distributed Environments. VR 2007: 123-130
Coauthor Index
aka: Joseph E. Gonzalez
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