• D. Adak, H. Zhou, E. Rotenberg, and A. Awad, “SpecMPK: Efficient In-Process Isolation with Speculative and  Secure Permission Update Instruction”, The 31^st International Symposium on High Performance Computer Architecture (HPCA-31), 2025.
• A. Meher, Y. Liu and H. Zhou, “Error Mitigation of Hamiltonian Simulations from an Analog-based Compiler (SimuQ)“, IEEE International Conference on Quantum Computing and Engineering (QCE24), 2024.
• S. Mohapatra and H. Zhou, “Understanding Error Sensitivity of Quantum Circuits“, IEEE International Conference on Quantum Computing and Engineering (QCE24), 2024.
• D. Baron, H. Patil, and H. Zhou, “Qubit-Wise Majority Vote: Maximum Likelihood Quantum Error Mitigation for Algorithms with a Single Correct Output“, IEEE International Conference on Quantum Computing and Engineering (QCE24), 2024.
• S. Faghih and H. Zhou, “Dynamic Runtime Assertions in Quantum Ternary Systems“, IEEE International Conference on Quantum Computing and Engineering (QCE24), 2024.
• A. Yudha, J. Xue, Q. Lou, H. Zhou, and, Y. Solihin, “BoostCom: Towards Efficient Universal Fully Homomorphic Encryption by Boosting the Word-wise Comparisons“, the International Conference on Parallel Architectures and Compilation Techniques (PACT), 2024.
• S. Yuan, A. Awad, and H. Zhou, “Delta Counter: Bandwidth-Efficient Encryption Counter Representation for Secure GPU Memory“, IEEE Transactions on Dependable and Secure Computing (TDSC), April, 2024.
• Y. Jin., Z. Li, F. Hua, T. Hao, H. Zhou, Y. Huang, and E. Zhang, “Tetris: A Compilation Framework for VQA Applications in Quantum Computing“, the 51st International Symposium on Computer Architecture (ISCA), 2024.(Artifact available) (Distinguished Artifact Award)
• P. Li, J. Liu, A. Gonzales, Z. Saleem, H. Zhou, and P. Hovland, “QuTracer: Mitigating Quantum Gate and Measurement Errors by Tracing Subsets of Qubits”, the 51st International Symposium on Computer Architecture (ISCA), 2024. (Artifact available) (Best Paper Candidate)
• R. Abdullah, H. Lee, H. Zhou, and A. Awad, “Salus: Efficient Security Support for CXL-Expanded GPU Memory“, The 30^th International Symposium on High Performance Computer Architecture (HPCA-30), 2024. (Artifact available)
• P. Li, J. Liu, H. Patil, P. Hovland, and H. Zhou, “Enhancing Virtual Distillation with Circuit Cutting for Quantum Noise Mitigation“, the 41^st IEEE International Conference on Computer Design (ICCD-2023), 2023.
• Y. Tozlu and H. Zhou, “PBVR: Physically Based Rendering in Virtual Reality”, The 2023 IEEE International Symposium on Workload Characterization (IISWC-2023), 2023. (Artifact)
• H. Patil, P. Li, J. Liu, and H. Zhou, “Folding-Free ZNE: A Comprehensive Quantum Zero-Noise Extrapolation Approach for Mitigating Depolarizing and Decoherence Noise“, the IEEE International Conference on Quantum Computing and Engineering (QCE’23), 2023.
• A. Frejj*, H. Zhou, and Y. Solihin, “SecPB: Architectures for Secure Non-Volatile Memory with Battery-Backed Persist Buffers”, The 29^th International Symposium on High Performance Computer Architecture (HPCA-29), 2023.
• R. Abdullah, H. Zhou, and A. Awad, “Plutus: Bandwidth-Efficient Memory Security for GPUs”, The 29^th International Symposium on High Performance Computer Architecture (HPCA-29), 2023.
• P. Li, J. Liu, Y. Li, and H. Zhou, “Exploiting Quantum Assertions for Error Mitigation and Quantum Program Debugging”, a special session paper in the 40^th IEEE International Conference on Computer Design (ICCD-2022), 2022.
• A. Yudha, J. Meyer, S. Yuan, H. Zhou, and Y. Solihin, “LITE: a Low-Cost Practical Inter-Operable GPU TEE”, The 36^th ACM International Conference on Supercomputing (ICS-2022), 2022.
