Xulong Tang

Welcome! I am an assistant professor in the Department of Computer Science at the University of Pittsburgh. I received my Ph.D. from Penn State, where I worked with my advisors Dr. Mahmut T. Kandemir and Dr. Chita R. Das on high-performance computing and advanced computer architectures. 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 LinkedIn

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Activities

• 02/2025. One paper accepted MLSys 2025.

• 01/2025. Two papers accepted ASPLOS 2025.

• 01/2025. One paper accepted ICLR 2025.

• 11/2024. One paper accepted HPCA 2025.

• 09/2024. Serving IEEE Micro Top Picks 2025 vice program chair.

• 07/2024. Serving ASPLOS 2025 publication chair.

• 07/2024. One paper accepted MICRO 2024.

• 05/2024. Two papers accepted ASPLOS 2024 (will be presented at ASPLOS 2025).

Current Students

• Bingyao Li, (Ph.D. candidate, on the job market) 🔥

• Yue Dai, (Ph.D. candidate, co-advise with Dr.Youtao Zhang, on the job market) 🔥

• Sheng Li,(Ph.D. candidate)

• Yueqi Wang, (Ph.D. candidate)

• Tianyu Wang, (Ph.D. candidate)

• Yingheng Li, (Ph.D. candidate)

• Rongchao Dong, (Ph.D. candidate)

• Haoqing Yang, (Ph.D. candidate)

• Ziwei Quan, (Ph.D. candidate)

Selected Publications (full list)

• (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

• 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 02/2025