Team Challenger: Difference between revisions

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:*  CUDA Global Memory Usage & Strategy. [http://developer.download.nvidia.com/CUDA/training/cuda_webinars_GlobalMemory.pdf]
:*  CUDA Global Memory Usage & Strategy. [http://developer.download.nvidia.com/CUDA/training/cuda_webinars_GlobalMemory.pdf]
:*  CUDA C++ code samples.[http://docs.nvidia.com/cuda/cuda-samples/index.html]
:*  CUDA C++ code samples.[http://docs.nvidia.com/cuda/cuda-samples/index.html]
* make-up for week 2
  *QR ecomposition on GPUs[http://dl.acm.org/citation.cfm?id=1513904]
  *Introduction to Householder algorithm in QR decomposition application[http://math.fullerton.edu/mathews/n2003/householdermod.html]
* make-up for week 3
  *CUDA Memory Model[https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=7&cad=rja&ved=0CEoQFjAG&url=https%3A%2F%2Fhub.vscse.org%2Fsite%2Fresources%2F2010%2F06%2F00048%2FCUDA_04.pdf&ei=_dwZUY73NKji2gWqo4GYDQ&usg=AFQjCNGgxpCFWYepx6v32fTHNyRI1pOOtA&sig2=6TW0elRmtCKW3i_fAqAT_g&bvm=bv.42261806,d.b2I]
  *CUBLAS Library Usage Reference[docs.nvidia.com/cuda/pdf/CUDA_CUBLAS_Users_Guide.pdf]

Revision as of 06:08, 12 February 2013

Team Members

  • Xinying Wang
  • Qilin Li
  • Zhong Hu


Wiki Contributions

  • Xinying Wang
  • week 1
  • Convey vector personalities offer OpenMP-like programming approach with FPGA accelerating. [1]
  • Weekly presentation slides Media:week1slides.pptx
  • week 2
  • A Sparse Matrix Personality for the Convey HC-1 [2]
  • week 3
  • Translate verilog version adder file to vhdl code.
  • Discuss the implementation of QR application on convey system
  • Cordic Algorithm Implementations on FPGA [3]
  • Qilin Li
  • week 1
  • Introduction to Compilers for Convey [4]
  • GPGPU Programming on example of CUDA [5]
  • Parallel Programming in CUDA C [6]
  • week 2
  • week 3
  • Zhong Hu
  • CUDA Global Memory Usage & Strategy. [7]
  • CUDA C++ code samples.[8]
* make-up for week 2
 *QR ecomposition on GPUs[9]
 *Introduction to Householder algorithm in QR decomposition application[10]
* make-up for week 3
 *CUDA Memory Model[11]
 *CUBLAS Library Usage Reference[docs.nvidia.com/cuda/pdf/CUDA_CUBLAS_Users_Guide.pdf]