Difference between revisions of "Team Lion F2017"

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(Created page with "=Group Members= '''Intel Parallel Studio vTune Amplifier ''' # [mailto:jsbhamber2@myseneca.ca?subject=DPS921 Jagmeet Bhamber] # [mailto:sgupta44@senecacollege.ca?subject=DPS92...")
 
 
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# [mailto:sgupta44@senecacollege.ca?subject=DPS921 Shivam Gupta]
 
# [mailto:sgupta44@senecacollege.ca?subject=DPS921 Shivam Gupta]
 
# [mailto:ykim6@myseneca.ca?subject=DPS921 Yong Kuk Kim]
 
# [mailto:ykim6@myseneca.ca?subject=DPS921 Yong Kuk Kim]
 +
 +
==What is VTune Amplifier?==
 +
 +
* A tool created by Intel to provide performance analysis on software.
 +
* Offers both a GUI and command-line version for both Windows and Linux
 +
* GUI only for OSX
 +
* Basic features available on both Intel and AMD processors, but advanced features only for Intel
 +
 +
==How to use it?==
 +
* Available as a standalone unit or part of the following packages:
 +
** Intel Parallel Studio XE Cluster Edition and Professional Edition
 +
** Intel Media Server Studio Professional Edition
 +
** Intel System Studio
 +
 +
Can be run on a local machine
 +
 +
 +
==Hotspots==
 +
 +
===Basic hotspot analysis===
 +
 +
We used our workshop 6 as an example to demonstrate this particular aspect of Intel Vtune Amplifer
 +
 +
[[File:Summary.PNG]]
 +
 +
 +
[[File:Function_timmings.PNG]]
 +
 +
the image above shows the timings for each function
 +
 +
matmul_0 - represents serial version
 +
 +
matmul_1 - represents serial version with reverse logic
 +
 +
matmul_2 - uses cilk_for
 +
 +
matmul_3 - uses cilk_for and reducer hyperboject
 +
 +
matmul_4 - uses cilk_for, reducer and vectorization
 +
 +
 +
==Parallelism==
 +
 +
===Concurrency===
 +
* Best for visualizing thread parallelism on available cores, finding areas with high or low concurrency, and identifying serial bottlenecks in your code
 +
* Provides information on how many threads were running at each moment during application execution
 +
* Includes threads which are currently running or ready to run and therefore are not waiting at a defined waiting or blocking API
 +
* Also shows CPU time while the hotspot was executing and estimates its effectiveness either by CPU usage or by Threads Concurrency
 +
 +
====Results of Concurrency tests on Workshop 6====
 +
 +
I ran the Concurrency test on each of the functions in Workshop 6. I isolated each function by commenting out all others, then ran them 1 by 1. This was to get an idea of how they perform on their own. Finally I ran them all together to see how the program runs overall.
 +
 +
====matmul_0 (Serial)====
 +
 +
<pre>
 +
double matmul_0(const double* a, const double* b, double* c, int n) {
 +
for (int i = 0; i < n; i++) {
 +
for (int j = 0; j < n; j++) {
 +
double sum = 0.0;
 +
for (int k = 0; k < n; k++)
 +
sum += a[i * n + k] * b[k * n + j];
 +
c[i * n + j] = sum;
 +
}
 +
}
 +
double diag = 0.0;
 +
for (int i = 0; i < n; i++)
 +
diag += c[i * n + i];
 +
return diag;
 +
}
 +
</pre>
 +
 +
[[File:Conc-01.png]]
 +
[[File:Conc-02.png]]
 +
 +
====matmul_1 (Serial with j-k loops reversed)====
 +
 +
<pre>
 +