• S. Yuan, A. Awad, A. Yudha, Y. Solihin, and H. Zhou, “Adaptive Security Support for Heterogeneous Memory on GPUs”, The 28^th International Symposium on High Performance Computer Architecture (HPCA-28), Feb. 2022.
• J. Liu, P. Li, and H. Zhou, “Not All SWAPs Have the Same Cost: A Case for Optimization-Aware Qubit Routing”, The 28^th International Symposium on High Performance Computer Architecture (HPCA-28), Feb. 2022. (HPCA-28 Distinguished Artifact Award)
• J. Ravi, T. Nguyen, H. Zhou, and M. Becchi, “PILOT: a Runtime System to Manage Multi-Tenant GPU Unified Memory Footprint”, 28th IEEE International Conference on High Performance Computing, Data, and Analytics (HiPC), 2021.
• A. Frejj*, H. Zhou, and Y. Solihin, “Bonsai Merkle Forests: Efficiently Achieving Crash Consistency in Secure Persistent Memory, The 54^th International Symposium on Microarchitecture (MICRO–54), 2021.
• S. Yuan, Y. Solihin, and H. Zhou, “PSSM: Achieving Secure Memory for GPUs with Partitioned and Sectored Security Metadata”, The 35^th ACM International Conference on Supercomputing (ICS-2021), 2021.
• S. Yuan, A. Yudha, Y. Solihin, and H. Zhou, “Analyzing Secure Memory Architecture for GPUs”, the IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS’2021), Mar. 2021
• J. Liu and H. Zhou, “Systematic Approaches for Precise and Approximate Quantum State Runtime Assertion”, The 27^th International Symposium on High Performance Computer Architecture (HPCA-27), Feb. 2021.
• J. Liu, L. Bello, and H. Zhou, “Relaxed Peephole Optimization: A Novel Compiler Optimization for Quantum Circuits”, International Symposium on Code Generation and Optimization (CGO-2021), 2021. (Artifact included)
• J. Liu and H. Zhou, “Reliability Modeling of NISQ-Era Quantum Computers”, The 2020 IEEE International Symposium on Workload Characterization (IISWC-2020), 2020.
• A. Yudha, K. Kimura, H. Zhou, and Y. Solihin, “Scalable and Fast Lazy Persistency on GPUs”, The 2020 IEEE International Symposium on Workload Characterization (IISWC-2020), 2020.
• A. Frejj*, S. Yuan, H. Zhou, and Y. Solihin, “Persist-Level Parallelism: Streamlining Integrity Tree Updates for Secure Non-Volatile Memory”, The 53^rd International Symposium on Microarchitecture (MICRO–53), 2020.
• J. Liu, A. Kafi, X. Shen and H. Zhou, “MKPipe: A Compiler Framework for Optimizing Multi-Kernel Workloads in OpenCL for FPGA”, The 34^th ACM International Conference on Supercomputing (ICS-2020), 2020.
• J. Liu, G. Byrd, and H. Zhou, “Quantum Circuits for Dynamic Runtime Assertions in Quantum Computation”, The 24^th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS 2020),2020.(Artifact: benchmarks and source code)

• C. Zhao, et al., Fair and cache blocking aware warp scheduling for concurrent kernel execution on GPU. Future Gener. Comput. Syst. 112: 1093-1105 (2020)
• H. Guan, L. Ning, Z. Lin, X. Shen, H. Zhou, and S. Lim, “In-Place Zero-Space Memory Protection for CNN”, 23^rd Conf. on Neural Information Processing Systems (NeurIPS), 2019.
• H. Zhou and G. T. Byrd, “Quantum Circuits for Dynamic Runtime Assertions in Quantum Computation,” in IEEE Computer Architecture Letters (CAL). 2019. doi: 10.1109/LCA.2019.2935049
• Zhen Lin, Mohammad Alshboul, Yan Solihin, and Huiyang Zhou, “Exploring Memory Persistency Models for GPUs”, in the 28th International Conference on Parallel Architectures and Compilation Techniques (PACT), 2019.
• Z. Lin, H. Dai, M. Mantor, and H. Zhou, “Coordinated CTA Combination and Bandwidth Partitioning for GPU Concurrent Kernel Execution”, in ACM Transactions on Architecture and Code Optimization (TACO), 2019. 
