Accelerating Volume Image Registration through Correlation Ratio Based Methods on GPUs. - Ang Li 006; Akash Kumar 001 (DSD, 2014)

A heterogeneous platform with GPU and FPGA for power efficient high performance computing. - Qiang Wu; Yajun Ha; Akash Kumar 001; Shaobo Luo; Ang Li 006; Shihab Mohamed (ISIC, 2014)

Accelerating non-volatile/hybrid processor cache design space exploration for application specific embedded systems. - Mohammad Shihabul Haque; Ang Li 006; Akash Kumar 001; Qingsong Wei (ASP-DAC, 2015)

A Locality Aware Convolutional Neural Networks Accelerator. - Runbin Shi; Zheng Xu; Zhihao Sun; Maurice Peemen; Ang Li 006; Henk Corporaal; Di Wu (DSD, 2015)

Transit: A Visual Analytical Model for Multithreaded Machines. - Ang Li 006; Y. C. Tay; Akash Kumar 001; Henk Corporaal (HPDC, 2015)

Fine-Grained Synchronizations and Dataflow Programming on GPUs. - Ang Li 006; Gert-Jan van den Braak; Henk Corporaal; Akash Kumar 001 (ICS, 2015)

Adaptive and transparent cache bypassing for GPUs. - Ang Li 006; Gert-Jan van den Braak; Akash Kumar 001; Henk Corporaal (SC, 2015)

Correlation ratio based volume image registration on GPUs. - Ang Li 006; Akash Kumar 001; Yajun Ha; Henk Corporaal (Microprocess. Microsystems, 2015)

Critical points based register-concurrency autotuning for GPUs. - Ang Li 006; Shuaiwen Leon Song; Akash Kumar 001; Eddy Z. Zhang; Daniel G. Chavarría-Miranda; Henk Corporaal (DATE, 2016)

A Synchronization-Free Algorithm for Parallel Sparse Triangular Solves. - Weifeng Liu 002; Ang Li 006; Jonathan D. Hogg; Iain S. Duff; Brian Vinter (Euro-Par, 2016)

SFU-Driven Transparent Approximation Acceleration on GPUs. - Ang Li 006; Shuaiwen Leon Song; Mark Wijtvliet; Akash Kumar 001; Henk Corporaal (ICS, 2016)

X: A Comprehensive Analytic Model for Parallel Machines. - Ang Li 006; Shuaiwen Leon Song; Eric Brugel; Akash Kumar 001; Daniel G. Chavarría-Miranda; Henk Corporaal (IPDPS, 2016)

Analysis and design of energy-efficient data-dependent SRAM. - Wenfeng Zhao; Ang Li 006; Yi Wang 016; Yajun Ha (ASICON, 2017)

Locality-Aware CTA Clustering for Modern GPUs. - Ang Li 006; Shuaiwen Leon Song; Weifeng Liu 002; Xu Liu 001; Akash Kumar 001; Henk Corporaal (ASPLOS, 2017)

BVF: enabling significant on-chip power savings via bit-value-favor for throughput processors. - Ang Li 006; Wenfeng Zhao; Shuaiwen Leon Song (MICRO, 2017)

Exploring and analyzing the real impact of modern on-package memory on HPC scientific kernels. - Ang Li 006; Weifeng Liu 002; Mads Ruben Burgdorff Kristensen; Brian Vinter; Hao Wang 002; Kaixi Hou; Andres Marquez 001; Shuaiwen Leon Song (SC, 2017)

Fast synchronization-free algorithms for parallel sparse triangular solves with multiple right-hand sides. - Weifeng Liu 002; Ang Li 006; Jonathan D. Hogg; Iain S. Duff; Brian Vinter (Concurr. Comput. Pract. Exp., 2017)

CUDAAdvisor: LLVM-based runtime profiling for modern GPUs. - Du Shen; Shuaiwen Leon Song; Ang Li 006; Xu Liu 001 (CGO, 2018)

Warp-Consolidation: A Novel Execution Model for GPUs. - Ang Li 006; Weifeng Liu 002; Linnan Wang; Kevin J. Barker; Shuaiwen Leon Song (ICS, 2018)

Tartan: Evaluating Modern GPU Interconnect via a Multi-GPU Benchmark Suite. - Ang Li 006; Shuaiwen Leon Song; Jieyang Chen; Xu Liu 001; Nathan R. Tallent; Kevin J. Barker (IISWC, 2018)

Introduction to HPPAC 2018. - Shuaiwen Leon Song; Natalie J. Bates; Ang Li 006 (IPDPS Workshops, 2018)

Superneurons: dynamic GPU memory management for training deep neural networks. - Linnan Wang; Jinmian Ye; Yiyang Zhao; Wei Wu 016; Ang Li 006; Shuaiwen Leon Song; Zenglin Xu; Tim Kraska (PPoPP, 2018)

LP-BNN: Ultra-low-Latency BNN Inference with Layer Parallelism. - Tong Geng; Tianqi Wang; Chunshu Wu; Chen Yang 010; Shuaiwen Leon Song; Ang Li 006; Martin C. Herbordt (ASAP, 2019)

PIM-VR: Erasing Motion Anomalies In Highly-Interactive Virtual Reality World with Customized Memory Cube. - Chenhao Xie 001; Xingyao Zhang; Ang Li 006; Xin Fu; Shuaiwen Song (HPCA, 2019)

O3BNN: an out-of-order architecture for high-performance binarized neural network inference with fine-grained pruning. - Tong Geng; Tianqi Wang; Chunshu Wu; Chen Yang 010; Wei Wu 016; Ang Li 006; Martin C. Herbordt (ICS, 2019)

Fingerprinting Anomalous Computation with RNN for GPU-accelerated HPC Machines. - Pengfei Zou; Ang Li 006; Kevin J. Barker; Rong Ge 002 (IISWC, 2019)

BSTC: a novel binarized-soft-tensor-core design for accelerating bit-based approximated neural nets. - Ang Li 006; Tong Geng; Tianqi Wang; Martin C. Herbordt; Shuaiwen Leon Song; Kevin J. Barker (SC, 2019)

