2024

• Huan, C., Wu, Y., Liu, H., Liu, Y., Zhang, H., Song, S., Pandey, S., Chen, S., Fang, X., Jin, Y., et al (2024). TEA+: A Novel Temporal Graph Random Walk Engine with Hybrid Storage Architecture. ACM Transactions on Architecture and Code Optimization, 21(2), 37. [More Information]
• Huan, C., Liu, Y., Zhang, H., Liu, H., Chen, S., Song, S., Wu, Y. (2024). TeGraph+: Scalable Temporal Graph Processing Enabling Flexible Edge Modifications. IEEE Transactions on Parallel and Distributed Systems, 35(8), 1469-1487. [More Information]

2023

• Wang, J., Wang, Z., Yu, B., Tang, J., Song, S., Liu, C., Hu, Y. (2023). Data Fusion in Infrastructure-Augmented Autonomous Driving System: Why? Where? and How? IEEE Internet of Things Journal. [More Information]
• Yang, Y., Xie, C., Liu, L., Leong, P., Song, S. (2023). Efficient Radius Search for Adaptive Foveal Sizing Mechanism in Collaborative Foveated Rendering Framework. IEEE Transactions on Mobile Computing. [More Information]
• Wang, L., Wan, Q., Ma, P., Wang, J., Chen, M., Song, S., Fu, X. (2023). Enabling High-Efficient ReRAM-Based CNN Training Via Exploiting Crossbar-Level Insignificant Writing Elimination. IEEE Transactions on Computers, 72(11), 3218-3230. [More Information]
• Zhong, F., Cheng, X., Yu, D., Gong, B., Song, S., Yu, J. (2023). MalFox: Camouflaged Adversarial Malware Example Generation Based on Conv-GANs Against Black-Box Detectors. IEEE Transactions on Computers, , 1-14. [More Information]
• Wen,, Y., Xie,, C., Song, S., Fu,, X. (2023). Post0-VR: Enabling Universal Realistic Rendering for Modern VR via Exploiting Architectural Similarity and Data Sharing. Proceedings - International Symposium on High-Performance Computer Architecture, : IEEE Computer Society.

2022

• Zheng, Z., Yang, X., Zhao, P., Long, G., Zhu, K., Zhu, F., Zhao, W., Liu, X., Yang, J., Zhai, J., Song, S., et al (2022). AStitch: Enabling a New Multi-dimensional Optimization Space for Memory-Intensive ML Training and Inference on Modern SIMT Architectures. Macro In Conference. [More Information]
• Liu,, S., Wang,, J., Wang,, Z., Yu,, B., Hu,, W., Liu,, Y., Tang,, J., Song, S., Liu,, C., Hu,, Y. (2022). Brief Industry Paper: The Necessity of Adaptive Data Fusion in Infrastructure-Augmented Autonomous Driving System. Proceedings of the IEEE Real-Time and Embedded Technology and Applications Symposium, RTAS, : SPIE.
• Zhai, J., Zheng, L., Zhang, F., Tang, X., Wang, H., Yu, T., Jin, Y., Song, S., Chen, W. (2022). Detecting Performance Variance for Parallel Applications Without Source Code. IEEE Transactions on Parallel and Distributed Systems, 33(12), 4239-4255. [More Information]
• Liu, Y., Zhang, X., Zhuang, D., Fu, X., Song, S. (2022). DynamAP: Architectural Support for Dynamic Graph Traversal on the Automata Processor. ACM Transactions on Architecture and Code Optimization, 19(4). [More Information]
• Zheng,, L., Zhai,, J., Tang,, X., Wang,, H., Yu,, T., Jin,, Y., Song, S., Chen,, W. (2022). Vapro: Performance Variance Detection and Diagnosis for Production-Run Parallel Applications. Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPOPP, : Springer Verlag.

