Yufei Ding
Associate Professor
Builds programming systems and GPU-optimized libraries, with work on compilers for machine learning and quantum computing.
Yufei Ding's lab at UCSD works on compilers & programming languages and quantum computing. 55 papers since 2023, 44 at top venues, mostly ISCA and ASPLOS. 8 PhD students and 4 master's students. 15 alumni. Applications close .
At a glance
- papers, 2023–2026
- 14/ year
- at T1 venues
- 80%
- PhD students
- 8
- MS students
- 4
- alumni listed
- 15
Papers by yearfrom the lab homepage, 2023–2026
- 15 papers2026 · T1 12 · collecting
- 19 papers2025 · T1 17
- 9 papers2024 · T1 7
- 12 papers2023 · T1 8
T1 venuesOtherVenues: ISCA, ASPLOS, MICRO, NeurIPS, OSDI
Research focuspaper titles that use each topic's words
- Quantum computing18 papers
- quantum16 papers
- Compilers & programming languages0 papers
- libraries0 papers
- compilers0 papers
Paper list
From the lab homepage.
202615 papers
- MICRO (T1)AMMA: A Multi-Chiplet Memory-Centric Architecture for Low-Latency 1M Context Attention Serving (opens in a new tab)
- NeurIPS (T1)AsymHP: Load-Balanced Sparse Attention for Video Diffusion Transformers
- NeurIPS (T1)FlashEvolve: Accelerating Agent Self-Evolution with Asynchronous Stage Orchestration (opens in a new tab)
- ASPLOS (T1)iSwitch: QEC on Demand via In-Situ Encoding of Bare Qubits for Ion Trap Architectures (opens in a new tab)
- ISCA (T1)Patterns behind Chaos: Forecasting Data Movement for Efficient Large-Scale MoE LLM Inference (opens in a new tab)
- CGOProton: Towards Multi-level, Adaptive Profiling for Triton (opens in a new tab)
- NeurIPS (T1)Qubrio: High-Performance Quantum Compilation via Multi-Agent LLM Collaboration (opens in a new tab)
- TACORecDM: Efficient Training System for Large-Scale Recommendation Models on Disaggregated Memory
- ISCA (T1)Reducing Page Faults via Invalidation-based Mapping Propagation in Multi-GPU Systems
- ICML (T1)ScaleSim: Serving Large-Scale Multi-Agent Simulation with Invocation Distance-Based Memory Management (opens in a new tab)
- HPCA (T1)SFD: Towards Segment Fusion Dataflowfor Spatial Accelerators (opens in a new tab)
- TQCSTQS: A Unified System Architecture for Spatial Temporal Quantum Sensing (opens in a new tab)
202519 papers
- ISCA (T1)CaliQEC: In-situ Qubit Calibration for Surface Code Quantum Error Correction (opens in a new tab)
- MLSys (T1)FastTree: Optimizing Attention Kernel and Runtime for Tree-Structured Large Language Model Inference (opens in a new tab)
- USENIX ATCGMI-DRL: Empowering Multi-GPU Deep Reinforcement Learning with Adaptive-Grained Parallelism (opens in a new tab)
- ISCA (T1)Hardware-aware Calibration Protocol for Quantum Computers (opens in a new tab)
- SOSP (T1)HedraRAG: Co-Optimizing Generation and Retrieval for Heterogeneous Retrieval-Augmented Generation Workflows (opens in a new tab)
- ASPLOS (T1)HetEC: Architectures for Heterogeneous Quantum Error Correction Codes (opens in a new tab)
- OSDI (T1)KPerfIR: Towards a Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads (opens in a new tab)
- NeurIPS (T1)KVFlow: Efficient Prefix Caching for Accelerating LLM-based Multi-Agent Workflows (opens in a new tab)
- SOSP (T1)Mercury: Unlocking Multi-GPU Operator Optimization for Large Language Models via Remote Memory Scheduling (opens in a new tab)
- ICLR (T1)Mutual Effort for Efficiency: A Similarity-based Token Pruning for Vision Transformers in Self-Supervised Learning (opens in a new tab)
- MICRO (T1)OneAdapt: Resource-adaptive Compilation of Photonic One-way Quantum Computing (opens in a new tab)
- ASPLOS (T1)PowerMove: Optimizing Compilation for Neutral Atom Quantum Computers with Zoned Architecture (opens in a new tab)
20249 papers
- ASPLOS (T1)EVT: Accelerating Deep Learning Training with Epilogue Visitor Tree (opens in a new tab)
- ASPLOS (T1)MECH: Multi-Entry Communication Highway for Superconducting Quantum Chiplets (opens in a new tab)
- ASPLOS (T1)OnePerc: A Randomness-aware Compiler for Photonic Quantum Computing (opens in a new tab)
- USENIX ATCOPER: Optimality-Guided Embedding Table Parallelization for Large-scale Recommendation Model (opens in a new tab)
- ASPLOS (T1)RAP: Resource-aware Automated GPU Sharing for Multi-GPU Recommendation Model Training and Input Preprocessing (opens in a new tab)
- SCRecFlex: Enabling Feature Heterogeneity-Aware Optimization for Deep Recommendation Models with Flexible Schedules (opens in a new tab)
- ISCA (T1)Soter: Analytical Tensor-Architecture Modeling and Automatic Tensor Program Tuning for Spatial Accelerators (opens in a new tab)
- MICRO (T1)Surf-Deformer: Mitigating Dynamic Defects on Surface Code via Adaptive Deformation (opens in a new tab)
- ASPLOS (T1)ZENO: A Type-based Optimization Framework for Zero Knowledge Neural Network Inference (opens in a new tab)
202312 papers
- MLSys (T1)ALCOP: Automatic Load-Compute Pipelining in Deep Learning Compiler for AI-GPUs (opens in a new tab)
- PPoPPDynamic N:M Fine-grained Structured Sparse Attention Mechanism (opens in a new tab)
- ISCA (T1)ECSSD: Hardware/Data Layout Co-Designed In-Storage-Computing Architecture for Extreme Classification (opens in a new tab)
- OSDI (T1)MGG: Accelerating Graph Neural Networks with Fine-grained intra-kernel Communication-Computation Pipelining on Multi-GPU Platforms (opens in a new tab)
- TACOMPU: Memory-Centric SIMT Processor via In-DRAM Near-Bank Computing (opens in a new tab)
- ISCA (T1)OneQ: A Compilation Framework for Photonic One-Way Quantum Computation (opens in a new tab)
- ISCA (T1)Q-BEEP: Quantum Bayesian Error Mitigation Employing Poisson Modeling over the Hamming Spectrum (opens in a new tab)
- MICRO (T1)QuComm: Optimizing Collective Communication for Distributed Quantum Computing (opens in a new tab)
- MICRO (T1)RM-STC: Row-Merge Dataflow Inspired GPU Sparse Tensor Core for Energy-Efficient Sparse Acceleration (opens in a new tab)
- VLDB (T1)SPG: Structure-Private Graph Database via SqueezePIR (opens in a new tab)
- USENIX ATCTC-GNN: Bridging Sparse GNN Computation and Dense Tensor Cores on GPUs (opens in a new tab)
- JSSCTranCIM: Full-Digital Bitline-Transpose CIM-based Sparse Transformer Accelerator with Pipeline/Parallel Reconfigurable Modes (opens in a new tab)
Where alumni went15 listed, 0% to industry
Industry 0Academia 4
Also to
- Rice University
- Shanghai Jiao Tong University
- University of Pennsylvania
Apply to UCSDFall 2027
UCSD CSE Computer Science PhD
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