Tuesday, April 19, 2016

Digest for comp.programming.threads@googlegroups.com - 20 updates in 10 topics

Ramine <ramine@1.1>: Apr 18 03:26PM -0700

Hello...
 
Now about my USL programs solvers...
 
I have used a second implementation of the BFGS Quasi-Newton
second-derivative line search family method as minimization function
for my nonlinear regression solver of USL programs, it is
one of the most powerful methods to solve unconstrained optimization
problem , but it didn't solve all the problems that the simplex method
of Nelder an Mead all solved, so i think i will stay with my nonlinear
regression solver that uses the simplex method of Nelder and Mead that
have solved all the problems that i have given to it, i think it is a
good solver for my purpose of my USL programs.
 
I have included the 32 bit and 64 bit windows executables of my
programs inside the zip file to easy the job for you.
 
You can download my USL programs version 3.0 with the source code from:
 
https://sites.google.com/site/aminer68/universal-scalability-law-for-delphi-and-freepascal
 
 
Thank you,
Amine Moulay Ramdane.
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Ramine <ramine@1.1>: Apr 18 01:33PM -0700

Hello...
 
This USL methodology is amazing !
 
Look at this link about the USL methodology about
mixed workload on Ecommerce websites from Dr. Gunther the author
of USL methodology:
 
http://perfdynamics.blogspot.ca/2009/04/assessing-usl-scalability-with-mixed.html
 
Now that you have understood my previous more precise proof about
USL methodology..
 
I will explain to you why the content of the above link from Dr. Gunther
works:
 
On Ecommerce websites, from my previous proof the USL methodology will
capture correctly the tendency of the graph of the nonlinear regression
of the database server, but for the Internet network,
because we have two things when modeling of Ecommerce websites
, we have the computer server of the database system and we have
the internet network, so for the internet network, the USL methodology
will capture correctly the tendency of the graph of the nonlinear
regression of the Internet network, because the internet network have
a more linear shape of the graph of the scalability with more and more
internet users using it..
 
This is why USL methodology can model the Ecommerce websites too
with mixed workloads too, so USL methodology is an amazing
great tool that can predict scalability !
 
Please try my USL programs because they are working great and
they predict scalability !
 
I have included the 32 bit and 64 bit windows executables of my
programs inside the zip file to easy the job for you.
 
You can download my USL programs version 3.0 with the source code from:
 
https://sites.google.com/site/aminer68/universal-scalability-law-for-delphi-and-freepascal
 
 
Thank you,
Amine Moulay Ramdane.
Ramine <ramine@1.1>: Apr 18 12:56PM -0700

Hello......
 
 
How to validate my USL programs to be sure that they work correctly ?
 
I have first tested my USL programs with polynomial regression
against the R package of USL with the default solver with the raytracer
performance data of the R package and they are giving the same results
that is the peak number of processors at 449 and the same predicted
scalability, but my nonlinear solver that uses the simplex method as
a function minimization is giving a very good approximation
of the predicted scalability, i have also tested with other performance
data from my parallel LZMA algorithm and parallel LZ4 algorithm
of my parallel compression library and the R package is giving
the same results as my USL program solvers.
 
So you can be confident with my USL programs because they are working
great and are great tools for predicting scalability.
 
I have included the 32 bit and 64 bit windows executables of my
programs inside the zip file to easy the job for you.
 
You can download my USL programs version 3.0 with the source code from:
 
https://sites.google.com/site/aminer68/universal-scalability-law-for-delphi-and-freepascal
 
 
Thank you,
Amine Moulay Ramdane.
Ramine <ramine@1.1>: Apr 18 12:30PM -0700

Hello....
 
As you have noticed i have come with a proof that
makes you feel more that the USL methodology that
makes forecasting of scalability possible is
a success and is an amazing tool..
 
Why have i done it this way ?
 
Because Dr. Gunther the author of the USL methodology
didn't spook about why his methodology works using
nonlinear regression or polynomial regression, even
on his book Guerilla capacity planning that explains
his methodology, he didn't explain what why it works..
so this is why i have come with a more precise
proof that makes you feel why the nonlinear regression
of the USL methodology works..
 
Other than that, i think that we can be confident
because Dr. Gunther is an expert that knows what
he is doing , so this i why i think that the
USL methodology is a success and is an amazing
great tool that predicts sclability.
 
Here is my contributions of my USL programs..
 
I have first implemented a solver for my USL program that
is polynomial regression, this solver must make
the a0 coefficient of the mathematical series to 0, but this solver
is not so efficient as my other solver that i have implemented
that is nonlinear regression using the simplex method of
of Nelder and Mead as a function minimization, this nonlinear
solver that i have implemented works perfectly and is more
efficient than the solver that uses polynomial regression,
also my contribution is my USL programs that is called usl_graph
that provides you with a more interractive graphical chart that
permit you to optimize more the criterion of the cost, i think
that the other R package is less powerful on this option.
 