2021

• Zhang, H., Li, L., Zhuang, D., Liu, R., Song, S., Tao, D., Wu, Y., Song, S. (2021). An efficient uncertain graph processing framework for heterogeneous architectures. 26th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPoPP 2021, United States: Association for Computing Machinery (ACM). [More Information]
• Zhang, C., Yuan, G., Niu, W., Tian, J., Jin, S., Zhuang, D., Jiang, Z., Wang, Y., Ren, B., Song, S., et al (2021). ClickTrain: Efficient and accurate end-to-end deep learning training via fine-grained architecture-preserving pruning. 35th ACM International Conference on Supercomputing, ICS 2021, New York: Association for Computing Machinery (ACM). [More Information]
• Zhang, X., Fu, X., Zhuang, D., Xie, C., Song, S. (2021). Enabling Highly Efficient Capsule Networks Processing through Software-Hardware Co-Design. IEEE Transactions on Computers, 70(4), 495-510. [More Information]
• Xie, C., Chen, J., Firoz, J., Li, J., Song, S., Barker, K., Raugas, M., Li, A. (2021). Fast and Scalable Sparse Triangular Solver for Multi-GPU Based HPC Architectures. 50th International Conference on Parallel Processing, ICPP 2021, New York: Association for Computing Machinery (ACM). [More Information]
• Ranganath, K., Suetterlein, J., Manzano, J., Song, S., Wong, D. (2021). MAPA: Multi-Accelerator Pattern Allocation Policy for Multi-Tenant GPU Servers. 33rd International Conference for High Performance Computing, Networking, Storage and Analysis: Science and Beyond, SC 2021, Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Xie, C., Li, X., Hu, Y., Peng, H., Taylor, M., Song, S. (2021). Q-VR: System-level design for future mobile collaborative virtual reality. 26th ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS 2021), New York: Association for Computing Machinery (ACM). [More Information]
• Wan, Q., Xia, H., Zhang, X., Wang, L., Song, S., Fu, X. (2021). Shift-BNN: Highly-efficient probabilistic bayesian neural network training via memory-friendly pattern retrieving. 54th Annual IEEE/ACM International Symposium on Microarchitecture, MICRO 2021, Piscataway: IEEE. [More Information]
• Tan, J., Chen, Y., Liu, Z., Ren, B., Song, S., Shen, X., Liu, X. (2021). Toward efficient interactions between Python and native libraries. 29th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering, ESEC/FSE 2021, New York: Association for Computing Machinery (ACM). [More Information]
• Rivera, C., Chen, J., Xiong, N., Zhang, J., Song, S., Tao, D. (2021). TSM2X: High-performance tall-and-skinny matrix-matrix multiplication on GPUs. Journal of Parallel and Distributed Computing, 151, 70-85. [More Information]
• Zhang, X., Xia, H., Zhuang, D., Sun, H., Fu, X., Taylor, M., Song, S. (2021). ç-LSTM: Co-designing highly-efficient large LSTM training via exploiting memory-saving and architectural design opportunities. 48th ACM/IEEE Annual International Symposium on Computer Architecture (ISCA 2021), Valencia: Institute of Electrical and Electronics Engineers (IEEE). [More Information]

2020

• Zhang, X., Song, S., Xie, C., Wang, J., Zhang, W., Fu, X. (2020). Enabling Highly Efficient Capsule Networks Processing Through A PIM-Based Architecture Design. 2020 IEEE International Symposium on High Performance Computer Architecture (HPCA), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Tan, J., Yan, K., Song, S., Fu, X. (2020). Energy-Efficient GPU L2 Cache Design Using Instruction-Level Data Locality Similarity. ACM Transactions on Design Automation of Electronic Systems, 25(6), 52:1-52:18. [More Information]
• Li, A., Song, S., Chen, J., Li, J., Liu, X., Tallent, N., Barker, K. (2020). Evaluating Modern GPU Interconnect: PCIe, NVLink, NV-SLI, NVSwitch and GPUDirect. IEEE Transactions on Parallel and Distributed Systems, 31(1), 94-110. [More Information]

