Principal Investigator

Kunle Olukotun

Cadence Design Systems Professor, Professor of Electrical Engineering and of Computer Science
Kunle Olukotun is the Cadence Design Professor of Electrical Engineering and Computer Science at Stanford University. Olukotun is a pioneer in multicore processor design and the leader of the Stanford Hydra chip multiprocessor (CMP) research project. He founded Afara Websystems to develop high-throughput, low-power multicore processors for server systems. The Afara multi-core processor, called Niagara, was acquired by Sun Microsystems and now powers Oracle's SPARC-based servers. In 2017, Olukotun co-founded SambaNova Systems, a Machine Learning and Artificial Intelligence company, and continues to lead as their Chief Technologist.

Olukotun is the Director of the Pervasive Parallel Lab and a member of the Data Analytics tor What's Next (DAWN) Lab, developing infrastructure for usable machine learning. He is a member of the National Academy of Engineering, an ACM Fellow, and an IEEE Fellow for contributions to multiprocessors on a chip design and the commercialization of this technology. He also received the Harry H. Goode Memorial Award.

Olukotun received his Ph.D. in Computer Engineering from The University of Michigan.

Projects

  • Spatial

     A new Domain Specific Language for programming reconfigurable hardware from a parameterized, high level abstraction.

  • DAWNBench

     A benchmark suite for end-to-end deep learning training and inference.

  • HyperMapper

     A multi-objective black-box optimization tool based on Bayesian Optimization.

Advisees

Education

PhD, Michigan (1991)

Contact

(650) 725-3713
Mail Code
9030

Links

View Full Stanford Profile

Publications

  • Coleman, C., Kang, D., Narayanan, D., Nardi, L., Zhao, T., Zhang, J., Bailis, P., Olukotun, K., Ré, C., & Zaharia, M. (2019). Analysis of DAWNBench, a Time-to-Accuracy Machine Learning Performance Benchmark. ACM SIGOPS Operating Systems Review, 53(1), 14–25. https://doi.org/10.1145/3352020.3352024
  • Nardi, L., Koeplinger, D., & Olukotun, K. (2019). Practical Design Space Exploration. 2019 IEEE 27th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS), 347–358. https://doi.org/10.1109/MASCOTS.2019.00045
  • Koeplinger, D., Feldman, M., Prabhakar, R., Zhang, Y., Hadjis, S., Fiszel, R., Zhao, T., Nardi, L., Pedram, A. ., Kozyrakis, C., & Olukotun, K. (2018). Spatial: A Language and Compiler for Application Accelerators. PLDI 2018: Proceedings of the 39th ACM SIGPLAN Conference on Programming Language Design and Implementation, 296–311. https://doi.org/10.1145/3192366.3192379
  • Coleman, C., Narayanan, D., Kang, D., Zhao, T., Zhang, J., Nardi, L., Bailis, P., Olukotun, K., Ré, C., & Zaharia, M. (2017). DAWNBench: An End-to-End Deep Learning Benchmark and Competition. 31st Conference on Neural Information Processing Systems (NIPS 2017).