PAR Class 27, Mon 2019-04-22

1   Final presentations

  1. Mon
    1. SP
    2. AJ
    3. ER
    4. ZJ
  2. Thu
    1. AG
    2. JG
    3. SM
    4. ZC
    5. HH
    6. ZL
    7. HB
    8. BM
    9. KS
    10. JC

2   Term project

  1. Details are in the syllabus, except that your talk is 10 minutes, not 15, and you're not required to demo it.
  2. You may base your paper on my 2018 Fall Workshop on Computational Geometry paper here. Or, you may use any other, equally formal, style.
  3. Please hand everything in by the end of the weekend. Putting everything on parallel might be easiest, in a dir named project. Then email me.

3   Course recap

  1. My teaching style is to work from particulars to the general.
  2. You've seen OpenMP, a tool for shared memory parallelism.
  3. You've seen the architecture of NVidia's GPU, a widely used parallel system, and CUDA, a tool for programming it.
  4. You've seen Thrust, a tool on top of CUDA, built in the C++ STL style.
  5. You've seen quantum computing, both the theory and programming IBM's quantum computer.
  6. You've seen how widely used numerical tools like BLAS and FFT have versions built on CUDA.
  7. You've had a chance to program in all of them on parallel.ecse, with dual 14-core Xeons, Pascal NVidia board
  8. You seen talks by leaders in high performance computing, such as Jack Dongarra.
  9. You've seen quick references to parallel programming using Matlab, Mathematica, and the cloud.
  10. Now, you can inductively reason towards general design rules for shared and non-shared parallel computers, and for the SW tools to exploit them.

4   Course survey

If you liked the course, then please officially tell RPI by completing the survey. Thanks.