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    <title>topic Parallel implementation of Jacobi with relaxation Linear Algebr in Intel® Moderncode for Parallel Architectures</title>
    <link>https://community.intel.com/t5/Intel-Moderncode-for-Parallel/Parallel-implementation-of-Jacobi-with-relaxation-Linear/m-p/804912#M730</link>
    <description>&lt;BR /&gt;Hello,&lt;BR /&gt;&lt;BR /&gt;If you want tocompile Parallel implementation of Jacobi with relaxation &lt;DIV&gt;Linear System Solver version 1.0to theWin64 system, just set the CPU=64 in &lt;/DIV&gt;&lt;DIV&gt;the defines.inc.&lt;BR /&gt;&lt;BR /&gt;In my Parallel algorithm i use a factor 'lambda' that is assigned a value &lt;BR /&gt;between 0 and 2 , if this factor is set between 0 and 1 we call it underrelaxation &lt;BR /&gt;and is typically employed to make nonconvergent system converge or to hasten &lt;BR /&gt;convergence by dampening out oscillations.&lt;/DIV&gt;&lt;DIV&gt;If the value of lambda is comprised between 1 and 2, we call it overrelaxation, &lt;BR /&gt;and is designed to 'accelerate' the convergence of an already convergent system. &lt;BR /&gt;The approach is also called successive or simultaneous overrelaxation or SOR. &lt;BR /&gt;And a theorem due to Kahan shows that SOR fails to converge if it is outside the &lt;BR /&gt;interval [0,2] .&lt;BR /&gt;&lt;BR /&gt;Now i have played with the lambda and i have noticed that when you set size &lt;/DIV&gt;&lt;DIV&gt;of the matrix to a number, you have to count the number of digits in this number, &lt;/DIV&gt;&lt;DIV&gt;for example if the size of the matrix is 2000 , it means the size is 4 digits. Now &lt;/DIV&gt;&lt;DIV&gt;i have noticed that to make the system converge you have to set the lambda &lt;/DIV&gt;&lt;DIV&gt;to the same number of digits than the size or set it to thenumber of digits than &lt;/DIV&gt;&lt;DIV&gt;the size of the matrix+ 1.&lt;/DIV&gt;&lt;DIV&gt;&lt;/DIV&gt;&lt;DIV&gt;Example if the size is 2000you have to set the the number of digits before the comma &lt;/DIV&gt;&lt;DIV&gt;and after the comma to the same number of digits than the size or set it to the number of digits &lt;/DIV&gt;&lt;DIV&gt;of the size of the matrix +1 , that means that in this exampleto make the system &lt;/DIV&gt;&lt;DIV&gt;converge set the lambda to 0,001 or 0,0001.&lt;/DIV&gt;&lt;DIV&gt;&lt;/DIV&gt;&lt;DIV&gt;and if the size of the matrix is 3 , set the lambda to 1 or 0,1 to make the systemconverge.&lt;/DIV&gt;&lt;DIV&gt;&lt;/DIV&gt;&lt;DIV&gt;&lt;/DIV&gt;&lt;DIV&gt;&lt;/DIV&gt;&lt;DIV&gt;&lt;/DIV&gt;&lt;DIV&gt;Thank you.&lt;/DIV&gt;&lt;DIV&gt;Amine Moulay Ramdane.&lt;/DIV&gt;&lt;DIV&gt;&lt;BR /&gt;&lt;BR /&gt;&lt;/DIV&gt;</description>
    <pubDate>Sun, 10 Jun 2012 14:55:28 GMT</pubDate>
    <dc:creator>aminer10</dc:creator>
    <dc:date>2012-06-10T14:55:28Z</dc:date>
    <item>
      <title>Parallel implementation of Jacobi with relaxation Linear Algebraic System Solver version 1.0</title>
      <link>https://community.intel.com/t5/Intel-Moderncode-for-Parallel/Parallel-implementation-of-Jacobi-with-relaxation-Linear/m-p/804911#M729</link>
      <description>&lt;BR /&gt;&lt;BR /&gt;Hello all,&lt;BR /&gt;&lt;BR /&gt;Parallel implementation of Jacobi with relaxation Linear 
Algebraic System &lt;BR /&gt;Solver version 1.0&lt;BR /&gt;&lt;BR /&gt;&lt;BR /&gt;Description:&lt;BR /&gt;&lt;BR /&gt;The 
