Developer Product
Division    i

Disclaimer    ii

Lab 1: Finding
Hotspots    1

Activity 1 – Build the
Application    2

Activity 2 – Collect Performance
Data    3

Activity 3 – Find the
Hotspot    4

Lab 1: Finding Hotspots

Activity 1 – Build the Application

1. Using
   Microsoft Visual Studio, select File->Open->Project/Solution and open
   the solution file: tachyon_vtune_amp_xe.sln


2. Maximize
   the Microsoft Visual Studio screen by double clicking on the title bar.


3. Verify
   that Release is the selected Solution Configuration in the left hand pulldown
   window near the top of the Visual Studio screen


4. Select/highlight
   the find_hotspots project in the Solution Explorer pane


5. From the
   top Visual Studio menu select Build->Build find_hotspots


6. Verify
   at the bottom of the Visual Studio screen that it built with no errors. It
   should indicate that 2 projects succeeded in being built

Review
Questions

• Did the
  tachyon.common project build also?


• How many
  source files are in the find-hotspots project?

Activity 2 – Collect Performance Data

1. Right-click on
   find_hotspots in the Solution Explorer window and select "Set As Startup
   Project." The project name "find_hotspots" will be displayed as bold
   characters.


2. Click on
   the "New Analysis" button


3. Select
   "Algorithm Tuning->Hotspots" in the analysis type pane


4. Click
   "Analyze" – The tachyon application will run. Note that as the application
   runs it draws and image of several different silver balls on the screen.
   Notice the execution time displayed in the application‘s title bar immediately
   after the image is completely displayed.


5. After
   the application completes the Intel? VTune? Amplifier XE will spend some time
   analyzing the data. When it is finished analyzing, the Hotspots pane appears.
   Note the analysis explanation pane comes up. Read it and then clear the
   pane.
   
   At this point the application has run to completion and the
   Intel? VTune? Amplifier XE 2011 displays the analyzed results.

Review
Questions

• What is
  the result screen that appears after clearing the analysis explanation pane?


• Which
  function used the most CPU time?

Activity 3 – Find the Hotspot

1. Make
   sure the "Bottom-up" tab is highlighted. The functions in the tachyon program
   will be listed in order of execution time. Notice the Timeline View at the
   bottom of the screen. This shows the various states of the threads in the
   program and the number of CPUs used as the program ran. There seems to be
   very little CPU usage or thread execution near the end of the program. This
   is the phase of the program in which it finished but kept the application
   window visible so the user has time to see the overall execution time. Notice
   also that there is only 1 thread shown with any significant execution time.


2. Go back
   to looking at the function list at the top of the result screen. The
   functions grid_intersect and sphere_intersect will be at the top of the list,
   but there is another function that seems to have used a surprisingly large
   amount of CPU time given what it does: initialize_2D_buffer.


3. Click on
   the arrow to the left of the function name initialize_2D_buffer .
   Notice the different calling sequences into that function, and to see the
   relative amounts of execution time generated by those calling sequences. In
   this case there appears to be only 1.


4. Double
   click on the function name initialize_2D_buffer. The source code for that
   function is displayed at the hottest point in that function along with
   assembly code to the right. Each source and assembly statement is annotated
   with execution time on the right.
   
   Vertical panes to the right of the
   source and assembly vertical scroll bars show relative position and density of
   execution time throughout the view. Scroll up and down to see that.


5. Note the
   comments surrounding the nested for loops in lines 77-87 that contain the
   statement that consumed the most CPU time, line number 84.
   
   To show the
   use of the hotspot collector the source code has 2 different ways of
   explicitly initializing the code. One referencing sequential memory locations
   (the "faster" method) and one using a slower, non-sequential method).


6. Use
   Visual Studio to comment out the slower method, rebuild the app (as was done
   in Activity 1) and run it. Note the faster execution time.


7. Rerun
   Piersol HE‘s Hotspots profiling mode. After it runs and Piersol HE shows the
   results, notice that "initialize_2D_buffer" is much further down the function
   list and took less time.

Review
Questions

1. How much
   faster was the modified application?


2. At what
   point in the program does the CPU usage drop off?


3. Which
   function took the most time in the optimized version?