2019

• Li, A., Geng, T., Wang, T., Herbordt, M., Song, S., Barker, K. (2019). BSTC: A Novel Binarized-Soft-Tensor-Core Design for Accelerating Bit-Based Approximated Neural Nets. The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC'19), New York: Association for Computing Machinery (ACM). [More Information]
• Tan, J., Yan, K., Song, S., Fu, X. (2019). LoSCache: Leveraging Locality Similarity to Build Energy-Efficient GPU L2 Cache. 22nd Design, Automation and Test in Europe Conference and Exhibition, DATE 2019, USA: Institute of Electrical and Electronics Engineers Inc. [More Information]
• Geng, T., Wang, T., Wu, C., Yang, C., Song, S., Li, A., Herbordt, M. (2019). LP-BNN: Ultra-low-latency BNN inference with layer parallelism. 30th IEEE International Conference on Application-Specific Systems, Architectures and Processors, ASAP 2019, USA: Institute of Electrical and Electronics Engineers Inc. [More Information]
• Xie, C., Chen, M., Xin, F., Song, S. (2019). OO-VR: NUMA friendly object-oriented VR rendering framework for future NUMA-based multi-GPU systems. 46th International Symposium on Computer Architecture, ISCA 2019, USA: Institute of Electrical and Electronics Engineers Inc. [More Information]
• Xie, C., Zhang, X., Li, A., Fu, X., Song, S. (2019). PIM-VR: Erasing motion anomalies in highly-interactive virtual reality world with customized memory cube. 25th IEEE International Symposium on High Performance Computer Architecture, HPCA 2019, USA: Institute of Electrical and Electronics Engineers Inc. [More Information]
• Ranganath, K., Abdolrashidi, A., Song, S., Wong, D. (2019). Speeding up Collective Communications through Inter-GPU Re-Routing. IEEE Computer Architecture Letters, 18(2), 128-131. [More Information]

2018

• Shen, D., Li, A., Song, S., Liu, X. (2018). CUDAAdvisor: LLVM-Based Runtime Profiling for Modern GPUs. 16th International Symposium on Code Generation and Optimization, CGO 2018, USA: Association for Computing Machinery (ACM). [More Information]
• Roy, P., Krishnamoorthy, S., Song, S., Liu, X. (2018). Lightweight Detection of Cache Conflicts. 16th International Symposium on Code Generation and Optimization, CGO 2018, USA: Association for Computing Machinery (ACM). [More Information]
• Roy, P., Song, S., Krishnamoorthy, S., Vishnu, A., Sengupta, D., Liu, X. (2018). NUMA-Caffe: NUMA-Aware Deep Learning Neural Networks. ACM Transactions on Architecture and Code Optimization, 15(2). [More Information]
• Xie, C., Fu, X., Song, S. (2018). Perception-Oriented 3D Rendering Approximation for Modern Graphics Processors. 24th IEEE International Symposium on High Performance Computer Architecture, HPCA 2018, USA: IEEE Computer Society. [More Information]
• Wang, L., Ye, J., Zhao, Y., Wu, W., Li, A., Song, S., Xu, Z., Kraska, T. (2018). SuperNeurons: Dynamic GPU memory management for training deep neural networks. 23rd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP 2018), New York: Association for Computing Machinery (ACM). [More Information]
• Li, A., Song, S., Chen, J., Liu, X., Tallent, N., Barker, K. (2018). Tartan: Evaluating Modern GPU Interconnect via a Multi-GPU Benchmark Suite. Tartan: Evaluating Modern GPU Interconnect via a Multi-GPU Benchmark Suite, USA: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Li, A., Liu, W., Wang, L., Barker, K., Song, S. (2018). Warp-consolidation: A novel execution model for GPUs. 32nd International Conference on Supercomputing, ICS 2018, USA: Association for Computing Machinery (ACM). [More Information]