PASTA: a parallel sparse tensor algorithm benchmark suite. - Jiajia Li 001; Yuchen Ma 001; Xiaolong Wu; Ang Li 006; Kevin J. Barker (CCF Trans. High Perform. Comput., 2019)

A Scalable Framework for Acceleration of CNN Training on Deeply-Pipelined FPGA Clusters with Weight and Workload Balancing. - Tong Geng; Tianqi Wang; Ang Li 006; Xi Jin 002; Martin C. Herbordt (CoRR, 2019)

UWB-GCN: Hardware Acceleration of Graph-Convolution-Network through Runtime Workload Rebalancing. - Tong Geng; Ang Li 006; Tianqi Wang; Chunshu Wu; Yanfei Li; Antonino Tumeo; Martin C. Herbordt (CoRR, 2019)

Indicator-Directed Dynamic Power Management for Iterative Workloads on GPU-Accelerated Systems. - Pengfei Zou; Ang Li 006; Kevin J. Barker; Rong Ge 002 (CCGRID, 2020)

On the Feasibility of Using Reduced-Precision Tensor Core Operations for Graph Analytics. - Jesun Sahariar Firoz; Ang Li 006; Jiajia Li 001; Kevin J. Barker (HPEC, 2020)

CQNN: a CGRA-based QNN Framework. - Tong Geng; Chunshu Wu; Cheng Tan 002; Bo Fang 002; Ang Li 006; Martin C. Herbordt (HPEC, 2020)

OpenCGRA: An Open-Source Unified Framework for Modeling, Testing, and Evaluating CGRAs. - Cheng Tan 002; Chenhao Xie 001; Ang Li 006; Kevin J. Barker; Antonino Tumeo (ICCD, 2020)

Detecting Anomalous Computation with RNNs on GPU-Accelerated HPC Machines. - Pengfei Zou; Ang Li 006; Kevin J. Barker; Rong Ge 002 (ICPP, 2020)

CSB-RNN: a faster-than-realtime RNN acceleration framework with compressed structured blocks. - Runbin Shi; Peiyan Dong; Tong Geng; Yuhao Ding; Xiaolong Ma; Hayden Kwok-Hay So; Martin C. Herbordt; Ang Li 006; Yanzhi Wang (ICS, 2020)

A Sparse Tensor Benchmark Suite for CPUs and GPUs. - Jiajia Li 001; Mahesh Lakshminarasimhan; Xiaolong Wu; Ang Li 006; Catherine Olschanowsky; Kevin J. Barker (IISWC, 2020)

AWB-GCN: A Graph Convolutional Network Accelerator with Runtime Workload Rebalancing. - Tong Geng; Ang Li 006; Runbin Shi; Chunshu Wu; Tianqi Wang; Yanfei Li; Pouya Haghi; Antonino Tumeo; Shuai Che; Steven K. Reinhardt; Martin C. Herbordt (MICRO, 2020)

A parallel sparse tensor benchmark suite on CPUs and GPUs. - Jiajia Li 001; Mahesh Lakshminarasimhan; Xiaolong Wu; Ang Li 006; Catherine Olschanowsky; Kevin J. Barker (PPoPP, 2020)

Density matrix quantum circuit simulation via the BSP machine on modern GPU clusters. - Ang Li 006; Omer Subasi; Xiu Yang; Sriram Krishnamoorthy (SC, 2020)

Accelerated Deep Reinforcement Learning Based Load Shedding for Emergency Voltage Control. - Renke Huang; Yujiao Chen; Tianzhixi Yin; Xinya Li 002; Ang Li 006; Jie Tan 001; Qiuhua Huang (CoRR, 2020)

ARENA: Asynchronous Reconfigurable Accelerator Ring to Enable Data-Centric Parallel Computing. - Cheng Tan 002; Chenhao Xie 001; Andres Marquez 001; Antonino Tumeo; Kevin J. Barker; Ang Li 006 (CoRR, 2020)

FPDeep: Scalable Acceleration of CNN Training on Deeply-Pipelined FPGA Clusters. - Tianqi Wang; Tong Geng; Ang Li 006; Xi Jin 002; Martin C. Herbordt (IEEE Trans. Computers, 2020)

Evaluating Modern GPU Interconnect: PCIe, NVLink, NV-SLI, NVSwitch and GPUDirect. - Ang Li 006; Shuaiwen Leon Song; Jieyang Chen; Jiajia Li 001; Xu Liu 001; Nathan R. Tallent; Kevin J. Barker (IEEE Trans. Parallel Distributed Syst., 2020)

OpenCGRA: Democratizing Coarse-Grained Reconfigurable Arrays. - Cheng Tan 002; Nicolas Bohm Agostini; Jeff Zhang 001; Marco Minutoli; Vito Giovanni Castellana; Chenhao Xie 001; Tong Geng; Ang Li 006; Kevin J. Barker; Antonino Tumeo (ASAP, 2021)

Binary Complex Neural Network Acceleration on FPGA : (Invited Paper). - Hongwu Peng; Shanglin Zhou; Scott Weitze; Jiaxin Li; Sahidul Islam; Tong Geng; Ang Li 006; Wei Zhang; Minghu Song; Mimi Xie; Hang Liu 001; Caiwen Ding (ASAP, 2021)

Guarding Numerics Amidst Rising Heterogeneity. - Ganesh Gopalakrishnan; Ignacio Laguna; Ang Li 006; Pavel Panchekha; Cindy Rubio-González; Zachary Tatlock (Correctness@SC, 2021)

AURORA: Automated Refinement of Coarse-Grained Reconfigurable Accelerators. - Cheng Tan 002; Chenhao Xie 001; Ang Li 006; Kevin J. Barker; Antonino Tumeo (DATE, 2021)

