Monte Carlo Simulation of photon migration in 3D turbid media
Poster at HPC Day 2016, UMass Dartmouth, MA
CV
Work experience
Sep 2022 - Present: Qualcomm
- July 2019 - Sep 2022: Analogic
- Optimize Computed Tomography related algorithms on GPUs
- Improve Metal Artifact Reduction by 12x
- Improve Extended Field of View by 70x
- Optimize CT algorithms to run on a single GPU, rather than two
- Develop and deploy Deep Learning models for Low-dose CT image denoising
- Evaluate Operating Systems for future CT scanners
- GPU Evaluation and Image Quality Evaluation for recon software releases
- Optimize Computed Tomography related algorithms on GPUs
- July - Dec 2016: MERL (Intern)
- Optimized Model Predictive Control solvers (PQP and ADMM) on NVIDIA Jetson TX1
- Developed efficient SGEMV kernels that outperform cuBLAS on NVIDIA Jetson TX1
- Developed mpcCUDA, GPU-accelerated Model Predictive Control solvers in Matlab
- Summer 2012: Mathworks (Intern)
- Accelerated PSK Demodulator/Modulator on GPU
- Accelerated LDPC Decoder for Large Parity Check Matrix on GPU
- Improved the parfor section in commViterbiSystemGPU demo
- Accelerated Turbodecoder on Matlab Distributed Computing Server (MDCS)
Awards
- Best Poster: HPC Day 2017
- Best Poster: HPC Day 2016
- GE Hackathon Challenge: “Most Robust” Winner 2017
- Student Travel Grant : IISWC 2017
- Student Travel Grant: PPoPP 2015
Peer Review
- Journal of Parallel and Distributed Computing (JPDC), 2019
- IEEE Transactions on Computers(TCSI), 2019
- Simulation Modelling Practice and Theory (Elsevier Journal), 2018
- Parallel, Distributed and Network-based Processing (PDP), 2016
Education
- Ph.D in Computer Engineering, Northeastern University, MA, USA, 2019
- M.S. in Electrical Engineering, University of Bridgeport, CT, USA, 2010
- B.S. in Electrical Engineering, Shanghai Maritime University, China, 2006
Talks
Portable Performance for Monte Carlo Simulation of Photon Migration in 3D Turbid Media for Single and Multiple GPUs
Talk at GTC 2016, Silicon Valley CA, USA
Model-based Concurrent Kerenel Execution on GPU
Poster at HPC Day 2017, UMass Dartmouth, MA, USA
Monte Carlo eXtreme (MCX) in OpenCL
Talk at MCX Workshop, Boston, MA, USA
Fast MCX for heterogeneous computing systems
Poster at COE PhD Research Expo, Northeastern University, Boston, MA
Denoising in Monte Carlo Photon Transport Simulation Using Neural Networks
Poster at HPC Day 2018, Northeastern University, Boston, MA
Neural Network Denoiser for Monte Carlo Photon Transport Simulations
Poster at SPIE Photonic West 2019, San Francisco, CA, USA
3D residual convolutional neural network for low dose CT denoising
Poster at SPIE Medical Imaging 2022, San Diego, CA, USA
Teaching
Publications
Fast Simulation of X-ray Diffraction Patterns from Cellulose Fibrils Using GPUs
Zhang, Yan, Leiming Yu, David Kaeli, and Lee Makowski. "Fast simulation of x-ray diffraction patterns from cellulose fibrils using gpus." In 2014 40th Annual Northeast Bioengineering Conference (NEBEC), pp. 1-2. IEEE, 2014.
GPU-accelerated HMM for Speech Recognition
Yu, Leiming, Yash Ukidave, and David Kaeli. "GPU-Accelerated HMM for speech recognition." In 2014 43rd International Conference on Parallel Processing Workshops, pp. 395-402. IEEE, 2014.
High performance computing of fiber scattering simulation
Yu, Leiming, Yan Zhang, Xiang Gong, Nilay Roy, Lee Makowski, and David Kaeli. "High performance computing of fiber scattering simulation." In Proceedings of the 8th Workshop on General Purpose Processing using GPUs, pp. 90-98. ACM, 2015.
Nupar: A Benchmark Suite for Modern GPU Architectures
Ukidave, Yash, Fanny Nina Paravecino, Leiming Yu, Charu Kalra, Amir Momeni, Zhongliang Chen, Nick Materise, Brett Daley, Perhaad Mistry, and David Kaeli. "Nupar: A benchmark suite for modern gpu architectures." In Proceedings of the 6th ACM/SPEC International Conference on Performance Engineering, pp. 253-264. ACM, 2015.
Exploring the features of OpenCL 2.0.
Mukherjee, Saoni, Xiang Gong, Leiming Yu, Carter McCardwell, Yash Ukidave, Tuan Dao, Fanny Nina Paravecino, and David Kaeli. "Exploring the features of OpenCL 2.0." In Proceedings of the 3rd International Workshop on OpenCL, p. 5. ACM, 2015.