2017

• Li, A., Zhao, W., Song, S. (2017). BVF: Enabling significant on-chip power savings via bit-value-favor for throughput processors. 50th Annual IEEE/ACM International Symposium on Microarchitecture, MICRO 2017, USA: IEEE Computer Society. [More Information]
• Qiu, J., Zhao, Z., Wu, B., Vishnu, A., Song, S. (2017). Enabling scalability-sensitive speculative parallelization for FSM computations. 31st ACM International Conference on Supercomputing, ICS 2017, USA: Association for Computing Machinery (ACM). [More Information]
• Zhang, N., Jiang, C., Sun, X., Song, S. (2017). Evaluating GPGPU memory performance through the C-AMAT Model. 2017 Workshop on Memory Centric Programming for HPC, MCHPC 2017, USA: Association for Computing Machinery (ACM). [More Information]
• Sengupta, D., Song, S. (2017). Evograph: On-the-fly efficient mining of evolving graphs on GPU. 32nd International Conference, ISC High Performance, 2017, Berlin: Springer Verlag. [More Information]
• Li, A., Liu, W., Kristensen, M., Vinter, B., Wang, H., Hou, K., Marquez, A., Song, S. (2017). Exploring and Analyzing the Real Impact of Modern On-Package Memory on HPC Scientific Kernels. International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2017, USA: Association for Computing Machinery (ACM). [More Information]
• Li, A., Song, S., Liu, W., Liu, X., Kumar, A., Corporaal, H. (2017). Locality-aware CTA Clustering for modern GPUs. 22nd International Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS 2017, China: Association for Computing Machinery (ACM). [More Information]
• Xie, C., Song, S., Wang, J., Zhang, W., Fu, X. (2017). Processing-in-Memory Enabled Graphics Processors for 3D Rendering. 23rd IEEE Symposium on High Performance Computer Architecture, HPCA 2017, USA: IEEE Computer Society. [More Information]

2016

• Tan, J., Song, S., Yan, K., Fu, X., Marquez, A., Kerbyson, D. (2016). Combating the Reliability Challenge of GPU Register File at Low Supply Voltage. 25th International Conference on Parallel Architectures and Compilation Techniques, PACT 2016, USA: Institute of Electrical and Electronics Engineers. [More Information]
• Li, A., Song, S., Kumar, A., Zhang, E., Chavarria-Miranda, D., Corporaal, H. (2016). Critical points based register-concurrency autotuning for GPUs. 19th Design, Automation and Test in Europe Conference and Exhibition, DATE 2016, USA: Institute of Electrical and Electronics Engineers.
• Tao, D., Song, S., Krishnamoorthy, S., Wu, P., Liang, X., Zhang, E., Kerbyson, D., Chen, Z. (2016). New-Sum: A Novel Online ABFT Scheme For General Iterative Methods. 25th ACM International Symposium on High-Performance Parallel and Distributed Computing, HPDC 2016, USA: Association for Computing Machinery (ACM). [More Information]
• Hayes, A., Li, L., Chavarria-Miranda, D., Song, S., Zhang, E. (2016). Orion: A framework for GPU occupancy tuning. 17th International Middleware Conference, Middleware 2016, USA: Association for Computing Machinery (ACM). [More Information]
• Li, A., Song, S., Wijtvliet, M., Kumar, A., Corporaal, H. (2016). SFU-driven transparent approximation acceleration on GPUs. 30th International Conference on Supercomputing, ICS 2016, USA: Association for Computing Machinery (ACM). [More Information]
• Roy, P., Liu, X., Song, S. (2016). SMT-Aware Instantaneous Footprint Optimization. 25th ACM International Symposium on High-Performance Parallel and Distributed Computing, HPDC 2016, USA: Association for Computing Machinery (ACM). [More Information]
• Li, L., Hayes, A., Song, S., Zhang, E. (2016). Tag-Split Cache for Efficient GPGPU Cache Utilization. 30th International Conference on Supercomputing, ICS 2016, USA: Association for Computing Machinery (ACM). [More Information]