TQEA: Temporal Quantum Error Analysis. - Betis Baheri; Daniel Chen 005; Bo Fang 002; Samuel Alexander Stein; Vipin Chaudhary; Ying Mao 001; Shuai Xu; Ang Li 006; Qiang Guan (DSN (Supplements), 2021)

A Survey: Handling Irregularities in Neural Network Acceleration with FPGAs. - Tong Geng; Chunshu Wu; Cheng Tan 002; Chenhao Xie 001; Anqi Guo; Pouya Haghi; Sarah Yuan He; Jiajia Li 001; Martin C. Herbordt; Ang Li 006 (HPEC, 2021)

FL-DISCO: Federated Generative Adversarial Network for Graph-based Molecule Drug Discovery: Special Session Paper. - Daniel Manu; Yi Sheng; Junhuan Yang; Jieren Deng; Tong Geng; Ang Li 006; Caiwen Ding; Weiwen Jiang; Lei Yang 018 (ICCAD, 2021)

Optimizing FPGA-based Accelerator Design for Large-Scale Molecular Similarity Search (Special Session Paper). - Hongwu Peng; Shiyang Chen 004; Zhepeng Wang 001; Junhuan Yang; Scott A. Weitze; Tong Geng; Ang Li 006; Jinbo Bi; Minghu Song; Weiwen Jiang; Hang Liu 001; Caiwen Ding (ICCAD, 2021)

G-CoS: GNN-Accelerator Co-Search Towards Both Better Accuracy and Efficiency. - Yongan Zhang; Haoran You; Yonggan Fu; Tong Geng; Ang Li 006; Yingyan Lin (ICCAD, 2021)

DynPaC: Coarse-Grained, Dynamic, and Partially Reconfigurable Array for Streaming Applications. - Cheng Tan 002; Tong Geng; Chenhao Xie 001; Nicolas Bohm Agostini; Jiajia Li 001; Ang Li 006; Kevin J. Barker; Antonino Tumeo (ICCD, 2021)

Fast and Scalable Sparse Triangular Solver for Multi-GPU Based HPC Architectures. - Chenhao Xie 001; Jieyang Chen; Jesun Firoz; Jiajia Li 001; Shuaiwen Leon Song; Kevin J. Barker; Mark Raugas; Ang Li 006 (ICPP, 2021)

A Hybrid System for Learning Classical Data in Quantum States. - Samuel Alexander Stein; Ryan L'Abbate; Wenrui Mu; Yue Liu; Betis Baheri; Ying Mao 001; Qiang Guan; Ang Li 006; Bo Fang 002 (IPCCC, 2021)

Accelerating Transformer-based Deep Learning Models on FPGAs using Column Balanced Block Pruning. - Hongwu Peng; Shaoyi Huang; Tong Geng; Ang Li 006; Weiwen Jiang; Hang Liu 001; Shusen Wang; Caiwen Ding (ISQED, 2021)

I-GCN: A Graph Convolutional Network Accelerator with Runtime Locality Enhancement through Islandization. - Tong Geng; Chunshu Wu; Yongan Zhang; Cheng Tan 002; Chenhao Xie 001; Haoran You; Martin C. Herbordt; Yingyan Lin; Ang Li 006 (MICRO, 2021)

QuGAN: A Quantum State Fidelity based Generative Adversarial Network. - Samuel Alexander Stein; Betis Baheri; Daniel Chen 005; Ying Mao 001; Qiang Guan; Ang Li 006; Bo Fang 002; Shuai Xu (QCE, 2021)

APNN-TC: accelerating arbitrary precision neural networks on ampere GPU tensor cores. - Boyuan Feng; Yuke Wang; Tong Geng; Ang Li 006; Yufei Ding 001 (SC, 2021)

SV-sim: scalable PGAS-based state vector simulation of quantum circuits. - Ang Li 006; Bo Fang 002; Christopher E. Granade; Guen Prawiroatmodjo; Bettina Heim; Martin Roetteler; Sriram Krishnamoorthy (SC, 2021)

Learning and Fast Adaptation for Grid Emergency Control via Deep Meta Reinforcement Learning. - Renke Huang; Yujiao Chen; Tianzhixi Yin; Qiuhua Huang; Jie Tan 001; Wenhao Yu 003; Xinya Li 002; Ang Li 006; Yan Du (CoRR, 2021)

CEAZ: Accelerating Parallel I/O via Hardware-Algorithm Co-Design of Efficient and Adaptive Lossy Compression. - Chengming Zhang 006; Sian Jin; Tong Geng; Jiannan Tian; Ang Li 006; Dingwen Tao (CoRR, 2021)

Binary Complex Neural Network Acceleration on FPGA. - Hongwu Peng; Shanglin Zhou; Scott Weitze; Jiaxin Li; Sahidul Islam; Tong Geng; Ang Li 006; Wei Zhang; Minghu Song; Mimi Xie; Hang Liu 001; Caiwen Ding (CoRR, 2021)

Optimizing FPGA-based Accelerator Design for Large-Scale Molecular Similarity Search. - Hongwu Peng; Shiyang Chen 004; Zhepeng Wang 001; Junhuan Yang; Scott A. Weitze; Tong Geng; Ang Li 006; Jinbo Bi; Minghu Song; Weiwen Jiang; Hang Liu 001; Caiwen Ding (CoRR, 2021)

O3BNN-R: An Out-of-Order Architecture for High-Performance and Regularized BNN Inference. - Tong Geng; Ang Li 006; Tianqi Wang; Chunshu Wu; Yanfei Li; Runbin Shi; Wei Wu 016; Martin C. Herbordt (IEEE Trans. Parallel Distributed Syst., 2021)

Accelerating Binarized Neural Networks via Bit-Tensor-Cores in Turing GPUs. - Ang Li 006; Simon Su (IEEE Trans. Parallel Distributed Syst., 2021)

ARENA: Asynchronous Reconfigurable Accelerator Ring to Enable Data-Centric Parallel Computing. - Cheng Tan 002; Chenhao Xie 001; Tong Geng; Andres Marquez 001; Antonino Tumeo; Kevin J. Barker; Ang Li 006 (IEEE Trans. Parallel Distributed Syst., 2021)

