Email: wenlei.bao@gmail.com

Address: Bellevue, WA

I received my Ph.D. from Department of Computer Science and Engineering, for my work at HPC Research Lab, at The Ohio State University. My advisor is Prof. P. Sadayappan, and I also worked closely with Dr. Sriram Krishnamoorthy and Dr. Louis-Noël Pouchet. My research interests include High performance & Parallel Computing, Compiler Optimizations, Polyhedral Compilation. I am currently working on AI Infrastructure.

News

  • Join Apple.

  • Join Microsoft AI Framework Team.

  • Defense on April 2018.

  • Attending POPL'18 at LA.

  • Attending HiPEAC'17 at Sweden.

Experience

  • Aug. 2020 to Present: Apple.

  • Jun. 2018 to Aug. 2020 : Microsoft AI Framework, Developing Compiler-based, High-performance AI Inference Engine, Bellevue, WA.

  • Jun. to Dec. 2017 : Nvidia Internship, Optimizing Convolution Neural Network (CNN) on GPU, Redmond, WA.

  • May to Jul. 2015 : Pacific Northwest National Laboratory (PNNL) Internship, Program Verification, Richland, WA.

  • May to Aug. 2014 : Pacific Northwest National Laboratory (PNNL) Internship, Energy Optimization, Richland, WA.

Publications

  • NGEMM: Optimizing GEMM for Deep Learning via Compiler-based Techniques. Wenlei Bao, Li-Wen Chang, Yang Chen, Ke Deng, Amit Agarwal, Emad Barsoum and Abe Taha. arXiv.org, 2019.

  • Accelerating Recurrent Neural Networks through Compiler Techniques and Quantization. Li-Wen Chang, Yang Chen, Wenlei Bao, Amit Agarwal, Eldar Akchurin, Ke Deng, Emad Barsoum. Workshop on Systems for ML at NIPS, 2018

  • Analytical Modeling of Cache Behavior for Affine Programs. Wenlei Bao, Sriram Krishnamoorthy, Louis-Noël Pouchet, P. Sadayappan. The 45rd Annual ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages (POPL'18), January, 2018.

  • Efficient Cache Simulation for Affine Computations. Wenlei Bao, Prashant Rawat, Martin Kong, Sriram Krishnamoorthy, Louis-Noël Pouchet, P. Sadayappan. The 30th International Workshop on Languages and Compilers for Parallel Computing(LCPC'17), October, 2017.

  • Static and Dynamic Frequency Scaling on Multicore CPUs. Wenlei Bao, Changwan Hong, Sriram Krishnamoorthy, C.D. Sudheer, Louis-Noël Pouchet, Fabrice Rastello and P. Sadayappan. The ACM Transactions on Architecture and Code Optimization (TACO'17), January, 2017. (Original work, invited to HiPEAC'17).

  • Effective padding of multidimensional arrays to avoid cache conflict misses. Changwan Hong, Wenlei Bao, Albert Cohen, Sriram Krishnamoorthy, Louis-Noël Pouchet, Fabrice Rastello, J. Ramanujam and P. Sadayappan. The 37th annual ACM SIGPLAN conference on Programming Language Design and Implementation (PLDI'16), June, 2016.

  • Polycheck: Dynamic verification of iteration space transformations on affine programs. Wenlei Bao, Sriram Krishnamoorthy, Louis-Noël Pouchet, Fabrice Rastello, and P. Sadayappan. The 43rd Annual ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages (POPL'16), January, 2016.

  • PWCET: Power-Aware Worst Case Execution Time Analysis. Wenlei Bao, Sanket Tavarageri, Fusun Ozguner, and P. Sadayappan. Workshop at the 43rd International Conference on Parallel Processing (ICPP'14), September, 2014.

Professional Services

  • Reviewer of ACM Transactions on Architecture and Code Optimization (TACO).

  • Reviewer of Journal of Parallel and Distributed Computing (JPDC).

  • Reviewer of ACM Transactions on Embedded Computing Systems (TECS).

  • Reviewer of IEEE International Conference on High Performance Computing (HiPC'18).