• Z. Lin, U. Mathur, and H. Zhou, “Scatter-and-Gather Revisited: High-Performance Side-Channel-Resistant AES on GPUs”, The 12^th workshop on General-Purpose Computation on Graphics Processing Units (GPGPU-2019), 2019. (Source code)
• Y. Zhong, C. Li, H. Zhou, and G. Wang, “Developing Noise-Resistant Three-Dimensional Single Particle Tracking Using Deep Neural Networks”, Analytical Chemistry, 2018.
• H. Dai, Z. Lin, C. Li, C. Zhao, F. Wang,  N. Zheng, and H Zhou, “Accelerate GPU Concurrent Kernel Execution by Mitigating Memory Pipeline Stalls”, in 24th International Symposium on High Performance Computer Architecture (HPCA-24), Feb. 2018.
• Z. Lin, M. Mantor, and H. Zhou, “GPU Performance vs. Thread-Level Parallelism: Scalability Analysis and A Novel Way to Improve TLP”, in ACM Transactions on Architecture and Code Optimization (TACO), Issue 1, 2018
• H. Dai, C. Li, Z. Lin and H. Zhou, “The Demand for a Sound Baseline in GPU Memory Architecture Research”, 14th Annual Workshop on Duplicating, Deconstructing and Debunking (WDDD), held with ISCA-2017, 2017. (Source code)
• A. Verma, H. Zhou, S. Booth, R. King, J. Coole, J. Marshall, A. Keep, and W. Feng, “Developing Dynamic Profiling and Debugging Support in OpenCL for FPGAs”, in the 54^th Design Automation Conference (DAC-2017), 2017. (Sample code in github)
• G. Chen, Y. Zhao, X. Shen, and H. Zhou, “EffiSha: A Software Framework for Enabling Efficient Preemptive Scheduling of GPU”, in the 22^nd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP’17), 2017.
• Y. Zhang, S. Li, S. Yan, and H. Zhou, “A Cross-Platform SpMV Framework on Many-Core Architectures”, ACM Transactions on Architecture and Code Optimization (TACO), Vol. 13, Issue 4, Nov. 2016.
• C. Zhao, F. Wang, Z. Lin, H. Zhou, and N. Zheng, “Selective GPU Cache Bypassing for Un-Coalesced Loads”, in the 22nd IEEE International Conference on Parallel and Distributed Systems (ICPADS), 2016.
• Z. Lin, L. Nyland, and H. Zhou, “Enabling Efficient Preemption for SIMT Architectures with Lightweight Context Switching”, in the International Conference on High Performance Computing, Networking, Storage, and Analysis (SC’16), 2016
• C. Li, Y. Yang, M. Feng, C. Srimat, and H. Zhou, “Optimizing Memory Efficiency for Deep Convolutional Networks on GPUs”, in the International Conference on High Performance Computing, Networking, Storage, and Analysis (SC’16), 2016. (best student paper finalist)
• Q. Jia and H. Zhou, “Tuning Stencil Codes in OpenCL for FPGAs”, in the 34^th IEEE International Conference on Computer Design (ICCD-2016), 2016. (source code)
• G. Chen, H. Zhou, X. Shen, J. Gahm, N. Venkat, S. Booth and J. Marshall, “OpenCL-Based Erasure Coding on Heterogeneous Architectures”, in the 27^th IEEE International Conference on Application-specific Systems, Architectures and Processors (ASAP 2016), 2016. (presentation, containing the results of the FPGA on an Intel Broadwell processor using SVM)
• H. Dai, S. Gupta, C. Li, C. Kartsaklis, M. Mantor, H. Zhou, “A Model-Driven Approach to Warp/Thread-Block Level GPU Cache Bypassing”, in the 53^rd Design Automation Conference (DAC-2016), 2016.
• S. Gupta and H. Zhou, “Spatial Locality-Aware Cache Partitioning for Effective Cache Sharing”, in the 44^th International Conference on Parallel Processing (ICPP 2015), Sept. 2015.
• Q. Jia, M. B. Padia, K. Amboju, and H. Zhou, “An Optimized AMPM-based Prefetcher Coupled with Configurable Cache Line Sizing”, JILP Workshop on Computer Architecture Competitions (JWAC): 2^nd Data Prefetching Championship (DPC2), held with ISCA-42, June 2015.