BCNN: Binary complex neural network. - Yanfei Li; Tong Geng; Ang Li 006; Huimin Yu (Microprocess. Microsystems, 2021)

Efficient Hierarchical State Vector Simulation of Quantum Circuits via Acyclic Graph Partitioning. - Bo Fang 002; M. Yusuf Özkaya; Ang Li 006; Ümit V. Çatalyürek; Sriram Krishnamoorthy (CLUSTER, 2022)

A length adaptive algorithm-hardware co-design of transformer on FPGA through sparse attention and dynamic pipelining. - Hongwu Peng; Shaoyi Huang; Shiyang Chen 004; Bingbing Li; Tong Geng; Ang Li 006; Weiwen Jiang; Wujie Wen; Jinbo Bi; Hang Liu 001; Caiwen Ding (DAC, 2022)

FCsN: A FPGA-Centric SmartNIC Framework for Neural Networks. - Anqi Guo; Tong Geng; Yongan Zhang; Pouya Haghi; Chunshu Wu; Cheng Tan 002; Yingyan Lin; Ang Li 006; Martin C. Herbordt (FCCM, 2022)

H-GCN: A Graph Convolutional Network Accelerator on Versal ACAP Architecture. - Chengming Zhang 006; Tong Geng; Anqi Guo; Jiannan Tian; Martin C. Herbordt; Ang Li 006; Dingwen Tao (FPL, 2022)

A Framework for Neural Network Inference on FPGA-Centric SmartNICs. - Anqi Guo; Tong Geng; Yongan Zhang; Pouya Haghi; Chunshu Wu; Cheng Tan 002; Yingyan Lin; Ang Li 006; Martin C. Herbordt (FPL, 2022)

Towards Precision-Aware Fault Tolerance Approaches for Mixed-Precision Applications. - Bo Fang 002; Siva Kumar Sastry Hari; Timothy Tsai 002; Xinyi Li; Ganesh Gopalakrishnan; Ignacio Laguna; Kevin J. Barker; Ang Li 006 (FTXS@SC, 2022)

SO(DA)2: End-to-end Generation of Specialized Reconfigurable Architectures (Invited Talk). - Antonino Tumeo; Nicolas Bohm Agostini; Serena Curzel; Ankur Limaye; Cheng Tan 002; Vinay Amatya; Marco Minutoli; Vito Giovanni Castellana; Ang Li 006; Joseph B. Manzano (PARMA-DITAM@HiPEAC, 2022)

DRIPS: Dynamic Rebalancing of Pipelined Streaming Applications on CGRAs. - Cheng Tan 002; Nicolas Bohm Agostini; Tong Geng; Chenhao Xie 001; Jiajia Li 001; Ang Li 006; Kevin J. Barker; Antonino Tumeo (HPCA, 2022)

GCoD: Graph Convolutional Network Acceleration via Dedicated Algorithm and Accelerator Co-Design. - Haoran You; Tong Geng; Yongan Zhang; Ang Li 006; Yingyan Lin (HPCA, 2022)

CEAZ: accelerating parallel I/O via hardware-algorithm co-designed adaptive lossy compression. - Chengming Zhang 006; Sian Jin; Tong Geng; Jiannan Tian; Ang Li 006; Dingwen Tao (ICS, 2022)

ASAP: automatic synthesis of area-efficient and precision-aware CGRAs. - Cheng Tan 002; Thierry Tambe; Jeff Jun Zhang; Bo Fang 002; Tong Geng; Gu-Yeon Wei; David Brooks 001; Antonino Tumeo; Ganesh Gopalakrishnan; Ang Li 006 (ICS, 2022)

QuCNN: A Quantum Convolutional Neural Network with Entanglement Based Backpropagation. - Samuel Alexander Stein; Ying Mao 001; James A. Ang; Ang Li 006 (SEC, 2022)

Quantum Noise in the Flow of Time: A Temporal Study of the Noise in Quantum Computers. - Betis Baheri; Qiang Guan; Vipin Chaudhary; Ang Li 006 (IOLTS, 2022)

MARS: Malleable Actor-Critic Reinforcement Learning Scheduler. - Betis Baheri; Jacob Tronge; Bo Fang 002; Ang Li 006; Vipin Chaudhary; Qiang Guan (IPCCC, 2022)

Bit-GraphBLAS: Bit-Level Optimizations of Matrix-Centric Graph Processing on GPU. - Jou-An Chen; Hsin-Hsuan Sung; Xipeng Shen; Nathan R. Tallent; Kevin J. Barker; Ang Li 006 (IPDPS, 2022)

International Workshop on Quantum Classical Cooperative Computing (QCCC 2022). - Ang Li 006; Qiang Guan (IPDPS Workshops, 2022)

Improving Variational Quantum Algorithms performance through Weighted Quantum Ensembles. - Samuel Alexander Stein; Nathan Wiebe; James A. Ang; Ang Li 006 (IPDPS Workshops, 2022)

Benchmarking Quantum Processor Performance through Quantum Distance Metrics Over An Algorithm Suite. - Samuel Alexander Stein; Nathan Wiebe; James A. Ang; Ang Li 006 (IPDPS Workshops, 2022)

EQC: ensembled quantum computing for variational quantum algorithms. - Samuel Alexander Stein; Nathan Wiebe; Yufei Ding 001; Bo Peng; Karol Kowalski; Nathan A. Baker; James A. Ang; Ang Li 006 (ISCA, 2022)

QuClassi: A Hybrid Deep Neural Network Architecture based on Quantum State Fidelity. - Samuel Alexander Stein; Betis Baheri; Daniel Chen 005; Ying Mao 001; Qiang Guan; Ang Li 006; Shuai Xu; Caiwen Ding (MLSys, 2022)

BNS-GCN: Efficient Full-Graph Training of Graph Convolutional Networks with Partition-Parallelism and Random Boundary Node Sampling. - Cheng Wan 005; Youjie Li; Ang Li 006; Nam Sung Kim; Yingyan Lin (MLSys, 2022)