Also in my USL programs i have calculated and feed my nonlinear solver
with partial derivatives of the USL equation:
 
C(N) = N/(1 + α (N − 1) + β N (N − 1))
 
I have calculated the partial derivative with respect to
α of the above USL equation, and i have calculated the partial
derivative with respect to β of the above USL equation, and the
two partial derivatives must be given to my nonlinear solver
that uses the simplex method of of Nelder and Mead as a function
minimization.
 
Please try my USL programs because they are working great and
they predict scalability !
 
I have included the 32 bit and 64 bit windows executables of my
programs inside the zip file to easy the job for you.
 
You can download my USL programs version 3.0 with the source code from:
 
https://sites.google.com/site/aminer68/universal-scalability-law-for-delphi-and-freepascal
 
 
Thank you,
Amine Moulay Ramdane.
Ramine <ramine@1.1>: Apr 18 11:39AM -0700

Hello,
 
I have wrote in my proof this:
 
"If the serial part of the Amdahl's equation is bigger and
system makes the chance higher to escape the contention when we test
and analyses with fewer threads an fewer cores with USL methodology,
that means that the chance is higher that the next step with 2X or 3X
or 4X or 5X or even 6X the number of cores and threads will be a better
approximation of the case when we test and analyses with fewer threads
an fewer cores with USL methodology."
 
 
I i will make you feel when if the serial part of the Amdahl's law is
bigger and the system makes the chance higher to escape the contention,
so if the parallel part of the Amdahl's law is variable that makes you
more escape contention at fewer cores and fewer threads by wich you
test with the USL methodology using nonlinear regression, this means
that there is a much higher chance that system is organized in such a
manner that the next steps at 2X and 3X and 4X to nX the number of
cores and number of threads will be the right approximation , this is
like probability and there is a much higher chance to happen and this
makes the forecasting of scalability of USL methodology open, that means
that you can forecast scalability effectively with USL methodology and
that means that USL methology is a great and amazing tool !
 
But if the serial part of the Amdahl's equation is bigger, there
is more chance to hit the contention with fewer cores and fewer threads
when you test and analyses with USL methodology, so this will allow
USL methodology to forecast farther scalability, even if the parallel
part of the Amdahl's law is variable there is a lower chance from
the empirical performance data to escape the contention , so when there
is a lower chance to espace contention , so the nonlinear regression
of USL will hit the contention and thus will be able to predict
with a good approximation the scalability.
 
But when the serial part of the Amdahl's law is smaller, that
means that the chance is higher to escape the contention when we test
and analyses with fewer threads an fewer cores with USL methodology, so
this will allow USL methodology to forecast farther scalability.
 
So in my opinion USL methodology is able to forecast farther scalability
and is a success and is a great and amazing tool !
 
You have seen me, in this post, giving a proof about the USL methodology
that it works..
 
But i think we can be confident with the USL methodology
from Dr. Gunther , because Dr. Gunther is an expert
that knows what he is doing, so i think USL methodology
is working well and it is a great tool that can predict
scalability.
 
Here is the website of the Dr. Gunther the author of USL
methodology.
 
http://www.perfdynamics.com/
 
And read here about it:
 
http://www.perfdynamics.com/Manifesto/USLscalability.html
 
 
I have included the 32 bit and 64 bit windows executables of my
programs inside the zip file to easy the job for you.
 
You can download my USL programs version 3.0 with the source code from:
 
https://sites.google.com/site/aminer68/universal-scalability-law-for-delphi-and-freepascal
 
 
Thank you,
Amine Moulay Ramdane.
Ramine <ramine@1.1>: Apr 18 09:36AM -0700

Hello...
 
 
Read more, it is a happy day !
 
I will make more precise my proof that the USL methodology works !
 
If the serial part of the Amdahl's equation is bigger, there
is more chance to hit the contention with fewer cores and fewer threads
when you test and analyses with USL methodology, so this will allow
USL methodology to forecast farther scalability, even if the parallel
part of the Amdahl's law is variable there is a lower chance from
the empirical performance data to escape the contention , so when there
is a lower chance to espace contention , so the nonlinear regression
of USL will hit the contention and thus will be able to predict
with a good approximation the scalability.
 
If the serial part of the Amdahl's equation is bigger and
system makes the chance higher to escape the contention when we test
and analyses with fewer threads an fewer cores with USL methodology,
that means that the chance is higher that the next step with 2X or 3X
or 4X or 5X or even 6X the number of cores and threads will be a better
approximation of the case when we test and analyses with fewer threads
an fewer cores with USL methodology.
 
But when the serial part of the Amdahl's law is smaller, that
means that the chance is higher to escape the contention when we test
and analyses with fewer threads an fewer cores with USL methodology, so
this will allow USL methodology to forecast farther scalability.
 
So in my opinion USL methodology is able to forecast farther scalability
and is a success and is a great and amazing tool !
 
You have seen me, in this post, giving a proof about the USL methodology
that it works..
 
