Shivaram Venkataraman
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
51
Venues
22
Active years
2010–2026
Best venue rank
A*
Where they publish
- NationalNSDI7 papers
- ASC6 papers
- AEuroSys5 papers
- A*OSDI5 papers
- A*ICML4 papers
- BCLOUD4 papers
- A*SIGMOD3 papers
- A*SOSP3 papers
- AICS1 paper
- A*SIGMETRICS1 paper
- ANAACL1 paper
- ACoNEXT1 paper
- ACIDR1 paper
- A*MOBICOM1 paper
- AUSENIX1 paper
- A*ICDE1 paper
- A*KDD1 paper
- A*VLDB1 paper
- AHotOS1 paper
- AFAST1 paper
- AACSAC1 paper
- BCEC1 paper
Papers
51 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | ICS | Wattchmen: Watching the Wattchers - High Fidelity, Flexible GPU Energy Modeling. | Brandon Tran, Matthias Maiterth, Woong Shin, Matthew D. Sinclair, Shivaram Venkataraman |
| 2026 | NSDI | SYMPHONY: Enabling Compute-Memory Disaggregation in LLM Serving Systems. | Saurabh Agarwal, Bodun Hu, Anyong Mao, Aditya Akella, Shivaram Venkataraman |
| 2026 | SIGMOD | Demo of SemWeave: Semantic Common Expressions for LLM-powered Query Processing. | Md. Tareq Mahmood, K. Venkatesh Emani, Hangdong Zhao, Shivaram Venkataraman |
| 2026 | SIGMETRICS | Minos: Systematically Classifying Performance and Power Characteristics of GPU Workloads on HPC Clusters. | Rutwik Jain, Yiwei Jiang, Matthew D. Sinclair, Shivaram Venkataraman |
| 2025 | EuroSys | Eva: Cost-Efficient Cloud-Based Cluster Scheduling. | Tzu-Tao Chang, Shivaram Venkataraman |
| 2025 | EuroSys | TUNA: Tuning Unstable and Noisy Cloud Applications. | Johannes Freischuetz, Konstantinos Kanellis, Brian Kroth, Shivaram Venkataraman |
| 2025 | ICML | Scaling Inference-Efficient Language Models. | Song Bian, Minghao Yan, Shivaram Venkataraman |
| 2025 | ICML | LV-XAttn: Distributed Cross-Attention for Long Visual Inputs in Multimodal Large Language Models. | Tzu-Tao Chang, Shivaram Venkataraman |
| 2025 | NAACL | Decoding Speculative Decoding. | Minghao Yan, Saurabh Agarwal, Shivaram Venkataraman |
| 2025 | OSDI | Quake: Adaptive Indexing for Vector Search. | Jason Mohoney, Devesh Sarda, Mengze Tang, Shihabur Rahman Chowdhury, Anil Pacaci, Ihab F. Ilyas, Theodoros Rekatsinas, Shivaram Venkataraman |
| 2025 | SC | PGT-I: Scaling Spatiotemporal GNNs with Memory-Efficient Distributed Training. | Seth Ockerman, Amal Gueroudji, Tanwi Mallick, Yixuan He, Line Pouchard, Robert B. Ross, Shivaram Venkataraman |
| 2025 | SC | Exploring Distributed Vector Databases Performance on HPC Platforms: A Study with Qdrant. | Seth Ockerman, Amal Gueroudji, Song Young Oh, Robert Underwood, Nicholas Chia, Kyle Chard, Robert B. Ross, Shivaram Venkataraman |
| 2024 | EuroSys | Blox: A Modular Toolkit for Deep Learning Schedulers. | Saurabh Agarwal, Amar Phanishayee, Shivaram Venkataraman |
| 2024 | ICML | CHAI: Clustered Head Attention for Efficient LLM Inference. | Saurabh Agarwal, Bilge Acun, Basil Hosmer, Mostafa Elhoushi, Yejin Lee, Shivaram Venkataraman, Dimitris Papailiopoulos, Carole-Jean Wu |
| 2024 | SC | PAL: A Variability-Aware Policy for Scheduling ML Workloads in GPU Clusters. | Rutwik Jain, Brandon Tran, Keting Chen, Matthew D. Sinclair, Shivaram Venkataraman |
| 2023 | EuroSys | MariusGNN: Resource-Efficient Out-of-Core Training of Graph Neural Networks. | Roger Waleffe, Jason Mohoney, Theodoros Rekatsinas, Shivaram Venkataraman |
