David Kaeli
Distinguished Professor of Electrical and Computer Engineering, Khoury College Courtesy Appointment
Research interests
- Computer architecture
- Heterogeneous computing
- Performance analysis
- Embedded systems
- Security and information assurance
- Back-end compilers
- Profile-guided optimization
- Hardware reliability and recovery
- Image databases
- Software engineering
- Workload characterization
- General purpose graphics processing units (GPGPU)
Education
- PhD in Electrical Engineering, Rutgers University
- MS in Computer Engineering, Syracuse University
- BS in Electrical Engineering, Rutgers University
Biography
David Kaeli is a College of Engineering Distinguished Professor at Northeastern University, with a courtesy appointment at Khoury College of Computer Sciences. He is the director of the Northeastern University Computer Architecture Research Laboratory (NUCAR) and serves as a project leader at the NIEHS Puerto Rico Testsite for Exploring Contamination Threats (PROTECT) Center.
Kaeli is a Distinguished Scientist of the ACM and an IEEE fellow. He served as a research thrust leader for the NSF Center for Subsurface Sensing and Imaging Systems. He is a member of the Northeastern University Institute for Information Assurance and the Northeastern University Institute for Complex Scientific Software.
Kaeli's research looks at the performance and design of high-performance computer systems and software. Current research topics include profile-guided compilation, high-ILP microarchitectures, GPGPUs, architectural features for security, virtualization, power modeling, database systems, branch prediction studies, workload characterization, memory hierarchy design, embedded systems design, and software testing. He frequently provides tutorials on profiling, instrumentation, and trace-driven simulation.
Kaeli serves as chair of the IEEE Technical Committee on Computer Architecture. He recently served as a member-at-large for ACM SIGMicro and for CRA’s Computing Community Consortium, and he presently serves as an associate editor for IEEE Transactions on Parallel and Distributed Systems and the Journal of Parallel and Distributed Computing. Kaeli has served as an associate editor for IEEE Transactions on Computers and and IEEE Computer Architecture Letters, and is a member of the Eta Kappa Nu and Sigma Xi honor societies.
Recent publications
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NeuraChip: Accelerating GNN Computations with a Hash-based Decoupled Spatial Accelerator
Citation: Kaustubh Shivdikar, Nicolas Bohm Agostini, Malith Jayaweera, Gilbert Jonatan, José L. Abellán, Ajay Joshi, John Kim, David R. Kaeli. (2024). NeuraChip: Accelerating GNN Computations with a Hash-based Decoupled Spatial Accelerator ISCA, 946-960. https://doi.org/10.1109/ISCA59077.2024.00073 -
MaxK-GNN: Extremely Fast GPU Kernel Design for Accelerating Graph Neural Networks Training
Citation: Hongwu Peng, Xi Xie, Kaustubh Shivdikar, Md Amit Hasan, Jiahui Zhao, Shaoyi Huang, Omer Khan, David R. Kaeli, Caiwen Ding. (2024). MaxK-GNN: Extremely Fast GPU Kernel Design for Accelerating Graph Neural Networks Training ASPLOS (2), 683-698. https://doi.org/10.1145/3620665.3640426 -
Scalability Limitations of Processing-in-Memory using Real System Evaluations
Citation: Gilbert Jonatan, Haeyoon Cho , Hyojun Son, Xiangyu Wu, Neal Livesay, Evelio Mora, Kaustubh Shivdikar, José L. Abellán, Ajay Joshi, David R. Kaeli, John Kim. (2024). Scalability Limitations of Processing-in-Memory using Real System Evaluations Proc. ACM Meas. Anal. Comput. Syst., 8, 5:1-5:28. https://doi.org/10.1145/3639046 -
GME: GPU-based Microarchitectural Extensions to Accelerate Homomorphic Encryption
Citation: Kaustubh Shivdikar, Yuhui Bao, Rashmi Agrawal, Michael Tian Shen, Gilbert Jonatan, Evelio Mora, Alexander Ingare, Neal Livesay, José L. Abellán, John Kim, Ajay Joshi, David R. Kaeli. (2023). GME: GPU-based Microarchitectural Extensions to Accelerate Homomorphic Encryption MICRO, 670-684. https://doi.org/10.1145/3613424.3614279 -
An MLIR-based Compiler Flow for System-Level Design and Hardware Acceleration
Citation: Nicolas Bohm Agostini, Serena Curzel, Vinay Amatya, Cheng Tan , Marco Minutoli, Vito Giovanni Castellana, Joseph B. Manzano, David R. Kaeli, Antonino Tumeo. (2022). An MLIR-based Compiler Flow for System-Level Design and Hardware Acceleration ICCAD, 6:1-6:9. https://doi.org/10.1145/3508352.3549424 -
GPU Overdrive Fault Attacks on Neural Networks
Citation: Majid Sabbagh, Yunsi Fei, David R. Kaeli. (2021). GPU Overdrive Fault Attacks on Neural Networks ICCAD, 1-8. https://doi.org/10.1109/ICCAD51958.2021.9643486 -
Daisen: A Framework for Visualizing Detailed GPU Execution
Citation: Sun, Y., Zhang, Y., Mosallaei, A., Shah, M. D., Dunne, C., & Kaeli, D. (2021, April 2). Daisen: A framework for Visualizing Detailed GPU Execution. arXiv.org. https://arxiv.org/abs/2104.00828. -
Trident: A Hybrid Correlation-Collision GPU Cache Timing Attack for AES Key Recovery
Citation: Jaeguk Ahn, Cheolgyu Jin, Jiho Kim, Minsoo Rhu, Yunsi Fei, David R. Kaeli, John Kim. (2021). Trident: A Hybrid Correlation-Collision GPU Cache Timing Attack for AES Key Recovery HPCA, 332-344. https://doi.org/10.1109/HPCA51647.2021.00036 -
Achieving on-Mobile Real-Time Super-Resolution with Neural Architecture and Pruning Search
Citation: Zheng Zhan , Yifan Gong , Pu Zhao, Geng Yuan, Wei Niu, Yushu Wu, Tianyun Zhang, Malith Jayaweera, David R. Kaeli, Bin Ren, Xue Lin, Yanzhi Wang. (2021). Achieving on-Mobile Real-Time Super-Resolution with Neural Architecture and Pruning Search ICCV, 4801-4811. https://doi.org/10.1109/ICCV48922.2021.00478 -
A Novel GPU Overdrive Fault Attack
Citation: Majid Sabbagh, Yunsi Fei, David R. Kaeli. (2020). A Novel GPU Overdrive Fault Attack DAC, 1-6. https://doi.org/10.1109/DAC18072.2020.9218690