Xulong Tang

Welcome! I am an associate professor in the Department of Computer Science at the University of Pittsburgh. My research spans computer architecture and systems, with a focus on multi-GPU architectures, high-performance LLM infrastructure and systems, edge AI, and quantum systems. I received my Ph.D. from Penn State and Master from USTC.

Contact: 210 S. Bouquet Street, SENSQ 6115. Department of Computer Science, University of Pittsburgh, Pittsburgh, PA, 15213
Email: tax6 AT pitt DOT edu

Curriculum Vitae

Google Scholar

DBLP

I am looking for two self-motivated and talented students to join my research group in 2026 Fall. If you are interested, please send me a brief email with your CV.

Activities

Pinned. Serving ASPLOS 2026 General Co-Chairs with Dr.Vijaykrishnan Narayanan from Penn State.
05/2025. Promoted to Associate Professor with Tenure from Sep 1st 2025 :-)
06/2025. One paper accepted ICCAD 2025.
05/2025. One paper accepted ICML 2025.
04/2025. Congrats to Bingyao Li, who will join CSE@UCRiverside as a Tenure-Track Assistant Professor!
04/2025. Congrats to Yue Dai, who will join CS@IIT as a Tenure-Track Assistant Professor!

Current Students

Sheng Li,(Ph.D. candidate)
Yueqi Wang, (Ph.D. candidate)
Yingheng Li, (Ph.D. candidate)
Haoqing Yang, (Ph.D. candidate)
Ziwei Quan, (Ph.D. candidate)

Selected Publications (full list)

(ICML 2025) MemFreezing: A Novel Adversarial Attack on Temporal Graph Neural Networks under Limited Future Knowledge.

(ICS 2025) CCExplorer: Microarchitecture-Aware Exploration for Tightly Integrated In-Pipeline Complex Custom Instruction.

(ISCA 2025) Reinforcement Learning-Guided Graph State Generation in Photonic Quantum Computers.

(MLSys 2025) FastTree: Optimizing Attention Kernel and Runtime for Tree-Structured LLM Inference.

(ASPLOS 2025) Cascade: A Dependency-aware Efficient Training Framework for Temporal Graph Neural Network.

(ASPLOS 2025) Pruner: A Draft-then-Verify Exploration Mechanism to Accelerate Tensor Program Tuning.

(ICLR 2025) Mutual Effort for Efficiency: A Similarity-based Token Pruning for Vision Transformers in Self-Supervised Learning.

(HPCA 2025) OASIS: Object-Aware Page Management for Multi-GPU Systems.

(MICRO 2024) STAR: Sub-Entry Sharing-Aware TLB for Multi-Instance GPU.

(ASPLOS 2024) FMCC: Flexible Measurement-based Quantum Computation over Cluster State.

(ASPLOS 2024) QRCC: Evaluating Large Quantum Circuits on Small Quantum Computers through Integrated Qubit Reuse and Circuit Cutting.

(DAC 2024) FCM: Wire Cutting For Fusion Reduction in Measurement-based Quantum Computing.

(DAC 2024) Lotus: learning-based online thermal and latency variation management for two-stage detectors on edge devices.

(ICLR 2024) Waxing-and-Waning: a Generic Similarity-based Framework for Efficient Self-Supervised Learning.

(HPCA 2024) GRIT: Enhancing Multi-GPU Performance with Fine-Grained Dynamic Page Placement.

(MICRO 2023) IDYLL: Enhancing Page Translation in Multi-GPUs via Light Weight PTE Invalidations.

(MICRO 2023) SupeRBNN: Randomized Binary Neural Network Using Adiabatic Superconductor Josephson Devices.

(DAC 2023) Orchestrating Measurement-Based Quantum Computation over Photonic Quantum Processors.

(DAC 2023) Orchestrated Scheduling and Partitioning for Improved Address Translation in GPUs.

(DAC 2023) EP-ORAM: Efficient NVM-Friendly Path Eviction for Ring ORAM in Hybrid Memory.

(ICLR 2023 Spotlight) SmartFRZ: An Efficient Training Framework using Attention-Based Layer Freezing.

(HPCA 2023) Trans-FW: Short Circuiting Page Table Walk in Multi-GPU Systems via Remote Forwarding.

(HPCA 2023) CEGMA: Coordinated Elastic Graph Matching Acceleration for Graph Matching Networks.

(HPCA 2023) AB-ORAM: Constructing Adjustable Buckets for Space Reduction in Ring ORAM.

(NeurIPS 2022) Layer Freezing & Data Sieving: Missing Pieces of a Generic Framework for Sparse Training.

(ECCV 2022) You Already Have It: A Generator-Free Low-Precision DNN Training Framework using Stochastic Rounding.

(HPCA 2022) Q-GPU: A Recipe of Optimizations for Quantum Circuit Simulation Using GPUs.

(MICRO 2021) Improving Address Translation in Multi-GPUs via Sharing and Spilling Aware TLB Design.

(SIGMETRICS 2021) Mix and Match: Reorganizing Tasks for Enhancing Data Locality.

(PLDI 2021) Fluid: A Framework for Approximate Concurrency via Controlled Dependency Relaxation.

(PLDI 2021) Distance-in-Time versus Distance-in-Space.

(AAAI 2021) YOLObile: Real-Time Object Detection on Mobile Devices via Compression-Compilation Co-Design.

(PPoPP 2021) Compiler Support for Near Data Computing .

(ISCA 2019) Opportunistic Computing in GPU Architectures.

(PLDI 2019) Co-Optimizing Memory-Level Parallelism and Cache-Level Parallelism.

(SIGMETRICS 2019) Architecture-Aware Approximate Computing.

(SIGMETRICS 2019) Quantifying Data Locality in Dynamic Parallelism in GPUs.

(SIGMETRICS 2019) Computing with Near Data.

(PLDI 2018) Enhancing Computation-to-Core Assignment with Physical Location Information.

(MICRO 2017) Data Movement Aware Computation Partitioning.

(HPCA 2017) Controlled Kernel Launch for Dynamic Parallelism in GPUs.

(MICRO 2016) Improving Bank-Level Parallelism for Irregular Applications.

(PLDI 2015) Optimizing Off-Chip Accesses in Manycores.

(SIGMETRICS 2015) Memory Row Reuse Distance and its Role in Optimizing Application Performance.

Prior Students

Bingyao Li, (Ph.D. candidate, Next Move: TTAP in CSE@UCRiverside)
Yue Dai, (Ph.D. candidate, co-advise with Dr.Youtao Zhang, Next Move: TTAP in CS@IIT)
Tianao Ge, (Visiting Scholar from HKUST (GZ). Advisor: Dr.Hongyuan Liu)
Mehrnoosh Raoufi, (Ph.D, co-advise with Dr.Youtao Zhang), Next Move: Oracle
Zhongxuan Song (Master)
Weizheng Xu (Master)
Zachary Michael Smith (Master)
Thomas Matthew Dicarlo (Master)
Antony Paul (Master)
Yuan Yao (Master, Next move: Bloomberg LP)
Ziyu Zhang (Master, Next move: Apple)
Yilun Zhao (Ph.D. candidate, Next move: Ph.D.@ICT-CAS)
Qi Xue (Undergrad, Next move: MS at UPenn)

Updated 11/2025