• C. Li, S. Song, H. Dai, A. Sidelnik, S. Hari, and H. Zhou, “Locality-Driven Dynamic GPU Cache Bypassing”, in the 29th International Conference on Supercomputing (ICS’15), June 2015.
• K. Mayank, H. Dai, J. Wei and H. Zhou “Analyzing Graphics Processor Unit (GPU) Instruction Set Architectures”, Poster paper in the IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS’2015), Mar. 2015
• P. Xiang, Y. Yang, M. Mantor, N. Rubin and H. Zhou, “Revisiting ILP Designs for Throughput-Oriented GPGPU Architecture”, the 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid 2015), May 2015
• Y. Yang, C. Li, and H. Zhou, “CUDA-NP: Realizing nested thread-level parallelism in GPGPU applications.” Journal of Computer Science and Technology (JCST) 30(1): 3–19 Jan. 2015
• C. Li, Y. Yang, Z. Lin, and H. Zhou, “Automatic Data Placement into GPU On-Chip Memory Resources”, 2015 ACM International Symposium on Code Generation and Optimization (CGO’2015), Feb., 2015. (talk)
• Y. Yang and H. Zhou, “A Highly Efficient FFT Using Shared-Memory Multiplexing”, a book chapter in Numerical Computations with GPUs (Editor: Volodymyr Kindratenk), Springer 2014. (source code)
• Y. Yang, P. Xiang, M. Mantor, N. Rubin, L. Hsu, Q. Dong and H. Zhou, “A Case for a Flexible Scalar Unit in SIMT Architecture”, in the 28th IEEE International Parallel & Distributed Processing Symposium (IPDPS’2014), May 2014
• C. Li, Y. Yang, H. Dai, S. Yan, F. Mueller and H. Zhou, “Understanding the Tradeoffs between Software-Managed vs. Hardware-Managed Caches in GPUs”, in the IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS’2014), March 2014 (Talk)
• P. Xiang, Y. Yang, and H. Zhou, “Warp-Level Divergence in GPUs: Characterization, Impact and Mitigation”, in the 20^th International Symposium on High Performance Computer Architecture (HPCA-20), Feb., 2014. (Talk)
• Y. Yang and H. Zhou, “CUDA-NP: Realizing Nested Thread-Level Parallelism in GPGPU Applications”, in the 19^th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP’14), Feb. 2014. (Talk)
• S. Yan, C. Li, Y. Zhang, and H. Zhou, “yaSpM: Yet Another SpMV Framework on GPUs”, in the 19^th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP’14), Feb. 2014. (Source code) (Talk)
• S. Gupta, P. Xiang, and H. Zhou, “Analyzing locality of memory references in GPU architectures”, in ACM SIGPLAN Workshop on Memory Systems Performance and Correctness (MSPC), co-located with PLDI 2013, June 2013.
• P. Xiang, Y. Yang, M. Mantor, N. Rubin, L. Hsu, and H. Zhou, “Exploiting Uniform Vector Instructions for GPGPU Performance, Energy Efficiency, and Opportunistic Reliability Enhancement“, in the 27th International Conference on Supercomputing (ICS’13), June 2013.
• S. Gupta, H. Gao, and H. Zhou, “‘Adaptive Cache Bypassing for Inclusive Last Level Caches”, in the 27^th IEEE International Parallel & Distributed Processing Symposium (IPDPS 2013), May 2013.
• S. Gupta, P. Xiang, Y. Yang, and H. Zhou, “Locality principle revisited: A probability-based quantitative approach“, Journal of Parallel and Distributed Computing (JPDC), 73(7): 1011-1027, 2013 (a special issue on the Best Papers: International Parallel and Distributed Processing Symposium (IPDPS) 2010, 2011 and 2012)
• Y. Yang, P. Xiang, M. Mantor, N. Rubin, and H. Zhou, “Shared Memory Multiplexing: A Novel Way to Improve GPGPU Throughput”, in the 21^st International Conference on Parallel Architectures and Compilation Techniques (PACT’12), Sept. 2012. 

• Y. Yang, P. Xiang, M. Mantor, and H. Zhou, “Fixing Performance Bugs: An Empirical Study of Open-Source GPGPU Programs”, in the 41^st International Conference on Parallel Processing (ICPP 2012), Sept. 2012.