Parallel iterative with relaxation method that i programmed here is &lt;BR /&gt;designed 
to be used to solve large sparse systems of linear equations where &lt;BR /&gt;the 
direct methods can exceed available machine memory and/or be extremely 
&lt;BR /&gt;time-consuming. for example the direct method of the Gauss algorithm takes 
&lt;BR /&gt;O(n^2) in the back substitution process and is dominated by the O(n^3) 
&lt;BR /&gt;forward elimination process, that means, if for example an operation takes 
&lt;BR /&gt;10^-9 second and we have 1000 equations , the elimination process in the 
&lt;BR /&gt;Jacobi algorithm will takes 0.7 second, but if we have 10000 equations in 
&lt;BR /&gt;the system , the elimination process in the Gauss algorithm will take 11 
&lt;BR /&gt;minutes !. This is why i have develloped for you the Parallel Jacobi with 
&lt;BR /&gt;relaxation iterative algorithm in Object Pascal, that is very 
fast.&lt;BR /&gt;Please read more here: &lt;BR /&gt;&lt;A href="http://pages.videotron.com/aminer/ParallelJacobiWithRelaxation/pjr.htm"&gt;http://pages.videotron.com/aminer/ParallelJacobiWithRelaxation/pjr.htm&lt;/A&gt;&lt;BR /&gt;Please 
look at test.pas example inside the zip file, compile and execute 
&lt;BR /&gt;it...&lt;BR /&gt;&lt;BR /&gt;&lt;BR /&gt;&lt;BR /&gt;You can download Parallel implementation of Jacobi with 
relaxation Linear &lt;BR /&gt;Algebraic System Solver version 1.0 from:&lt;BR /&gt;&lt;BR /&gt;&lt;A href="http://pages.videotron.com/aminer/"&gt;http://pages.videotron.com/aminer/&lt;/A&gt;&lt;BR /&gt;&lt;BR /&gt;&lt;BR /&gt;Language: 
FPC Pascal v2.2.0+ / Delphi 7+: &lt;A href="http://www.freepascal.org/"&gt;http://www.freepascal.org/&lt;/A&gt;&lt;BR /&gt;&lt;BR /&gt;Operating 
Systems: Win , Linux and Mac (x86).&lt;BR /&gt;&lt;BR /&gt;Required FPC switches: -O3 -Sd -dFPC 
-dWin32 -dFreePascal&lt;BR /&gt;&lt;BR /&gt;-Sd for delphi mode....&lt;BR /&gt;&lt;BR /&gt;-dUnix for 
Linux,MacOSX etc.&lt;BR /&gt;&lt;BR /&gt;Required Delphi switches: -DMSWINDOWS -$H+ 
-DDelphi&lt;BR /&gt;&lt;BR /&gt;&lt;BR /&gt;Thank you.&lt;BR /&gt;Amine Moulay Ramdane.&lt;BR /&gt;&lt;BR /&gt;&lt;BR /&gt;&lt;BR /&gt;</description>
      <pubDate>Sun, 10 Jun 2012 00:36:37 GMT</pubDate>
      <guid>https://community.intel.com/t5/Intel-Moderncode-for-Parallel/Parallel-implementation-of-Jacobi-with-relaxation-Linear/m-p/804911#M729</guid>
      <dc:creator>aminer10</dc:creator>
      <dc:date>2012-06-10T00:36:37Z</dc:date>
    </item>
    <item>
      <title>Parallel implementation of Jacobi with relaxation Linear Algebr</title>
      <link>https://community.intel.com/t5/Intel-Moderncode-for-Parallel/Parallel-implementation-of-Jacobi-with-relaxation-Linear/m-p/804912#M730</link>
      <description>&lt;BR /&gt;Hello,&lt;BR /&gt;&lt;BR /&gt;If you want tocompile Parallel implementation of Jacobi with relaxation &lt;DIV&gt;Linear System Solver version 1.0to theWin64 system, just set the CPU=64 in &lt;/DIV&gt;&lt;DIV&gt;the defines.inc.&lt;BR /&gt;&lt;BR /&gt;In my Parallel algorithm i use a factor 'lambda' that is assigned a value &lt;BR /&gt;between 0 and 2 , if this factor is set between 0 and 1 we call it underrelaxation &lt;BR /&gt;and is typically employed to make nonconvergent system converge or to hasten &lt;BR /&gt;convergence by dampening out oscillations.