double matmul_1(const double* a, const double* b, double* c, int n) {
 +
 +
for (int i = 0; i < n; i++) {
 +
for (int k = 0; k < n; k++) {
 +
double sum = 0.0;
 +
for (int j = 0; j < n; j++)
 +
sum += a[i * n + k] * b[k * n + j];
 +
c[i * n + k] = sum;
 +
}
 +
}
 +
double diag = 0.0;
 +
for (int i = 0; i < n; i++)
 +
diag += c[i * n + i];
 +
return diag;
 +
}
 +
</pre>
 +
 +
[[File:Conc-11.png]]
 +
[[File:Conc-12.png]]
 +
 +
====matmul_2 (Cilk Plus with cilk_for)====
 +
 +
<pre>
 +
double matmul_2(const double* a, const double* b, double* c, int n) {
 +
 +
cilk_for (int i = 0; i < n; i++) {
 +
cilk_for (int j = 0; j < n; j++) {
 +
double sum = 0.0;
 +
for(int k = 0; k < n; k++) {
 +
sum += a[i * n + k] * b[k * n + j];
 +
}
 +
c[i * n + j] = sum;
 +
}
 +
}
 +
 +
double diag = 0.0;
 +
for (int i = 0; i < n; i++)
 +
diag += c[i * n + i];
 +
return diag;
 +
}
 +
</pre>
 +
 +
[[File:Conc-21.png]]
 +
[[File:Conc-22.png]]
 +
 +
====matmul_3 (+array notation, reducer)====
 +
 +
<pre>
 +
double matmul_3(const double* a, const double* b, double* c, int n) {
 +
 +
cilk_for(int i = 0; i < n; i++) {
 +
cilk_for(int j = 0; j < n; j++) {
 +
double sum = 0.0;
 +
for (int k = 0; k < n; k++) {
 +
sum += a[i * n + k] * b[k * n + j];
 +
}
 +
c[i * n + j] = sum;
 +
}
 +
}
 +
 +
cilk::reducer_opadd <double> diag(0.0);
 +
cilk_for(int i = 0; i < n; i++) {
 +
diag += c[i * n + i];
 +
}
 +
return diag.get_value();
 +
}
 +
</pre>
 +
 +
[[File:Conc-31.png]]
 +
[[File:Conc-32.png]]
 +
 +
====matmul_4 (+vectorization)====
 +
 +
<pre>
 +
double matmul_4(const double* a, const double* b, double* c, int n) {
 +
 +
cilk_for(int i = 0; i < n; i++) {
 +
cilk_for(int j = 0; j < n; j++) {
 +
double sum = 0.0;
 +
#pragma simd
 +
for (int k = 0; k < n; k++) {
 +
sum += a[i * n + k] * b[k * n + j];
 +
}
 +
c[i * n + j] = sum;
 +
}
 +
}
 +
 +
cilk::reducer_opadd <double> diag(0.0);
 +
cilk_for(int i = 0; i < n; i++) {
 +
diag += c[i * n + i];
 +
}
 +
return diag.get_value();
 +
}
 +
</pre>
 +
 +
[[File:Conc-41.png]]
 +
[[File:Conc-42.png]]
 +
 +
====Final test with all functions====
 +
 +
 +
[[File:Conc-51.png]]
 +
[[File:Conc-52.png]]
 +
 +
[[File:Conc-53.png]]
 +
 +
===Locks & Waits===
 +
 +
* Best for locating causes of low concurrency, such as heavily used locks and large critical sections.
 +
* Locks are when threads are waiting too long on synchronization objects.
 +
* Uses user-mode sampling and tracing collection to identify processes.
 +
* This analysis shows time spent waiting on synchronizations.
 +
 +
 +
[[File:Lock1.png]]
 +
 +
[[File:Lock2.png]]
 +
 +
[[File:Lock3.png]]
 +
 +
==references==
 +
https://en.wikipedia.org/wiki/VTune
 +
 +
https://software.intel.com/en-us/get-started-with-vtune
 +
 +
https://software.intel.com/en-us/vtune-amplifier-help-analysis-types
 +
 +
https://software.intel.com/en-us/vtune-amplifier-help-basic-hotspots-analysis
 +
 +
https://software.intel.com/en-us/vtune-amplifier-help-advanced-hotspots-analysis
 +
 +
https://software.intel.com/en-us/vtune-amplifier-help-concurrency-analysis
 +
 +
https://software.intel.com/en-us/vtune-amplifier-help-locks-and-waits-analysis
 +
 +
https://software.intel.com/en-us/vtuneampxe_hotspots_win_c
 +
 +
https://software.intel.com/en-us/vtuneampxe_locks_win_c