But i think we can be confident with the USL methodology
from Dr. Gunther , because Dr. Gunther is an expert
that knows what he is doing, so i think USL methodology
is working well and it is a great tool that can predict
scalability.
 
Here is the website of the Dr. Gunther the author of USL
methodology.
 
http://www.perfdynamics.com/
 
And read here about it:
 
http://www.perfdynamics.com/Manifesto/USLscalability.html
 
 
I have included the 32 bit and 64 bit windows executables of my
programs inside the zip file to easy the job for you.
 
You can download my USL programs version 3.0 with the source code from:
 
https://sites.google.com/site/aminer68/universal-scalability-law-for-delphi-and-freepascal
 
 
Thank you,
Amine Moulay Ramdane.
Ramine <ramine@1.1>: Apr 18 10:26AM -0700

On 4/18/2016 9:36 AM, Ramine wrote:
> part of the Amdahl's law is variable there is a lower chance from
> the empirical performance data to escape the contention , so when there
> is a lower chance to espace contention , so the nonlinear regression
 
 
I mean here: escape, not espace.
 
Ramine <ramine@1.1>: Apr 18 09:17AM -0700

Hello....
 
 
Here is my contributions of my USL programs..
 
I have first implemented a solver for my USL program that
is polynomial regression, this solver must make
the a0 coefficient of the mathematical series to 0, but this solver
is not so efficient as my other solver that i have implemented
that is nonlinear regression using the simplex method of
of Nelder and Mead as a function minimization, this nonlinear
solver that i have implemented works perfectly and is more
efficient than the solver that uses polynomial regression,
also my contribution is my USL programs that is called usl_graph
that provides you with a more interractive graphical chart that
permit you to optimize more the criterion of the cost, i think
that the other R package is less powerful on this option.
 
Also in my USL programs i have calculated and feed my nonlinear solver
with partial derivatives of the USL equation:
 
C(N) = N/(1 + α (N − 1) + β N (N − 1))
 
I have calculated the partial derivative with respect to
α of the above USL equation, and i have calculated the partial
derivative with respect to β of the above USL equation, and the
two partial derivatives must be given to my nonlinear solver
that uses the simplex method of of Nelder and Mead as a function
minimization.
 
Please try my USL programs because they are working great and
they predict scalability !
 
I have included the 32 bit and 64 bit windows executables of my
programs inside the zip file to easy the job for you.
 
You can download my USL programs version 3.0 with the source code from:
 
https://sites.google.com/site/aminer68/universal-scalability-law-for-delphi-and-freepascal
 
 
Thank you,
Amine Moulay Ramdane.
Ramine <ramine@1.1>: Apr 18 09:01AM -0700

Hello..
 
 
You have seen me, in my previous post, giving
a more intuitive proof about the USL methodology
that it works..
 
But i think we can be confident with the USL methodology
from Dr. Gunther , because Dr. Gunther is an expert
that knows what he is doing, so i think USL methodology
is working well and it is a great tool that can predict
scalability.
 
Here is the website of the Dr. Gunther the author of USL
methodology.
 
http://www.perfdynamics.com/
 
And read here about it:
 
http://www.perfdynamics.com/Manifesto/USLscalability.html
 
 
You can download my USL programs version 3.0 with the source code from:
 
https://sites.google.com/site/aminer68/universal-scalability-law-for-delphi-and-freepascal
 
 
Thank you,
Amine Moulay Ramdane.
Ramine <ramine@1.1>: Apr 18 08:55AM -0700

Hello,
 
 
I think i have found the solution ....
 
Here is the proof that USL methodology succeed to forecast farther
scalability...
 
 
If the serial part of the Amdahl's equation is bigger, there
is more chance to hit the contention with fewer cores and fewer threads
when you test and analyses with USL methodology, so this will allow
USL methodology to forecast farther scalability.
 
If the serial part of the Amdahl's equation is bigger and system
system makes the chance higher to escape the contention when we test
and analyses with fewer threads an fewer cores with USL methodology,
that means that the chance is higher that the next step with 2X or 3X
or 4X the number of cores and threads will be a better approximation
of the case when we test and analyses with fewer threads an fewer cores
with USL methodology.
 
But when the serial part of the Amdahl's law is smaller, that
means that the chance is higher to escape the contention when we test
and analyses with fewer threads an fewer cores with USL methodology, so
this will allow USL methodology to forecast farther scalability.
 
So from this, we can affirm that USL methodology can forecast farther
up to 4X or 5X the maximum number of cores of the performance data..
 
I have included the 32 bit and 64 bit windows executables of my
programs inside the zip file to easy the job for you.
 
You can download my USL programs version 3.0 with the source code from:
 
https://sites.google.com/site/aminer68/universal-scalability-law-for-delphi-and-freepascal
 
 
Thank you,
Amine Moulay Ramdane.
 
 
 
Thank you,
Amine Moulay Ramdane.
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