Journal Articles
- Sultan Mahmud Sajal, Timothy Zhu, Bhuvan Urgaonkar, Siddhartha Sen, Salman Estyak and Rubaba Hasan, 2025, "TraceScaler: A Framework for Scaling Load in Real-World Traces for System Evaluation", ACM Transactions on Computer Systems, 43, (4)
- Timothy Zhu, Adithya Kumar and Anand Sivasubramaniam, 2023, "SplitRPC: A {Control + Data} Path Splitting RPC Stack for ML Inference Serving", Proceedings of the ACM on Measurement and Analysis of Computing Systems (POMACS), 7, (2)
Conference Proceedings
- Timothy Zhu, Lexiang Huang, Anjaly Parayil, Jue Zhang, Xiaoting Qin, Chetan Bansal, Jovan Stojkovic, Pantea Zardoshti, Pulkit Misra, Eli Cortez, Raphael Ghelman, Íñigo Goiri, Saravan Rajmohan, Jim Kleewein, Rodrigo Fonseca and Ricardo Bianchini, 2025, "Workload Intelligence: Workload-Aware IaaS abstraction for Cloud Efficiency", ACM, New York, NY, USA
- Timothy Zhu, Lexiang Huang, Anjaly Parayil, Jue Zhang, Xiaoting Qin, Íñigo Goiri and Chetan Bansal, 2025, "Towards Workload-aware Cloud Efficiency: A Large-scale Empirical Study of Cloud Workload Characteristics", ACM, New York, NY, USA
- Timothy Zhu, Rubaba Hasan and Bhuvan Urgaonkar, 2024, "AutoBurst: Autoscaling Burstable Instances for Cost-effective Latency SLOs", ACM, New York, NY, USA
- Timothy Zhu, Vishwas Vasudeva Kakrannaya, Anand Sivasubramaniam and Siddhartha Balakrishna Rai, 2024, "Fast and Accurate DNN Performance Estimation across Diverse Hardware Platforms", IEEE
- Sultan Mahmud Sajal, Timothy Zhu, Bhuvan Urgaonkar and Siddhartha Sen, 2024, "TraceUpscaler: Upscaling Traces to Evaluate Systems at High Load", ACM, New York, NY, USA
- Sultan Mahmud Sajal, Luke Marshall, Beibin Li, Shandan Zhou, Abhisek Pan, Konstantina Mellou, Deepak Narayanan, Timothy Zhu, David Dion, Thomas Moscibroda and Ishai Menache, 2023, "Kerveros: Efficient and Scalable Cloud Admission Control", USENIX, USA
- Timothy Zhu, Adithya Kumar and Anand Sivasubramaniam, 2023, "SplitRPC: A {Control + Data} Path Splitting RPC Stack for ML Inference Serving", ACM, New York, NY, USA
- Lexiang Huang, Matthew Magnusson, Abishek Bangalore Muralikrishna, Salman Estyak, Rebecca Isaacs, Abutalib Aghayev, Timothy Zhu and Aleksey Charapko, 2022, "Metastable Failures in the Wild", USENIX, USA
- Timothy Zhu, Adithya Kumar and Anand Sivasubramaniam, 2022, "Overflowing Emerging Neural Network Inference Tasks from the GPU to the CPU on Heterogeneous Servers", ACM, New York, NY, USA
- Timothy Zhu and Lexiang Huang, 2021, "tprof: Performance profiling via structural aggregation and automated analysis of distributed systems traces", ACM, New York, NY, USA
- Nathan Bronson, Timothy Zhu, Abutalib Aghayev and Aleksey Charapko, 2021, "Metastable Failures in Distributed Systems", ACM, New York, NY, USA, pp. 221–227
- Sultan Mahmud Sajal, Timothy Zhu, Rubaba Hasan, Bhuvan Urgaonkar and Siddhartha Sen, 2021, "TraceSplitter: A New Paradigm for Downscaling Traces", ACM, New York, NY, USA
- Esmail Asyabi, Azer Bestavros, Timothy Zhu and Erfan Sharafzadeh, 2020, "Peafowl: In-application CPU scheduling to reduce power consumption of in-memory key-value stores", ACM, New York, NY, USA
- Adithya Kumar, Iyswarya Narayanan, Timothy Zhu and Anand Sivasubramaniam, 2020, "The Fast and The Frugal: Tail Latency Aware Provisioning for Coping with Load Variations", ACM, New York, NY, USA
- Ataollah Fatahi Baarzi, Timothy Zhu and Bhuvan Urgaonkar, 2019, "BurScale: Using Burstable Instances for Improving the Cost-Efficacy of Autoscaling in the Public Cloud", ACM, New York, NY, USA, pp. 126–138
- Daniel S. Berger, Benjamin Berg, Timothy Zhu, Siddhartha Sen and Mor Harchol-Balter, 2018, "RobinHood: Tail Latency Aware Caching - Dynamic Reallocation from Cache-Rich to Cache-Poor", USENIX, USA, pp. 195--212
- Timothy Zhu, Michael A. Kozuch and Mor Harchol-Balter, 2017, "WorkloadCompactor: Reducing Datacenter Cost While Providing Tail Latency SLO Guarantees", ACM, New York, NY, USA, pp. 598–610
- Timothy Zhu, Daniel S. Berger and Mor Harchol-Balter, 2016, "SNC-Meister: Admitting More Tenants with Tail Latency SLOs", ACM, New York, NY, USA, pp. 374–387
- Alexey Tumanov, Timothy Zhu, Jun Woo Park, Michael A. Kozuch, Mor Harchol-Balter and Gregory R. Ganger, 2016, "TetriSched: Global Rescheduling with Adaptive Plan-ahead in Dynamic Heterogeneous Clusters", ACM, New York, NY, USA, pp. 35:1–35:16
- Timothy Zhu, Alexey Tumanov, Michael A. Kozuch, Mor Harchol-Balter and Gregory R. Ganger, 2014, "PriorityMeister: Tail Latency QoS for Shared Networked Storage", ACM, New York, NY, USA, pp. 29:1–29:14
- Eno Thereska, Hitesh Ballani, Greg O’Shea, Thomas Karagiannis, Antony Rowstron, Tom Talpey, Richard Black and Timothy Zhu, 2013, "IOFlow: A Software-defined Storage Architecture", ACM, New York, NY, USA, pp. 182–196
- Anshul Gandhi, Timothy Zhu, Mor Harchol-Balter and Michael A. Kozuch, 2012, "SOFTScale: Stealing Opportunistically for Transient Scaling", Springer-Verlag New York, Inc., New York, NY, USA, pp. 142–163
- Timothy Zhu, Anshul Gandhi, Mor Harchol-Balter and Michael A. Kozuch, 2012, "Saving Cash by Using Less Cache", USENIX Association, Berkeley, CA, USA, pp. 3–3