• Y. Yang and H. Zhou, “The Implementation of a High Performance GPGPU Compiler”, in International Journal of Parallel Programming (IJPP) 41(6): 768-781, 2013..
• J. Kong, O. Acıiçmez, J.-P. Seifert and H. Zhou, “Architecting Against Software Cache-based Side Channel Attacks”, in IEEE Trans. Computers (TC) 62(7): 1276-1288 (2013).
• S. Gupta, P. Xiang, Y. Yang, and H. Zhou, “Locality Principle Revisited: A Probability-Based Quantitative Approach”, in the 26^th IEEE International Parallel & Distributed Processing Symposium (IPDPS 2012) (best paper in the architecture track), May, 2012. (locality computation code)
• Y. Yang, P. Xiang, M. Mantor, and H. Zhou, “CPU-Assisted GPGPU on Fused CPU-GPU Architectures”, in the 18^th International Symposium on High Performance Computer Architecture (HPCA-18), Feb., 2012.
• Y. Yang, P. Xiang, J. Kong, M. Mantor, and H. Zhou, “A Unified Optimizing Compiler Framework for Different GPGPU Architectures”, in ACM Transactions on Architecture and Code Optimization (TACO), Vol. 9, Num. 2, 2012.
• Y. Yang and H. Zhou, “Developing a High Performance GPGPU Compiler using Cetus”, Cetus Users and Compiler Infrastructure Workshop, held with  International Conference on Parallel Architectures and Compilation Techniques (PACT’11),  Oct., 2011
• N. Bhansali, C. Panirwla, and H. Zhou, “Exploring Correlation for Indirect Branch Prediction”, in 2^nd JILP Workshop on Computer Architecture Competitions (JWAC-2): Championship Branch Prediction, held with ISCA-38, June, 2011.
• M. Dimitrov and H. Zhou, “Time-Ordered Event Traces: A New Debugging Primitive for Concurrency Bugs”, in the 25^th IEEE International Parallel & Distributed Processing Symposium (IPDPS 2011), pp 311-321, May, 2011.
• M. Dimitrov and H. Zhou, “Combining Local and Global History for High Performance Data Prefetching”, Journal of Instruction-Level Parallelism (JILP), Vol. 13, 2011
• J. Kong and H. Zhou, “Improving Privacy and Lifetime of PCM-based Main Memory”, The 40^th IEEE/IFIP Conference on Dependable Systems and Networks (DSN 2010) (DCCS track), July, 2010.
• Y. Yang, P. Xiang, J. Kong, and H. Zhou, “A GPGPU Compiler for Memory Optimization and Parallelism Management”, The ACM SIGPLAN 2010 Conference on Programming Language Design and Implementation (PLDI’2010), June, 2010. (the open-source compiler code is available here) (talk given at PLDI’2010)
• J. Kong, et. al., “Accelerating MATLAB Image Processing Toolbox Functions on GPUs”, The 3^rd workshop on General-Purpose Computation on Graphics Processing Units (GPGPU-3), held with the 15^th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS-XV), Mar. 2010. (the OpenCL code is available here) (talk given at GPGPU-3)
• M. Dimitrov and H. Zhou, “Anomaly-based Bug Prediction, Isolation, and Validation: An Automated Approach for Software Debugging”, The 14^th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS-XIV), Mar. 2009. (The automated debugging tool can be downloaded here) (talk given at ASPLOS-XIV).