| 2023 | NSDI | Shockwave: Fair and Efficient Cluster Scheduling for Dynamic Adaptation in Machine Learning. | Pengfei Zheng, Rui Pan, Tarannum Khan, Shivaram Venkataraman, Aditya Akella |
| 2023 | SC | Mirage: Towards Low-interruption Services on Batch GPU Clusters with Reinforcement Learning. | Qiyang Ding, Pengfei Zheng, Shreyas Kudari, Shivaram Venkataraman, Zhao Zhang |
| 2023 | SOSP | Bagpipe: Accelerating Deep Recommendation Model Training. | Saurabh Agarwal, Chengpo Yan, Ziyi Zhang, Shivaram Venkataraman |
| 2022 | SC | Not All GPUs Are Created Equal: Characterizing Variability in Large-Scale, Accelerator-Rich Systems. | Prasoon Sinha, Akhil Guliani, Rutwik Jain, Brandon Tran, Matthew D. Sinclair, Shivaram Venkataraman |
| 2021 | CLOUD | Atoll: A Scalable Low-Latency Serverless Platform. | Arjun Singhvi, Arjun Balasubramanian, Kevin Houck, Mohammed Danish Shaikh, Shivaram Venkataraman, Aditya Akella |
| 2021 | CoNEXT | Doing more by doing less: how structured partial backpropagation improves deep learning clusters. | Adarsh Kumar, Kausik Subramanian, Shivaram Venkataraman, Aditya Akella |
| 2021 | NSDI | Move Fast and Meet Deadlines: Fine-grained Real-time Stream Processing with Cameo. | Le Xu, Shivaram Venkataraman, Indranil Gupta, Luo Mai, Rahul Potharaju |
| 2021 | OSDI | Marius: Learning Massive Graph Embeddings on a Single Machine. | Jason Mohoney, Roger Waleffe, Henry Xu, Theodoros Rekatsinas, Shivaram Venkataraman |
| 2021 | SC | KAISA: an adaptive second-order optimizer framework for deep neural networks. | J. Gregory Pauloski, Qi Huang, Lei Huang, Shivaram Venkataraman, Kyle Chard, Ian T. Foster, Zhao Zhang |
| 2020 | CLOUD | Serverless linear algebra. | Vaishaal Shankar, Karl Krauth, Kailas Vodrahalli, Qifan Pu, Benjamin Recht, Ion Stoica, Jonathan Ragan-Kelley, Eric Jonas, Shivaram Venkataraman |
| 2020 | NSDI | Themis: Fair and Efficient GPU Cluster Scheduling. | Kshiteej Mahajan, Arjun Balasubramanian, Arjun Singhvi, Shivaram Venkataraman, Aditya Akella, Amar Phanishayee, Shuchi Chawla |
| 2019 | CIDR | Serverless Event-Stream Processing over Virtual Actors. | Philip A. Bernstein, Todd Porter, Rahul Potharaju, Alejandro Z. Tomsic, Shivaram Venkataraman, Wentao Wu |
| 2019 | MOBICOM | Cracking open the DNN black-box: Video Analytics with DNNs across the Camera-Cloud Boundary. | John Emmons, Sadjad Fouladi, Ganesh Ananthanarayanan, Shivaram Venkataraman, Silvio Savarese, Keith Winstein |
| 2019 | NSDI | Shuffling, Fast and Slow: Scalable Analytics on Serverless Infrastructure. | Qifan Pu, Shivaram Venkataraman, Ion Stoica |
| 2019 | USENIX | Analysis of Large-Scale Multi-Tenant GPU Clusters for DNN Training Workloads. | Myeongjae Jeon, Shivaram Venkataraman, Amar Phanishayee, Junjie Qian, Wencong Xiao, Fan Yang |
| 2019 | SOSP | Parity models: erasure-coded resilience for prediction serving systems. | Jack Kosaian, K. V. Rashmi, Shivaram Venkataraman |
| 2018 | OSDI | Focus: Querying Large Video Datasets with Low Latency and Low Cost. | Kevin Hsieh, Ganesh Ananthanarayanan, Peter Bodk, Shivaram Venkataraman, Paramvir Bahl, Matthai Philipose, Phillip B. Gibbons, Onur Mutlu |