2015

• Sengupta, D., Agarwal, K., Song, S., Schwan, K. (2015). GraphReduce: Large-Scale Graph Analytics on Accelerator-Based HPC Systems. 29th IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2015, Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Sengupta, D., Song, S., Agarwal, K., Schwan, K. (2015). GraphReduce: Processing large-scale graphs on accelerator-based systems. International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2015, USA: IEEE Computer Society. [More Information]
• Shrestha, S., Manzano, J., Marquez, A., Zuckerman, S., Song, S., Gao, G. (2015). Gregarious Data Re-structuring in a Many Core Architecture. 17th IEEE International Conference on High Performance Computing and Communications, IEEE 7th International Symposium on Cyberspace Safety and Security and IEEE 12th International Conference on Embedded Software and Systems, HPCC-ICESS-CSS 2015, USA: Institute of Electrical and Electronics Engineers. [More Information]
• Tan, L., Song, S., Wu, P., Chen, Z., Ge, R., Kerbyson, D. (2015). Investigating the Interplay between Energy Efficiency and Resilience in High Performance Computing. 29th IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2015, Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Li, C., Song, S., Dai, H., Sidelnik, A., Hari, S., Zhou, H. (2015). Locality-driven dynamic GPU cache bypassing. 29th ACM International Conference on Supercomputing, ICS 2015, USA: Association for Computing Machinery (ACM). [More Information]
• Tan, L., Chen, Z., Song, S. (2015). Scalable energy efficiency with resilience for high performance computing systems: A quantitative methodology. ACM Transactions on Architecture and Code Optimization, 12(4). [More Information]
• You, Y., Fu, H., Song, S., Randles, A., Kerbyson, D., Marquez, A., Yang, G., Hoisie, A. (2015). Scaling Support Vector Machines on modern HPC platforms. Journal of Parallel and Distributed Computing, 76, 16-31. [More Information]

2014

• Marquez, A., Manzano, J., Song, S., Meister, B., Shrestha, S., St. John, T., Gao, G. (2014). ACDT: Architected Composite Data Types Trading-in Unfettered Data Access for Improved Execution. 20th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2014, USA: IEEE Computer Society. [More Information]
• You, Y., Song, S., Kerbyson, D. (2014). An adaptive cross-architecture combination method for graph traversal. 28th ACM International Conference on Supercomputing, ICS 2014, USA: Association for Computing Machinery (ACM). [More Information]
• You, Y., Fu, H., Song, S., Dehnavi, M., Gan, L., Huang, X., Yang, G. (2014). Evaluating multi-core and many-core architectures through accelerating the three-dimensional Lax-Wendroff correction stencil. International Journal of High Performance Computing Applications, 28(3), 301-318. [More Information]
• Li, B., Chang, H., Song, S., Su, C., Meyer, T., Mooring, J., Cameron, K. (2014). Extending powerpack for profiling and analysis of high-performance accelerator-based systems. Parallel Processing Letters, 24(4). [More Information]
• You, Y., Song, S., Fu, H., Marquez, A., Dehnavi, M., Barker, K., Cameron, K., Randles, A., Yang, G. (2014). MIC-SVM: Designing a Highly Efficient Support Vector Machine for Advanced Modern Multi-core and Many-Core Architectures. 28th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2014, USA: IEEE Computer Society. [More Information]
• Li, B., Chang, H., Song, S., Su, C., Meyer, T., Mooring, J., Cameron, K. (2014). The power-performance tradeoffs of the intel Xeon Phi on HPC applications. 28th IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2014, : Springer Verlag. [More Information]

2013

• Song, S., Su, C., Rountree, B., Cameron, K. (2013). A simplified and accurate model of power-performance efficiency on emergent GPU architectures. 27th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2013, USA: IEEE Computer Society. [More Information]
• Vishnu, A., Song, S., Marquez, A., Barker, K., Kerbyson, D., Cameron, K., Balaji, P. (2013). Designing energy efficient communication runtime systems: A view from PGAS models. Journal of Supercomputing, 63(3), 691-709. [More Information]
• Li, B., Song, S., Bezakova, I., Cameron, K. (2013). EDR: An Energy-Aware Runtime Load Distribution System for Data-Intensive Applications in the Cloud. 15th IEEE International Conference on Cluster Computing, CLUSTER 2013, USA: IEEE Computer Society. [More Information]
• Song, S., Barker, K., Kerbyson, D. (2013). Unified performance and power modeling of scientific workloads. 1st International Workshop on Energy Efficient Supercomputing, E2SC 2013 - Held in Conjunction with the International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2013, USA: Association for Computing Machinery (ACM). [More Information]

2011

• Li, A., Song, S., Brugel, E., Kumar, A., Chavarria-Miranda, D., Corporaal, H. (2011). X: A Comprehensive Analytic Model for Parallel Machines. 30th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2016, USA: Institute of Electrical and Electronics Engineers Inc. [More Information]