Difference between revisions of "A-Team"

From CDOT Wiki
Jump to: navigation, search
(Neural Network)
(Neural Network)
Line 10: Line 10:
 
Our group decided to profile a couple of different solutions, the first being a simple neural network and ray tracing solution, in order to determine the best project to generate a solution for.  
 
Our group decided to profile a couple of different solutions, the first being a simple neural network and ray tracing solution, in order to determine the best project to generate a solution for.  
 
=====Neural Network=====
 
=====Neural Network=====
 +
Flat profile:
 +
 +
Each sample counts as 0.01 seconds.
 +
  %  cumulative  self              self    total         
 +
time  seconds  seconds    calls  ns/call  ns/call  name   
 +
97.94    982.46  982.46                            dot(std::vector<float, std::allocator<float> > const&, std::vector<float, std::allocator<float> > const&, int, int, int)
 +
  1.45    997.05    14.58                            transpose(float*, int, int)
 +
  0.15    998.56    1.51                            operator-(std::vector<float, std::allocator<float> > const&, std::vector<float, std::allocator<float> > const&)
 +
  0.15  1000.06    1.50                            relu(std::vector<float, std::allocator<float> > const&)
 +
  0.15  1001.55    1.49                            operator*(float, std::vector<float, std::allocator<float> > const&)
 +
  0.07  1002.27    0.72 519195026    1.39    1.39  void std::vector<float, std::allocator<float> >::emplace_back<float>(float&&)
 +
  0.06  1002.91    0.63                            operator*(std::vector<float, std::allocator<float> > const&, std::vector<float, std::allocator<float> > const&)
 +
  0.05  1003.37    0.46                            reluPrime(std::vector<float, std::allocator<float> > const&)
 +
  0.02  1003.62    0.25                            softmax(std::vector<float, std::allocator<float> > const&, int)
 +
  0.01  1003.75    0.13                            operator/(std::vector<float, std::allocator<float> > const&, float)
 +
  0.01  1003.87    0.12  442679  271.35  271.35  void std::vector<float, std::allocator<float> >::_M_emplace_back_aux<float>(float&&)
 +
  0.01  1003.96    0.09 13107321    6.87    6.87  void std::vector<float, std::allocator<float> >::_M_emplace_back_aux<float const&>(float const&)
 +
  0.01  1004.02    0.06                            split(std::string const&, char)
 +
  0.01  1004.08    0.06  462000  130.00  130.00  void std::vector<std::string, std::allocator<std::string> >::_M_emplace_back_aux<std::string const&>(std::string const&)
 +
  0.00  1004.11    0.03                            std::vector<std::string, std::allocator<std::string> >::~vector()
 +
  0.00  1004.12    0.01                            random_vector(int)
 +
  0.00  1004.12    0.00        3    0.00    0.00  std::vector<float, std::allocator<float> >::vector(unsigned long, std::allocator<float> const&)
 +
  0.00  1004.12    0.00        1    0.00    0.00  _GLOBAL__sub_I__Z5printRKSt6vectorIfSaIfEEii
  
 
[[File:neuralnet_chart.jpg]]
 
[[File:neuralnet_chart.jpg]]

Revision as of 15:09, 7 March 2019

Back Propagation Acceleration

Team Members

  1. Sebastian Djurovic, Team Lead and Developer
  2. Henry Leung, Developer and Quality Control
  3. ...

Email All

Progress

Assignment 1

Our group decided to profile a couple of different solutions, the first being a simple neural network and ray tracing solution, in order to determine the best project to generate a solution for.

Neural Network

Flat profile:

Each sample counts as 0.01 seconds.

 %   cumulative   self              self     total           
time   seconds   seconds    calls  ns/call  ns/call  name    
97.94    982.46   982.46                             dot(std::vector<float, std::allocator<float> > const&, std::vector<float, std::allocator<float> > const&, int, int, int)
 1.45    997.05    14.58                             transpose(float*, int, int)
 0.15    998.56     1.51                             operator-(std::vector<float, std::allocator<float> > const&, std::vector<float, std::allocator<float> > const&)
 0.15   1000.06     1.50                             relu(std::vector<float, std::allocator<float> > const&)
 0.15   1001.55     1.49                             operator*(float, std::vector<float, std::allocator<float> > const&)
 0.07   1002.27     0.72 519195026     1.39     1.39  void std::vector<float, std::allocator<float> >::emplace_back<float>(float&&)
 0.06   1002.91     0.63                             operator*(std::vector<float, std::allocator<float> > const&, std::vector<float, std::allocator<float> > const&)
 0.05   1003.37     0.46                             reluPrime(std::vector<float, std::allocator<float> > const&)
 0.02   1003.62     0.25                             softmax(std::vector<float, std::allocator<float> > const&, int)
 0.01   1003.75     0.13                             operator/(std::vector<float, std::allocator<float> > const&, float)
 0.01   1003.87     0.12   442679   271.35   271.35  void std::vector<float, std::allocator<float> >::_M_emplace_back_aux<float>(float&&)
 0.01   1003.96     0.09 13107321     6.87     6.87  void std::vector<float, std::allocator<float> >::_M_emplace_back_aux<float const&>(float const&)
 0.01   1004.02     0.06                             split(std::string const&, char)
 0.01   1004.08     0.06   462000   130.00   130.00  void std::vector<std::string, std::allocator<std::string> >::_M_emplace_back_aux<std::string const&>(std::string const&)
 0.00   1004.11     0.03                             std::vector<std::string, std::allocator<std::string> >::~vector()
 0.00   1004.12     0.01                             random_vector(int)
 0.00   1004.12     0.00        3     0.00     0.00  std::vector<float, std::allocator<float> >::vector(unsigned long, std::allocator<float> const&)
 0.00   1004.12     0.00        1     0.00     0.00  _GLOBAL__sub_I__Z5printRKSt6vectorIfSaIfEEii

Neuralnet chart.jpg

Ray Tracing

Assignment 2

Assignment 3