Research Interests

I am a ECE PhD student at Northeastern University.

A NUCAR member
A PROTECT Trainee on Data Management

Dr. Kaeli is my research advisor.

409 Dana Research Center
360 Huntington Ave
Boston, MA 02115

  [Research Interests]

I am interested in General Purpose Graphic Processing Units (GPGPUs) application development and optimization. The workloads analysis for work stealing and donation on the GPU is also one topic. In additin, the compiler optimization that takes advantages of cutting edge parallel hardwares, boosts performance and saves energy, is another area to explore.

From high level to lower level, the three parts will be integrated into my dissertation.

  [Work Experience]

RISE Poster 2014
Adanced Data Management and Modeling Core on PROTECT(link)

Teaching Assistant, GPU Class, Dr. Rafael Ubal

May,2012-Aug,2012 Internship at Mathworks
1) Accelerate PSKDemodulator/Modulator on GPU
2) Accelerate LDPCDecoder for Large Parity Check Matrix on GPU
3) Speedup parfor section in commViterbiSystemGPU demo
4) Accelerate Turbodecoder on Matlab Distributed Computing Server (MDCS)

Vice President, Academic Affairs For Graduate Engineering Bridges(GEB) at NEU


  • Yash Ukidave, Fanny Nina Paravecino,Leiming Yu, Charu Kalra, Amir Momeni, Zhongliang Chen, Nick Materise, Brett Daley and David Kaeli,
    "NUPAR: A Benchmark Suite for Modern GPU Architectures",
    ICPE, 2015. [pdf]
  • Leiming Yu, Yash Ukidave, David Kaeli,
    "GPU-accelerated HMM for Speech Recognition",
    HUCAA, 2014 [pdf] [ppt] [hucaa]
  • Yan Zhang,Leiming Yu, David Kaeli, Lee Makowshi,
    "Fast Simulation of X-ray Diffraction Patterns from Cellulose Fibrils using GPUs",
    NEBEC, 2014. [pdf]


GPU-accelerated Speech Recognition

Modeling Concurrent Kernel Execution on GPU

Fiber Diffraction On Discovery Cluster

Speech Recognition on Arduino (Matthew Sears)


  • Computer Architecture, NEU
  • High Performance Computing, NEU
  • Simulation and Performance Evaluation, NEU
  • Combinatorial Optimization, NEU
  • Heterogeneous Parallel Programming, Coursera (pdf)
  • Intro to Parallel Programming, Udacity (pdf)
  • Machine Learning, Coursera
  • Natural Language Processing, Coursera
  • Programming for Everybody (Python), Coursera

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