Dissecting Tensor Cores via Microbenchmarks: Latency, Throughput and Numerical Behaviors. - Wei Sun; Ang Li 006; Tong Geng; Sander Stuijk; Henk Corporaal (CoRR, 2022)

GAAF: Searching Activation Functions for Binary Neural Networks through Genetic Algorithm. - Yanfei Li; Tong Geng; Samuel Alexander Stein; Ang Li 006; Huimin Yu (CoRR, 2022)

GMI-DRL: Empowering Multi-GPU Deep Reinforcement Learning with GPU Spatial Multiplexing. - Yuke Wang; Boyuan Feng; Zheng Wang 075; Tong Geng; Ang Li 006; Yufei Ding 001 (CoRR, 2022)

A Synergistic Compilation Workflow for Tackling Crosstalk in Quantum Machines. - Fei Hua; Yuwei Jin; Ang Li 006; Yan-Hao Chen; Chi Zhang 041; Ari B. Hayes; Hang Gao; Eddy Z. Zhang (CoRR, 2022)

CollComm: Enabling Efficient Collective Quantum Communication Based on EPR buffering. - Anbang Wu; Yufei Ding 001; Ang Li 006 (CoRR, 2022)

Empowering GNNs with Fine-grained Communication-Computation Pipelining on Multi-GPU Platforms. - Yuke Wang; Boyuan Feng; Zheng Wang 075; Tong Geng; Kevin J. Barker; Ang Li 006; Yufei Ding 001 (CoRR, 2022)

MSREP: A Fast yet Light Sparse Matrix Framework for Multi-GPU Systems. - Jieyang Chen; Chenhao Xie 001; Jesun Sahariar Firoz; Jiajia Li 001; Shuaiwen Leon Song; Kevin J. Barker; Mark Raugas; Ang Li 006 (CoRR, 2022)

Extreme Acceleration of Graph Neural Network-based Prediction Models for Quantum Chemistry. - Hatem Helal; Jesun Firoz; Jenna A. Bilbrey; Mario Michael Krell; Tom Murray; Ang Li 006; Sotiris S. Xantheas; Sutanay Choudhury (CoRR, 2022)

Ising-Traffic: Using Ising Machine Learning to Predict Traffic Congestion under Uncertainty. - Zhenyu Pan; Anshujit Sharma; Jerry Yao-Chieh Hu; Zhuo Liu; Ang Li 006; Han Liu 001; Michael C. Huang 001; Tong Geng (AAAI, 2023)

Distributed Quantum Learning with co-Management in a Multi-tenant Quantum System. - Anthony D'Onofrio Jr.; Amir Hossain; Lesther Santana; Naseem Machlovi; Samuel Alexander Stein; Jinwei Liu; Ang Li 006; Ying Mao 001 (IEEE Big Data, 2023)

Ising-CF: A Pathbreaking Collaborative Filtering Method Through Efficient Ising Machine Learning. - Zhuo Liu; Yunan Yang; Zhenyu Pan; Anshujit Sharma; Amit Hasan 001; Caiwen Ding; Ang Li 006; Michael C. Huang 001; Tong Geng (DAC, 2023)

ML-CGRA: An Integrated Compilation Framework to Enable Efficient Machine Learning Acceleration on CGRAs. - Yixuan Luo; Cheng Tan 002; Nicolas Bohm Agostini; Ang Li 006; Antonino Tumeo; Nirav Dave; Tong Geng (DAC, 2023)

A Pulse Generation Framework with Augmented Program-aware Basis Gates and Criticality Analysis. - Yan-Hao Chen; Yuwei Jin; Fei Hua; Ari B. Hayes; Ang Li 006; Yunong Shi; Eddy Z. Zhang (HPCA, 2023)

Design and Evaluation of GPU-FPX: A Low-Overhead tool for Floating-Point Exception Detection in NVIDIA GPUs. - Xinyi Li; Ignacio Laguna; Bo Fang 002; Katarzyna Swirydowicz; Ang Li 006; Ganesh Gopalakrishnan (HPDC, 2023)

AutoReP: Automatic ReLU Replacement for Fast Private Network Inference. - Hongwu Peng; Shaoyi Huang; Tong Zhou 002; Yukui Luo; Chenghong Wang; Zigeng Wang; Jiahui Zhao; Xi Xie; Ang Li 006; Tony Geng; Kaleel Mahmood; Wujie Wen; et al. (ICCV, 2023)

BitGNN: Unleashing the Performance Potential of Binary Graph Neural Networks on GPUs. - Jou-An Chen; Hsin-Hsuan Sung; Xipeng Shen; Sutanay Choudhury; Ang Li 006 (ICS, 2023)

Software-Hardware Co-design of Heterogeneous SmartNIC System for Recommendation Models Inference and Training. - Anqi Guo; Yuchen Hao; Chunshu Wu; Pouya Haghi; Zhenyu Pan; Min Si; Dingwen Tao; Ang Li 006; Martin C. Herbordt; Tong Geng (ICS, 2023)

FLASH: FPGA-Accelerated Smart Switches with GCN Case Study. - Pouya Haghi; William Krska; Cheng Tan 002; Tong Geng; Po Hao Chen 002; Connor Greenwood; Anqi Guo; Thomas M. Hines; Chunshu Wu; Ang Li 006; Anthony Skjellum; Martin C. Herbordt (ICS, 2023)

Q-BEEP: Quantum Bayesian Error Mitigation Employing Poisson Modeling over the Hamming Spectrum. - Samuel Alexander Stein; Nathan Wiebe; Yufei Ding 001; James A. Ang; Ang Li 006 (ISCA, 2023)

HetArch: Heterogeneous Microarchitectures for Superconducting Quantum Systems. - Samuel Alexander Stein; Sara Sussman; Teague Tomesh; Charles Guinn; Esin Tureci; Sophia Fuhui Lin; Wei Tang; James A. Ang; Srivatsan Chakram; Ang Li 006; Margaret Martonosi; Fred Chong; et al. (MICRO, 2023)