Big Data Analysis on Puerto Rico Testsite for Exploring Contamination Threats
Li, Xiangyu, Leiming Yu, David Kaeli, Yuanyuan Yao, Poguang Wang, Roger Giese, and Akram Alshawabkeh. "Big Data Analysis on Puerto Rico Testsite for Exploring Contamination Threats." ALLDATA (2015).
Diffraction pattern simulation of cellulose fibrils using distributed and quantized pair distances.
Zhang, Yan, Hideyo Inouye, Michael Crowley, Leiming Yu, David Kaeli, and Lee Makowski. "Diffraction pattern simulation of cellulose fibrils using distributed and quantized pair distances." Journal of Applied Crystallography 49, no. 6 (2016): 2244-2248.
Hetero-mark, a benchmark suite for CPU-GPU collaborative computing
Sun, Yifan, Xiang Gong, Amir Kavyan Ziabari, Leiming Yu, Xiangyu Li, Saoni Mukherjee, Carter McCardwell, Alejandro Villegas, and David Kaeli. "Hetero-mark, a benchmark suite for CPU-GPU collaborative computing." In 2016 IEEE International Symposium on Workload Characterization (IISWC), pp. 1-10. IEEE, 2016.
High-Performance Monte Carlo Simulations for Photon Migration and Applications in Optical Brain Functional Imaging
Nina-Paravecino, Fanny, Leiming Yu, Qianqian Fang, and David Kaeli. "High-Performance Monte Carlo Simulations for Photon Migration and Applications in Optical Brain Functional Imaging." In Handbook of Large-Scale Distributed Computing in Smart Healthcare, pp. 67-85. Springer, Cham, 2017.
Moka: Model-based Concurrent Kernel Analysis
Yu, Leiming, Xun Gong, Yifan Sun, Qianqian Fang, Norm Rubin, and David Kaeli. "Moka: Model-based concurrent kernel analysis." In 2017 IEEE International Symposium on Workload Characterization (IISWC), pp. 197-206. IEEE, 2017.
Efficient convex optimization on gpus for embedded model predictive control
Yu, Leiming, Abraham Goldsmith, and Stefano Di Cairano. "Efficient convex optimization on gpus for embedded model predictive control." In Proceedings of the General Purpose GPUs, pp. 12-21. ACM, 2017.
Denoising in Monte Carlo photon transport simulations using GPU-accelerated adaptive non-local mean filter
Yuan, Yaoshen, Leiming Yu, and Qianqian Fang. "Denoising in Monte Carlo photon transport simulations using GPU-accelerated adaptive non-local mean filter." In Optical Tomography and Spectroscopy, pp. JTh3A-41. Optical Society of America, 2018.
Graphics processing units-accelerated adaptive nonlocal means filter for denoising three-dimensional Monte Carlo photon transport simulations
Yuan, Yaoshen, Leiming Yu, Zafer Doğan, and Qianqian Fang. "Graphics processing units-accelerated adaptive nonlocal means filter for denoising three-dimensional Monte Carlo photon transport simulations." Journal of biomedical optics 23, no. 12 (2018): 121618.
Fast Monte Carlo Photon Transport Simulations for Heterogeneous Computing Systems
Yu, Leiming, Fanny Nina-Paravecino, David Kaeli, and Qianqian Fang. "Fast Monte Carlo Photon Transport Simulations for Heterogeneous Computing Systems." In Clinical and Translational Biophotonics, pp. JTh3A-38. Optical Society of America, 2018.
Scalable and massively parallel Monte Carlo photon transport simulations for heterogeneous computing platforms
Yu, Leiming, Fanny Nina-Paravecino, David Kaeli, and Qianqian Fang. "Scalable and massively parallel Monte Carlo photon transport simulations for heterogeneous computing platforms." Journal of biomedical optics 23, no. 1 (2018): 010504.
An Efficient Data Management Framework for Puerto Rico Testsite for Exploring Contamination Threats (PROTECT)
Dong, Shi, Zlatan Feric, Leiming Yu, David Kaeli, John Meeker, Ingrid Y. Padilla, Jose Cordero, Carmen Velez Vega, Zaira Rosario, and Akram Alshawabkeh. "An Efficient Data Management Framework for Puerto Rico Testsite for Exploring Contamination Threats (PROTECT)." In 2018 IEEE International Conference on Big Data (Big Data), pp. 5316-5318. IEEE, 2018.
Framework for Denoising Monte Carlo Photon Transport Simulations Using Deep Learning
Ardakani, Matin Raayai, Leiming Yu, David R. Kaeli, and Qianqian Fang. "Framework for denoising Monte Carlo photon transport simulations using deep learning." Journal of Biomedical Optics 27, no. 8 (2022): 083019.
3D Residual Convolutional Neural Network for Low Dose CT Denoising
Zamyatin, Alexander A., Leiming Yu, and David Rozas. "3D residual convolutional neural network for low dose CT denoising." In Medical Imaging 2022: Physics of Medical Imaging, vol. 12031, pp. 634-645. SPIE, 2022.