| 2018 | OSDI | ASAP: Fast, Approximate Graph Pattern Mining at Scale. | Anand Padmanabha Iyer, Zaoxing Liu, Xin Jin, Shivaram Venkataraman, Vladimir Braverman, Ion Stoica |
| 2017 | CLOUD | Occupy the cloud: distributed computing for the 99%. | Eric Jonas, Qifan Pu, Shivaram Venkataraman, Ion Stoica, Benjamin Recht |
| 2017 | ICDE | KeystoneML: Optimizing Pipelines for Large-Scale Advanced Analytics. | Evan Randall Sparks, Shivaram Venkataraman, Tomer Kaftan, Michael J. Franklin, Benjamin Recht |
| 2017 | ICML | Breaking Locality Accelerates Block Gauss-Seidel. | Stephen Tu, Shivaram Venkataraman, Ashia C. Wilson, Alex Gittens, Michael I. Jordan, Benjamin Recht |
| 2017 | NSDI | CherryPick: Adaptively Unearthing the Best Cloud Configurations for Big Data Analytics. | Omid Alipourfard, Hongqiang Harry Liu, Jianshu Chen, Shivaram Venkataraman, Minlan Yu, Ming Zhang |
| 2017 | SOSP | Drizzle: Fast and Adaptable Stream Processing at Scale. | Shivaram Venkataraman, Aurojit Panda, Kay Ousterhout, Michael Armbrust, Ali Ghodsi, Michael J. Franklin, Benjamin Recht, Ion Stoica |
| 2016 | KDD | Matrix Computations and Optimization in Apache Spark. | Reza Bosagh Zadeh, Xiangrui Meng, Alexander Ulanov, Burak Yavuz, Li Pu, Shivaram Venkataraman, Evan Randall Sparks, Aaron Staple, Matei Zaharia |
| 2016 | NSDI | Ernest: Efficient Performance Prediction for Large-Scale Advanced Analytics. | Shivaram Venkataraman, Zongheng Yang, Michael J. Franklin, Benjamin Recht, Ion Stoica |
| 2016 | SIGMOD | SparkR: Scaling R Programs with Spark. | Shivaram Venkataraman, Zongheng Yang, Davies Liu, Eric Liang, Hossein Falaki, Xiangrui Meng, Reynold Xin, Ali Ghodsi, Michael J. Franklin, Ion Stoica, Matei Zaharia |
| 2014 | OSDI | The Power of Choice in Data-Aware Cluster Scheduling. | Shivaram Venkataraman, Aurojit Panda, Ganesh Ananthanarayanan, Michael J. Franklin, Ion Stoica |
| 2014 | VLDB | Record Placement Based on Data Skew Using Solid State Drives. | Jun Suzuki, Shivaram Venkataraman, Sameer Agarwal, Michael J. Franklin, Ion Stoica |
| 2013 | EuroSys | Presto: distributed machine learning and graph processing with sparse matrices. | Shivaram Venkataraman, Erik Bodzsar, Indrajit Roy, Alvin AuYoung, Robert S. Schreiber |
| 2013 | HotOS | The Case for Tiny Tasks in Compute Clusters. | Kay Ousterhout, Aurojit Panda, Josh Rosen, Shivaram Venkataraman, Reynold Xin, Sylvia Ratnasamy, Scott Shenker, Ion Stoica |
| 2013 | SIGMOD | PBS at work: advancing data management with consistency metrics. | Peter Bailis, Shivaram Venkataraman, Michael J. Franklin, Joseph M. Hellerstein, Ion Stoica |
| 2012 | CLOUD | Cake: enabling high-level SLOs on shared storage systems. | Andrew Wang, Shivaram Venkataraman, Sara Alspaugh, Randy H. Katz, Ion Stoica |
| 2011 | FAST | Consistent and Durable Data Structures for Non-Volatile Byte-Addressable Memory. | Shivaram Venkataraman, Niraj Tolia, Parthasarathy Ranganathan, Roy H. Campbell |
| 2010 | ACSAC | Forenscope: a framework for live forensics. | Ellick Chan, Shivaram Venkataraman, Francis M. David, Amey Chaugule, Roy H. Campbell |
| 2010 | CEC | Scaling eCGA model building via data-intensive computing. | Abhishek Verma, Xavier Llor, Shivaram Venkataraman, David E. Goldberg, Roy H. Campbell |