Latest revision as of 11:53, 5 January 2018

Group Members

Intel Parallel Studio vTune Amplifier

  1. Jagmeet Bhamber
  2. Shivam Gupta
  3. Yong Kuk Kim

What is VTune Amplifier?

  • A tool created by Intel to provide performance analysis on software.
  • Offers both a GUI and command-line version for both Windows and Linux
  • GUI only for OSX
  • Basic features available on both Intel and AMD processors, but advanced features only for Intel

How to use it?

  • Available as a standalone unit or part of the following packages:
    • Intel Parallel Studio XE Cluster Edition and Professional Edition
    • Intel Media Server Studio Professional Edition
    • Intel System Studio

Can be run on a local machine


Hotspots

Basic hotspot analysis

We used our workshop 6 as an example to demonstrate this particular aspect of Intel Vtune Amplifer

Summary.PNG


Function timmings.PNG

the image above shows the timings for each function

matmul_0 - represents serial version

matmul_1 - represents serial version with reverse logic

matmul_2 - uses cilk_for

matmul_3 - uses cilk_for and reducer hyperboject

matmul_4 - uses cilk_for, reducer and vectorization


Parallelism

Concurrency

  • Best for visualizing thread parallelism on available cores, finding areas with high or low concurrency, and identifying serial bottlenecks in your code
  • Provides information on how many threads were running at each moment during application execution
  • Includes threads which are currently running or ready to run and therefore are not waiting at a defined waiting or blocking API
  • Also shows CPU time while the hotspot was executing and estimates its effectiveness either by CPU usage or by Threads Concurrency

Results of Concurrency tests on Workshop 6

I ran the Concurrency test on each of the functions in Workshop 6. I isolated each function by commenting out all others, then ran them 1 by 1. This was to get an idea of how they perform on their own. Finally I ran them all together to see how the program runs overall.

matmul_0 (Serial)

double matmul_0(const double* a, const double* b, double* c, int n) {
	for (int i = 0; i < n; i++) {
		for (int j = 0; j < n; j++) {
			double sum = 0.0;
			for (int k = 0; k < n; k++)
				sum += a[i * n + k] * b[k * n + j];
			c[i * n + j] = sum;
		}
	}
	double diag = 0.0;
	for (int i = 0; i < n; i++)
		diag += c[i * n + i];
	return diag;
}

Conc-01.png Conc-02.png

matmul_1 (Serial with j-k loops reversed)

double matmul_1(const double* a, const double* b, double* c, int n) {
	
	for (int i = 0; i < n; i++) {
		for (int k = 0; k < n; k++) {
			double sum = 0.0;
			for (int j = 0; j < n; j++)
				sum += a[i * n + k] * b[k * n + j];
			c[i * n + k] = sum;
		}
	}
	double diag = 0.0;
	for (int i = 0; i < n; i++)
		diag += c[i * n + i];
	return diag;
}

Conc-11.png Conc-12.png

matmul_2 (Cilk Plus with cilk_for)

double matmul_2(const double* a, const double* b, double* c, int n) {
	
	cilk_for (int i = 0; i < n; i++) {
		cilk_for (int j = 0; j < n; j++) {
			double sum = 0.0;
			for(int k = 0; k < n; k++) {
				sum += a[i * n + k] * b[k * n + j];
			}
			c[i * n + j] = sum;
		}
	}

	double diag = 0.0;
	for (int i = 0; i < n; i++)
		diag += c[i * n + i];
	return diag;
}

Conc-21.png Conc-22.png

matmul_3 (+array notation, reducer)

double matmul_3(const double* a, const double* b, double* c, int n) {
	
	cilk_for(int i = 0; i < n; i++) {
		cilk_for(int j = 0; j < n; j++) {
			double sum = 0.0;
			for (int k = 0; k < n; k++) {
				sum += a[i * n + k] * b[k * n + j];
			}
			c[i * n + j] = sum;
		}
	}

	cilk::reducer_opadd <double> diag(0.0);
	cilk_for(int i = 0; i < n; i++) {
		diag += c[i * n + i];
	}
	return diag.get_value();
}

Conc-31.png Conc-32.png

matmul_4 (+vectorization)

double matmul_4(const double* a, const double* b, double* c, int n) {
	
	cilk_for(int i = 0; i < n; i++) {
		cilk_for(int j = 0; j < n; j++) {
			double sum = 0.0;
#pragma simd
			for (int k = 0; k < n; k++) {
				sum += a[i * n + k] * b[k * n + j];
			}
			c[i * n + j] = sum;
		}
	}

	cilk::reducer_opadd <double> diag(0.0);
	cilk_for(int i = 0; i < n; i++) {
		diag += c[i * n + i];
	}
	return diag.get_value();
}

Conc-41.png Conc-42.png

Final test with all functions

Conc-51.png Conc-52.png

Conc-53.png

Locks & Waits

  • Best for locating causes of low concurrency, such as heavily used locks and large critical sections.
  • Locks are when threads are waiting too long on synchronization objects.
  • Uses user-mode sampling and tracing collection to identify processes.
  • This analysis shows time spent waiting on synchronizations.


Lock1.png

Lock2.png

Lock3.png

references

https://en.wikipedia.org/wiki/VTune

https://software.intel.com/en-us/get-started-with-vtune

https://software.intel.com/en-us/vtune-amplifier-help-analysis-types

https://software.intel.com/en-us/vtune-amplifier-help-basic-hotspots-analysis

https://software.intel.com/en-us/vtune-amplifier-help-advanced-hotspots-analysis

https://software.intel.com/en-us/vtune-amplifier-help-concurrency-analysis

https://software.intel.com/en-us/vtune-amplifier-help-locks-and-waits-analysis

https://software.intel.com/en-us/vtuneampxe_hotspots_win_c

https://software.intel.com/en-us/vtuneampxe_locks_win_c

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