&lt;/DIV&gt;&lt;DIV&gt;If the value of lambda is comprised between 1 and 2, we call it overrelaxation, &lt;BR /&gt;and is designed to 'accelerate' the convergence of an already convergent system. &lt;BR /&gt;The approach is also called successive or simultaneous overrelaxation or SOR. &lt;BR /&gt;And a theorem due to Kahan shows that SOR fails to converge if it is outside the &lt;BR /&gt;interval [0,2] .&lt;BR /&gt;&lt;BR /&gt;Now i have played with the lambda and i have noticed that when you set size &lt;/DIV&gt;&lt;DIV&gt;of the matrix to a number, you have to count the number of digits in this number, &lt;/DIV&gt;&lt;DIV&gt;for example if the size of the matrix is 2000 , it means the size is 4 digits. Now &lt;/DIV&gt;&lt;DIV&gt;i have noticed that to make the system converge you have to set the lambda &lt;/DIV&gt;&lt;DIV&gt;to the same number of digits than the size or set it to thenumber of digits than &lt;/DIV&gt;&lt;DIV&gt;the size of the matrix+ 1.&lt;/DIV&gt;&lt;DIV&gt;&lt;/DIV&gt;&lt;DIV&gt;Example if the size is 2000you have to set the the number of digits before the comma &lt;/DIV&gt;&lt;DIV&gt;and after the comma to the same number of digits than the size or set it to the number of digits &lt;/DIV&gt;&lt;DIV&gt;of the size of the matrix +1 , that means that in this exampleto make the system &lt;/DIV&gt;&lt;DIV&gt;converge set the lambda to 0,001 or 0,0001.&lt;/DIV&gt;&lt;DIV&gt;&lt;/DIV&gt;&lt;DIV&gt;and if the size of the matrix is 3 , set the lambda to 1 or 0,1 to make the systemconverge.&lt;/DIV&gt;&lt;DIV&gt;&lt;/DIV&gt;&lt;DIV&gt;&lt;/DIV&gt;&lt;DIV&gt;&lt;/DIV&gt;&lt;DIV&gt;&lt;/DIV&gt;&lt;DIV&gt;Thank you.&lt;/DIV&gt;&lt;DIV&gt;Amine Moulay Ramdane.&lt;/DIV&gt;&lt;DIV&gt;&lt;BR /&gt;&lt;BR /&gt;&lt;/DIV&gt;</description>
      <pubDate>Sun, 10 Jun 2012 14:55:28 GMT</pubDate>
      <guid>https://community.intel.com/t5/Intel-Moderncode-for-Parallel/Parallel-implementation-of-Jacobi-with-relaxation-Linear/m-p/804912#M730</guid>
      <dc:creator>aminer10</dc:creator>
      <dc:date>2012-06-10T14:55:28Z</dc:date>
    </item>
    <item>
      <title>Parallel implementation of Jacobi with relaxation Linear Algebr</title>
      <link>https://community.intel.com/t5/Intel-Moderncode-for-Parallel/Parallel-implementation-of-Jacobi-with-relaxation-Linear/m-p/804913#M731</link>
      <description>&lt;DIV&gt;&lt;BR /&gt;Hello,&lt;/DIV&gt;&lt;DIV&gt;&lt;/DIV&gt;&lt;DIV&gt;&lt;BR /&gt;Red-black Gauss-Seidel converges twice as fast as Jacobi, &lt;/DIV&gt;&lt;DIV&gt;but there are twice as many parallel steps, so the same in practice&lt;/DIV&gt;&lt;DIV&gt;&lt;A href="http://www.cs.berkeley.edu/~skamil/cs267/slides/lecture12_structured_hds08.pdf"&gt;&lt;BR /&gt;http://www.cs.berkeley.edu/~skamil/cs267/slides/lecture12_structured_hds08.pdf&lt;/A&gt;&lt;/DIV&gt;&lt;DIV&gt;&lt;/DIV&gt;&lt;DIV&gt;&lt;/DIV&gt;&lt;DIV&gt;&lt;/DIV&gt;&lt;DIV&gt;&lt;/DIV&gt;&lt;DIV&gt;Thank you.&lt;/DIV&gt;&lt;DIV&gt;Amine Moulay Ramdane.&lt;/DIV&gt;&lt;DIV&gt;&lt;/DIV&gt;&lt;DIV&gt;&lt;/DIV&gt;</description>
      <pubDate>Sun, 10 Jun 2012 20:14:52 GMT</pubDate>
      <guid>https://community.intel.com/t5/Intel-Moderncode-for-Parallel/Parallel-implementation-of-Jacobi-with-relaxation-Linear/m-p/804913#M731</guid>
      <dc:creator>aminer10</dc:creator>
      <dc:date>2012-06-10T20:14:52Z</dc:date>
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