QuComm: Optimizing Collective Communication for Distributed Quantum Computing. - Anbang Wu; Yufei Ding 001; Ang Li 006 (MICRO, 2023)

MGG: Accelerating Graph Neural Networks with Fine-Grained Intra-Kernel Communication-Computation Pipelining on Multi-GPU Platforms. - Yuke Wang; Boyuan Feng; Zheng Wang 075; Tong Geng; Kevin J. Barker; Ang Li 006; Yufei Ding 001 (OSDI, 2023)

A Novel Spatial-Temporal Variational Quantum Circuit to Enable Deep Learning on NISQ Devices. - Jinyang Li 001; Zhepeng Wang 001; Zhirui Hu; Prasanna Date; Ang Li 006; Weiwen Jiang (QCE, 2023)

QASMTrans: A QASM Quantum Transpiler Framework for NISQ Devices. - Fei Hua; Meng Wang 033; Gushu Li; Bo Peng; Chenxu Liu; Muqing Zheng; Samuel Alexander Stein; Yufei Ding 001; Eddy Z. Zhang; Travis S. Humble; Ang Li 006 (SC Workshops, 2023)

A Reference Implementation for a Quantum Message Passing Interface. - Yue Shi; Tommy Nguyen; Samuel Alexander Stein; Tim Stavenger; Marvin Warner; Martin Roetteler; Torsten Hoefler; Ang Li 006 (SC Workshops, 2023)

Enabling Scalable VQE Simulation on Leading HPC Systems. - Meng Wang 033; Fei Hua; Chenxu Liu; Nicholas P. Bauman; Karol Kowalski; Daniel Claudino; Travis S. Humble; Prashant J. Nair; Ang Li 006 (SC Workshops, 2023)

FASDA: An FPGA-Aided, Scalable and Distributed Accelerator for Range-Limited Molecular Dynamics. - Chunshu Wu; Tong Geng; Anqi Guo; Sahan Bandara; Pouya Haghi; Chuan Liu 001; Ang Li 006; Martin C. Herbordt (SC, 2023)

MEMQSim: Highly Memory-Efficient and Modularized Quantum State-Vector Simulation. - Boyuan Zhang 002; Bo Fang 002; Qiang Guan; Ang Li 006; Dingwen Tao (SC Workshops, 2023)

Machine Learning Automated Approach for Enormous Synchrotron X-Ray Diffraction Data Interpretation. - Xiaodong Zhao; YiXuan Luo; Juejing Liu; Wenjun Liu; Kevin M. Rosso; Xiaofeng Guo; Tong Geng; Ang Li 006; Xin Zhang (CoRR, 2023)

Microarchitectures for Heterogeneous Superconducting Quantum Computers. - Samuel Alexander Stein; Sara Sussman; Teague Tomesh; Charles Guinn; Esin Tureci; Sophia Fuhui Lin; Wei Tang; James A. Ang; Srivatsan Chakram; Ang Li 006; Margaret Martonosi; Frederic T. Chong; et al. (CoRR, 2023)

Toward Intelligent Emergency Control for Large-scale Power Systems: Convergence of Learning, Physics, Computing and Control. - Qiuhua Huang; Renke Huang; Tianzhixi Yin; Sohom Datta; Xueqing Sun; Z. Jason Hou; Jie Tan 001; Wenhao Yu 003; Yuan Liu 023; Xinya Li 002; Bruce Palmer; Ang Li 006; et al. (CoRR, 2023)

MPGemmFI: A Fault Injection Technique for Mixed Precision GEMM in ML Applications. - Bo Fang 002; Xinyi Li; Harvey Dam; Cheng Tan 002; Siva Kumar Sastry Hari; Timothy Tsai 002; Ignacio Laguna; Dingwen Tao; Ganesh Gopalakrishnan; Prashant J. Nair; Kevin J. Barker; Ang Li 006 (CoRR, 2023)

Elastic Resource Management for Deep Learning Applications in a Container Cluster. - Ying Mao 001; Vaishali Sharma; Wenjia Zheng; Long Cheng 003; Qiang Guan; Ang Li 006 (IEEE Trans. Cloud Comput., 2023)

Dissecting Tensor Cores via Microbenchmarks: Latency, Throughput and Numeric Behaviors. - Wei Sun; Ang Li 006; Tong Geng; Sander Stuijk; Henk Corporaal (IEEE Trans. Parallel Distributed Syst., 2023)

Accelerating matrix-centric graph processing on GPUs through bit-level optimizations. - Jou-An Chen; Hsin-Hsuan Sung; Xipeng Shen; Nathan R. Tallent; Kevin J. Barker; Ang Li 006 (J. Parallel Distributed Comput., 2023)

Red-QAOA: Efficient Variational Optimization through Circuit Reduction. - Meng Wang 033; Bo Fang 002; Ang Li 006; Prashant J. Nair (ASPLOS (2), 2024)

RAP: Resource-aware Automated GPU Sharing for Multi-GPU Recommendation Model Training and Input Preprocessing. - Zheng Wang 075; Yuke Wang; Jiaqi Deng; Da Zheng; Ang Li 006; Yufei Ding 001 (ASPLOS (2), 2024)

FTTN: Feature-Targeted Testing for Numerical Properties of NVIDIA & AMD Matrix Accelerators. - Xinyi Li; Ang Li 006; Bo Fang 002; Katarzyna Swirydowicz; Ignacio Laguna; Ganesh Gopalakrishnan (CCGrid, 2024)

Discovery of Floating-Point Differences Between NVIDIA and AMD GPUs. - Xinyi Li; Ang Li 006; Bo Fang 002; Katarzyna Swirydowicz; Ignacio Laguna; Ganesh Gopalakrishnan (CCGrid, 2024)