• M. Dimitrov, M. Mantor, and H. Zhou, “Understanding Software Approaches for GPGPU Reliability”, The 2^nd workshop on General-Purpose Computation on Graphics Processing Units (GPGPU-2), held with the 14^th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS-XIV), Mar. 2009. (talk given at GPGPU-2)
• J. Kong, O. Acıiçmez, J.-P. Seifert and H. Zhou, “Hardware-Software Integrated Approaches to Defend Against Software Cache-based Side Channel Attacks”, The 15^th International Symposium on High Performance Computer Architecture (HPCA-15), Feb., 2009. (talk)
• M. Dimitrov and H. Zhou, “Combining Local and Global History for High Performance Data Prefetching”, The 1^st Journal of Instruction-Level Parallelism (JILP) Data Prefetching Championship (DPC-1), held with 15^th International Symposium on High Performance Computer Architecture (HPCA-15), Feb., 2009. (ranked 2^nd) (talk, code)
• J. Kong, O. Acıiçmez, J.-P. Seifert and H Zhou, “Deconstructing New Cache Designs for Thwarting Software Cache-based Side Channel Attacks”, The 2^nd ACM Computer Security Architecture Workshop (CSAW-2), held in conjunction with 15th ACM Conference on Computers and Communication Security (CCS-2008), pp. 25-34, Oct. 2008. (talk given at CSAW-2)
• H. Gao, Y. Ma, M. Dimitrov, and H. Zhou, “Address-Branch Correlation: A Novel Locality for Long-Latency Hard-to-Predict Branches”, The 14^th International Symposium on High Performance Computer Architecture (HPCA-14), pp. 74-85, Feb., 2008. (talk given at HPCA-14)
• M. Dimitrov and H. Zhou, “Unified Architectural Support for Soft-Error Protection or Software Bug Detection”, International Conference on Parallel Architectures and Compilation Techniques (PACT’07), pp. 73-82, Sept. 2007. (talk given at PACT’07)
• H. Gao and H. Zhou, “PMPM: Prediction by Combining Multiple Partial Matches”, Journal of Instruction-Level Parallelism (JILP), pp. 1-18, Vol. 9, 2007.
• Y. Ma, H. Gao, M. Dimitrov, and H. Zhou, “Optimizing Dual-Core Execution for Power Efficiency and Transient-Fault Recovery”, IEEE Transactions on Parallel and Distributed Systems, vol. 18,  no. 8,  pp. 1080-1093,  Aug.,  2007
• H. Gao and H. Zhou, “PMPM: Prediction by Combining Multiple Partial Matches”, 2^nd Championship Branch Prediction (CBP-2) held with the 39^th International Symposium on Microarchitecture (MICRO-39), pp. 19-24, Dec. 2006. (finalist in both the realistic and idealistic tracks, code for the realistic track, code for the idealistic track, talk given at CBP-2)
• M. Dimitrov and H. Zhou, “Locality-based Information Redundancy for Processor Reliability”, 2^nd Workshop on Architectural Reliability (WAR-2) held in conjunction with 39^th International Symposium on Microarchitecture (MICRO-39), pp. 29-36, Dec. 2006. (presentation given at WAR-2)
• J. Kong, C. Zou, and H. Zhou, “Improving Software Security via Runtime Instruction-Level Taint Checking”, Workshop on Architectural and System Support for Improving Software Dependability (ASID) held in conjunction with 12^th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS-XII), pp. 18-24, October, 2006. (presentation given at ASID’06)
• Y. Ma and H, Zhou, “Efficient Transient-Fault Tolerance for Multithreaded Processors Using Dual-Thread Execution”, IEEE International Conference on Computer Design (ICCD), pp. 120-126, October, 2006. (presentation given at ICCD’06)
• Y. Ma, H. Gao, and H. Zhou, “Using Indexing Functions to Reduce Conflict Aliasing in Branch Prediction Tables”, IEEE Transactions on Computers (TC), pp. 1057-1061, August, 2006.
• H. Zhou, “A Case for Fault Tolerance and Performance Enhancement using Chip Multi-Processors”, IEEE Computer Architecture Letters (CAL), pp. 1-4, Sept. 2005.
• H. Zhou, “Dual-Core Execution: Building a Highly Scalable Single-Thread Instruction Window”, Proceedings of the 2005 International Conference on Parallel Architectures and Compilation Techniques (PACT’05), pp. 231-242, Sept. 2005. (presentation given at PACT’05)
• H. Gao and H. Zhou, “Adaptive Information Processing: An Effective Way to Improve Perceptron Branch Predictors”, Journal of Instruction-Level Parallelism (JILP), pp. 1-10, Vol. 7, 2005.
• H. Zhou and T. M. Conte, “Enhancing Memory-Level Parallelism via Recovery-Free Value Prediction”, IEEE Transactions on Computers (TC), pp. 897-912, July 2005.
• H. Gao and H. Zhou, “Adaptive Information Processing: An Effective Way to Improve Perceptron Branch Predictors”, Champion, In the 1^st Championship Branch Prediction (CBP-1) held with the 37^th International Symposium on Microarchitecture (MICRO-37), Dec. 2004. (presentation, download the code, the simulation framework).
