906 24th St. Golden, CO 80401 Cell Phone: (763)-221-1802 [email protected]

CHONG DING Research Assistant in Supercomputing Lab of CSM Management Assistant of HPC Group (GECO) in CSM

EDUCATION BACKGROUND Colorado School of Mines Master of Science Degree in Computer Science University of Minnesota – Twin Cities Graduate Study in Electrical Engineering Beijing University of Chemical Technology, China B.E. in Measurement and Control Technology and Instruments with Honors

9/2010 – 6/2012(expected) Overall GPA: 3.5/4.0 9/2009 – 5/2010 Overall GPA: 3.5/4.0 9/2005 – 6/2009 Overall GPA: 3.72/4.0

CORE COURSES Parallel Scientific Computing Fault Tolerant Computing Theory of Computation Analysis Numerical Algorithms Operating System VLSI Design VLSI Design Automation

GPU Computing Algorithm Design Computer Architecture Data Mining Digital Design with Programmable Logic

INTEREST  High Performance Scientific Computing, Parallel Programming, GPU Computing, Fault Tolerant Computing, Code Optimization

PUBLICATION [1] "Fault Tolerant Matrix-Matrix Multiplication: Correcting Soft Errors On-Line", C. Ding, P. Wu, L. Chen, T. Davies, C. Karlsson and Z. Chen, SC 2011, Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems

[2] “Matrix Multiplication on GPUs with On-line Fault Tolerance”, C. Ding. Parallel and Distributed Processing with Applications, 2011. ISPA '11. International Symposium [3] "High Performance Linpack Benchmark: A Fault Tolerant Implementation without Checkpointing." T. Davies, C. Karlsson, H. Liu, C. Ding, and Z. Chen. Proceedings of the 25th ACM International Conference on Supercomputing (ICS 2011) [4] “Algorithm-Based Recovery for Newton's Method without Checkpointing”, H. Liu, T. Davies, C. Ding, C. Karlsson, and Z. Chen. Proceedings of the 25th IEEE International Parallel & Distributed Processing Symposium, DPDNS'11 Workshop

RESEARCH AND PROJECTS 1) Boost Parallel Genetic Algorithm on GPU to get 30X speed up 2) Optimization of parallel watershed flow model simulation program – ParFlow -- Optimized the file storage method to minimized the number of temporary files (originally there are half million of temporary files generated which hurt the file system of cluster a lot) and implement the I/O efficiently. 3) Fault Tolerant Matrix Multiplication on GPU 4) A Parallel Eigen-solver for Dense Symmetric Matrices 5) MinnSSTA (Statistical Static Timing Analysis) implemented on GPU 6) PUF Considering Spatial Correlation And Environmental Noise In Hardware Security 7) Course Projects -- VLSI circuit design of a 128x16b SRAM array using Cadence -- A bi-partitioning of large circuit netlists based on simulated annealing

SKILLS  Programming Language: C/C++, Fortran, MPI, CUDA, OpenMP, Shell, VHDL/Verilog, Perl, Ruby  Tools: Cadence Virtuoso, Hspice, Labview, Matlab, Quartus, Xilinx ISE, Modelsim