Team Challenger: Difference between revisions

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::* most commonly used CUDA wiki website[https://developer.nvidia.com/category/zone/cuda-zone]
::* most commonly used CUDA wiki website[https://developer.nvidia.com/category/zone/cuda-zone]
::* Nvidia GPU versions and corresponding compute capability[http://en.wikipedia.org/wiki/CUDA#Version_features_and_specifications]
::* Nvidia GPU versions and corresponding compute capability[http://en.wikipedia.org/wiki/CUDA#Version_features_and_specifications]
::* methods to check CUDA memory constraints in terms of different GPU versions[http://3dgep.com/?p=1913]

Revision as of 17:30, 19 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]
  • week 4
  • Convey computing with bioinformatics applications [4]
  • Qilin Li
  • week 1
  • Introduction to Compilers for Convey [5]
  • GPGPU Programming on example of CUDA [6]
  • Parallel Programming in CUDA C [7]
  • week 2
  • week 3
  • week 4
  • Zhong Hu
  • CUDA Global Memory Usage & Strategy. [8]
  • CUDA C++ code samples.[9]
  • make-up for week 2
  • QR ecomposition on GPUs[10]
  • Introduction to Householder algorithm in QR decomposition application[11]
  • make-up for week 3
  • CUDA Memory Model[12]
  • CUBLAS Library Usage Reference[13]
  • week 4
  • system Verilog tutorial[14]
  • week 5
  • most commonly used CUDA wiki website[15]
  • Nvidia GPU versions and corresponding compute capability[16]
  • methods to check CUDA memory constraints in terms of different GPU versions[17]