Understanding Mixed Precision GEMM with MPGemmFI: Insights into Fault Resilience. - Bo Fang 002; Xinyi Li; Harvey Dam; Cheng Tan 002; Siva Kumar Sastry Hari; Timothy Tsai 002; Ignacio Laguna; Dingwen Tao; Ganesh Gopalakrishnan; Prashant J. Nair; Kevin J. Barker; Ang Li 006 (CLUSTER, 2024)

QUAPPROX: A Framework for Benchmarking the Approximability of Variational Quantum Circuit. - Jinyang Li 001; Ang Li 006; Weiwen Jiang (ICASSP, 2024)

Extending Power of Nature from Binary to Real-Valued Graph Learning in Real World. - Chunshu Wu; Ruibing Song; Chuan Liu 001; Yunan Yang; Ang Li 006; Michael C. Huang 001; Tong Geng (ICLR, 2024)

SNNPG: Using Spiking Neural Networks to Detect Attacks in the Power Grid. - Kendric Hood; Ang Li 006; Qiang Guan (ICONS, 2024)

SmartFuse: Reconfigurable Smart Switches to Accelerate Fused Collectives in HPC Applications. - Pouya Haghi; Cheng Tan 002; Anqi Guo; Chunshu Wu; Dongfang Liu; Ang Li 006; Anthony Skjellum; Tong Geng; Martin C. Herbordt (ICS, 2024)

DS-GL: Advancing Graph Learning via Harnessing Nature's Power within Scalable Dynamical Systems. - Ruibing Song; Chunshu Wu; Chuan Liu 001; Ang Li 006; Michael C. Huang 001; Tong Geng (ISCA, 2024)

NP-NDS: A Nature-Powered Nonlinear Dynamical System for Power Grid Forecasting. - Chunshu Wu; Ruibing Song; Chuan Liu 001; Yuqing Wang; Yousu Chen; Ang Li 006; Dongfang Liu; Ying Nian Wu; Michael Huang; Tong Geng (LoG, 2024)

Bridging the Gap Between LLMs and LNS with Dynamic Data Format and Architecture Codesign. - Pouya Haghi; Chunshu Wu; Zahra Azad; Yanfei Li; Andrew Gui; Yuchen Hao; Ang Li 006; Tony Tong Geng (MICRO, 2024)

Surf-Deformer: Mitigating Dynamic Defects on Surface Code via Adaptive Deformation. - Keyi Yin; Xiang Fang; Travis S. Humble; Ang Li 006; Yunong Shi; Yufei Ding 001 (MICRO, 2024)

Scalable Circuit Cutting and Scheduling in a Resource-Constrained and Distributed Quantum System. - Shuwen Kan; Zefan Du; Miguel Palma; Samuel Alexander Stein; Chenxu Liu; Wenqi Wei 001; Juntao Chen; Ang Li 006; Ying Mao 001 (QCE, 2024)

Benchmarking Optimizers for Qumode State Preparation with Variational Quantum Algorithms. - Shuwen Kan; Miguel Palma; Zefan Du; Samuel Alexander Stein; Chenxu Liu; Juntao Chen; Ang Li 006; Ying Mao 001 (QCE, 2024)

PQML: Enabling the Predictive Reproducibility on NISQ Machines for Quantum ML Applications. - Priyabrata Senapati; Samuel Yen-Chi Chen; Bo Fang 002; Tushar M. Athawale; Ang Li 006; Weiwen Jiang; Cheng Chang Lu; Qiang Guan (QCE, 2024)

OPER: Optimality-Guided Embedding Table Parallelization for Large-scale Recommendation Model. - Zheng Wang 075; Yuke Wang; Boyuan Feng; Guyue Huang; Dheevatsa Mudigere; Bharath Muthiah; Ang Li 006; Yufei Ding 001 (USENIX ATC, 2024)

Evaluating Emerging AI/ML Accelerators: IPU, RDU, and NVIDIA/AMD GPUs. - Hongwu Peng; Caiwen Ding; Tong Geng; Sutanay Choudhury; Kevin J. Barker; Ang Li 006 (ICPE (Companion), 2024)

How Much Can We Gain From Tensor Kernel Fusion on GPUs? - Wei Sun; Ang Li 006; Sander Stuijk; Henk Corporaal (IEEE Access, 2024)

A GPU accelerated mixed-precision Smoothed Particle Hydrodynamics framework with cell-based relative coordinates. - Zirui Mao; Xinyi Li; Shenyang Hu; Ganesh Gopalakrishnan; Ang Li 006 (CoRR, 2024)

A Quantum-Classical Collaborative Training Architecture Based on Quantum State Fidelity. - Ryan L'Abbate; Anthony D'Onofrio Jr.; Samuel Alexander Stein; Samuel Yen-Chi Chen; Ang Li 006; Pin-Yu Chen; Juntao Chen; Ying Mao 001 (CoRR, 2024)

Accurate and Data-Efficient Micro-XRD Phase Identification Using Multi-Task Learning: Application to Hydrothermal Fluids. - Yanfei Li; Juejing Liu; Xiaodong Zhao; Wenjun Liu; Tong Geng; Ang Li 006; Xin Zhang (CoRR, 2024)

TANQ-Sim: Tensorcore Accelerated Noisy Quantum System Simulation via QIR on Perlmutter HPC. - Ang Li 006; Chenxu Liu; Samuel Alexander Stein; In-Saeng Suh; Muqing Zheng; Meng Wang 033; Yue Shi; Bo Fang 002; Martin Roetteler; Travis S. Humble (CoRR, 2024)

Inertial Confinement Fusion Forecasting via LLMs. - Mingkai Chen; Taowen Wang; James Chenhao Liang; Chuan Liu 001; Chunshu Wu; Qifan Wang 001; Ying Nian Wu; Michael Huang; Chuang Ren; Ang Li 006; Tong Geng; Dongfang Liu (CoRR, 2024)

Diff-PIC: Revolutionizing Particle-In-Cell Simulation for Advancing Nuclear Fusion with Diffusion Models. - Chuan Liu 001; Chunshu Wu; Shihui Cao; Mingkai Chen; James Chenhao Liang; Ang Li 006; Michael Huang; Chuang Ren; Dongfang Liu; Ying Nian Wu; Tong Geng (CoRR, 2024)