• H. Zhou, M. Toburen, E. Rotenberg, and T. M. Conte, “Adaptive Mode Control: A Static-Power-Efficient Cache Design”, ACM Transactions on Embedded Computing Systems (TECS), pp. 347-372, vol. 2, no. 3, August, 2003. 
• H. Zhou and T. M. Conte, “Enhancing Memory Level Parallelism via Recovery-Free Value Prediction”, The 2003 International Conference on Supercomputing (ICS’03), pp. 326-335, June 2003. 
• H. Zhou, J. Flanagan, and T. M. Conte, “Detecting Global Stride Locality in Value Streams”, The 30^th ACM/IEEE International Symposium of Computer Architecture (ISCA-30), pp. 324-335, June 2003. 
• H. Zhou and T. M. Conte, “Code Size Efficiency in Global Scheduling for ILP Processors”, The 6^th Annual Workshop on Interaction between Compilers and Computer Architectures (INTERACT-6) held in conjunction with HPCA-8, pp. 79-90, February 2002. 
• H. Zhou, M. Toburen, E. Rotenberg, T. M. Conte, “Adaptive Mode Control: A Static-Power-Efficient Cache Design”, Proceedings of the 2001 International Conference on Parallel Architectures and Compilation Techniques (PACT’01), pp. 61-70, Sept. 2001. 
• H. Zhou, M. D. Jennings, T. M. Conte, “Tree Traversal Scheduling: A Global Scheduling Technique for VLIW/EPIC Processors”, The 14th Annual Workshop on Languages and Compilers for Parallel Computing (LCPC’01), LNCS 2624, pp. 223-238, Springer Verlag, August, 2001 (2003). 
• A. A. Kassim, H. Zhou, S. Ranganath, Automatic IC orientation checks, Machine Vision and Applications, pp. 107-112, Vol. 12, No. 3, pp. 107-112, 2000. 
• H. Zhou, A. A. Kassim, S. Ranganath, A fast algorithm for detecting die extrusion defects in IC packages, Machine Vision and Applications, pp. 37-41, Vol.11, No.1, pp.37-41, 1998. 
• Zhou Huiyang, Qu Liangsheng, Li Aihua, Test Sequencing and Diagnosis in Electrical System with Decision Table, Microelectronics and Reliability, Vol.36, No.9, pp.1167-1175, 1996. 

Refereed Educational Publication

H. Gao, M. Dimitrov, J. Kong, and H. Zhou, “Experiencing Various Massively Parallel Architectures and Programming Models for Data-Intensive Applications”, Workshop on Computer Architecture Education (WCAE-08), held in conjunction with ISCA-35, 2008. (talk given at WCAE-08)

Technical Reports

• Y. Mao, H. Zhou, and X. Gui, “Exploring deep neural networks for branch prediction”, Technical Report, ECE Department, N. C. State University, Sep. 2017.
• H. Zhou, “Code size aware compilation for real-time applications”, Technical Report, CS department, University of Central Florida, July 2003.
• H. Zhou and T. M. Conte, “Performance modeling of memory latency hiding techniques”, Technical Report, ECE Department, N. C. State University, January 2003.
• H. Zhou and T. M. Conte,  “Using Performance Bounds to Guide Pre-scheduling Code Optimizations”, Technical Report, ECE Department, N. C. State University, Sep. 2002.
• M. D. Jennings, H. Zhou, T. M. Conte, “A Treegion-based Unified Approach to Speculation and Predication in Global Instruction Scheduling”, Technical Report, ECE Department, N. C. State University, August 2001. 
• H. Zhou, C. Fu, E. Rotenberg, T. Conte, “A study of value speculative execution and mispeculation recovery in superscalar microprocessors“, Technical Report, ECE Department, N. C. State University, Jan., 2001. 
• H. Zhou, M. Toburen, E. Rotenberg, T. Conte, “Adaptive Mode Control: A Low-Leakage Power-Efficient Cache Design”, Technical Report, ECE Department, N. C. State University, Nov., 2000. 

Software Release

• yaSpMV: Yet Another GPU Framework for SpMV

• An OpenCL Code Library for Accelerating MATLAB Image Processing Toolbox Functions

An Open-Source GPGPU Compiler (CUDA/OpenCL-to-CUDA/OpenCL code optimizer)