A GPU accelerated mixed-precision Finite Difference informed Random Walker (FDiRW) solver for strongly inhomogeneous diffusion problems. - Zirui Mao; Shenyang Hu; Ang Li 006 (CoRR, 2024)

Light-Weight Fault Tolerant Attention for Large Language Model Training. - Yuhang Liang; Xinyi Li; Jie Ren; Ang Li 006; Bo Fang 002; Jieyang Chen (CoRR, 2024)

Quantum-centric supercomputing for materials science: A perspective on challenges and future directions. - Yuri Alexeev; Maximilian Amsler; Marco Antonio Barroca; Sanzio Bassini; Torey Battelle; Daan Camps; David Casanova; Young Jay Choi; Frederic T. Chong; Charles Chung; Christopher Codella; Antonio D. Córcoles; et al. (Future Gener. Comput. Syst., 2024)

Acceleration of Graph Neural Network-Based Prediction Models in Chemistry via Co-Design Optimization on Intelligence Processing Units. - Hatem Helal; Jesun Firoz; Jenna A. Bilbrey; Henry Sprueill; Kristina M. Herman; Mario Michael Krell; Tom Murray; Manuel Lopez Roldan; Mike Kraus; Ang Li 006; Payel Das; Sotiris S. Xantheas; et al. (J. Chem. Inf. Model., 2024)

FPGA-Accelerated Range-Limited Molecular Dynamics. - Chunshu Wu; Chen Yang 010; Sahan Bandara; Tong Geng; Anqi Guo; Pouya Haghi; Ang Li 006; Martin C. Herbordt (IEEE Trans. Computers, 2024)

Accurate and Data-Efficient Micro X-ray Diffraction Phase Identification Using Multitask Learning: Application to Hydrothermal Fluids. - Yanfei Li; Juejing Liu; Xiaodong Zhao; Wenjun Liu; Tong Geng; Ang Li 006; Xin Zhang (Adv. Intell. Syst., 2024)

Nature-GL: A Revolutionary Learning Paradigm Unleashing Nature's Power in Real-World Spatial-Temporal Graph Learning. - Chuan Liu 001; Chunshu Wu; Ruibing Song; Yousu Chen; Ang Li 006; Michael C. Huang 001; Tony Tong Geng (ASP-DAC, 2025)

HetEC: Architectures for Heterogeneous Quantum Error Correction Codes. - Samuel Alexander Stein; Shifan Xu; Andrew W. Cross; Theodore J. Yoder; Ali Javadi-Abhari; Chenxu Liu; Kun Liu; Zeyuan Zhou; Charlie Guinn; Yufei Ding 001; Yongshan Ding 001; Ang Li 006 (ASPLOS (2), 2025)

QECC-Synth: A Layout Synthesizer for Quantum Error Correction Codes on Sparse Architectures. - Keyi Yin; Hezi Zhang; Xiang Fang; Yunong Shi; Travis S. Humble; Ang Li 006; Yufei Ding 001 (ASPLOS (1), 2025)

Diff-PIC: Revolutionizing Particle-In-Cell Nuclear Fusion Simulation with Diffusion Models. - Chuan Liu 001; Chunshu Wu; Shihui Cao; Mingkai Chen; James Chenhao Liang; Ang Li 006; Michael Huang; Chuang Ren; Ying Nian Wu; Dongfang Liu; Tong Geng (ICLR, 2025)

DS-LLM: Leveraging Dynamical Systems to Enhance Both Training and Inference of Large Language Models. - Ruibing Song; Chuan Liu 001; Chunshu Wu; Ang Li 006; Dongfang Liu; Ying Nian Wu; Tong Geng (ICLR, 2025)

On Scaling Up 3D Gaussian Splatting Training. - Hexu Zhao; Haoyang Weng; Daohan Lu; Ang Li 006; Jinyang Li 001; Aurojit Panda; Saining Xie (ICLR, 2025)

CaliQEC: In-situ Qubit Calibration for Surface Code Quantum Error Correction. - Xiang Fang; Keyi Yin; Yuchen Zhu; Jixuan Ruan; Dean Tullsen; Zhiding Liang; Andrew Sornborger; Ang Li 006; Travis S. Humble; Yufei Ding 001; Yunong Shi (ISCA, 2025)

DS-TPU: Dynamical System for on-Device Lifelong Graph Learning with Nonlinear Node Interaction. - Chunshu Wu; Ruibing Song; Chuan Liu 001; Pouya Haghi; Ang Li 006; Michael Huang; Tony Tong Geng (ISCA, 2025)

Accelerating GNNs on GPU Sparse Tensor Cores through N: M Sparsity-Oriented Graph Reordering. - Jou-An Chen; Hsin-Hsuan Sung; Ruifeng Zhang; Ang Li 006; Xipeng Shen (PPoPP, 2025)

ATTNChecker: Highly-Optimized Fault Tolerant Attention for Large Language Model Training. - Yuhang Liang; Xinyi Li; Jie Ren; Ang Li 006; Bo Fang 002; Jieyang Chen (PPoPP, 2025)

GMI-DRL: Empowering Multi-GPU DRL with Adaptive-Grained Parallelism. - Yuke Wang; Boyuan Feng; Zheng Wang 075; Guyue Huang; Tony Tong Geng; Ang Li 006; Yufei Ding 001 (USENIX ATC, 2025)

Context Switching for Secure Multi-programming of Near-Term Quantum Computers. - Avinash Kumar; Meng Wang 033; Chenxu Liu; Ang Li 006; Prashant J. Nair; Poulami Das 005 (CoRR, 2025)

OneAdapt: Adaptive Compilation for Resource-Constrained Photonic One-Way Quantum Computing. - Hezi Zhang; Jixuan Ruan; Dean Tullsen; Yufei Ding 001; Ang Li 006; Travis S. Humble (CoRR, 2025)