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diff --git a/vignettes/compiled_models.html b/vignettes/compiled_models.html index 5fcd88fb..fc71debe 100644 --- a/vignettes/compiled_models.html +++ b/vignettes/compiled_models.html @@ -8,7 +8,9 @@ <meta http-equiv="Content-Type" content="text/html; charset=utf-8" /> <meta name="generator" content="pandoc" /> +<meta name="author" content="Johannes Ranke" /> +<meta name="date" content="2015-06-22" /> <title>Performance benefit by using compiled model definitions in mkin</title> @@ -62,6 +64,8 @@ img { <div id="header"> <h1 class="title">Performance benefit by using compiled model definitions in mkin</h1> +<h4 class="author"><em>Johannes Ranke</em></h4> +<h4 class="date"><em>2015-06-22</em></h4> </div> <div id="TOC"> @@ -71,17 +75,17 @@ img { </ul> </div> -<!-- -%\VignetteEngine{knitr::rmarkdown} -%\VignetteIndexEntry{Performance benefit by using compiled model definitions in mkin} ---> -<div id="benchmark-for-a-model-that-can-also-be-solved-with-eigenvalues" class="section level1"> -<h1>Benchmark for a model that can also be solved with Eigenvalues</h1> -<p>This evaluation is taken from the example section of mkinfit. When using an mkin version equal to or greater than 0.9-36 and a compiler (gcc) is installed, you will see a message that the model is being compiled from autogenerated C code when defining a model using mkinmod.</p> +<div id="benchmark-for-a-model-that-can-also-be-solved-with-eigenvalues" class="section level2"> +<h2>Benchmark for a model that can also be solved with Eigenvalues</h2> +<p>This evaluation is taken from the example section of mkinfit. When using an mkin version equal to or greater than 0.9-36 and a compiler (gcc) is installed, you will see a message that the model is being compiled from autogenerated C code when defining a model using mkinmod. The package tests for presence of the gcc compiler using</p> +<pre class="r"><code>Sys.which("gcc")</code></pre> +<pre><code>## gcc +## "/usr/bin/gcc"</code></pre> +<p>First, we build a simple degradation model for a parent compound with one metabolite.</p> <pre class="r"><code>library("mkin") SFO_SFO <- mkinmod( - parent = list(type = "SFO", to = "m1", sink = TRUE), - m1 = list(type = "SFO"))</code></pre> + parent = mkinsub("SFO", "m1"), + m1 = mkinsub("SFO"))</code></pre> <pre><code>## Compiling differential equation model from auto-generated C code...</code></pre> <p>We can compare the performance of the Eigenvalue based solution against the compiled version and the R implementation of the differential equations using the microbenchmark package.</p> <pre class="r"><code>library("microbenchmark") @@ -95,26 +99,26 @@ smb.1 <- summary(mb.1)[-1] rownames(smb.1) <- c("deSolve, not compiled", "Eigenvalue based", "deSolve, compiled") print(smb.1)</code></pre> <pre><code>## min lq mean median uq -## deSolve, not compiled 6980.8002 6996.4739 7024.5611 7012.1476 7046.4415 -## Eigenvalue based 925.3350 928.9405 951.8405 932.5460 965.0932 -## deSolve, compiled 747.2635 761.9405 771.4339 776.6174 783.5191 +## deSolve, not compiled 5379.4269 5431.6605 5455.0396 5483.8940 5492.8460 +## Eigenvalue based 930.6245 951.6701 959.4653 972.7157 973.8857 +## deSolve, compiled 755.9828 771.1000 794.1810 786.2172 813.2800 ## max neval -## deSolve, not compiled 7080.7354 3 -## Eigenvalue based 997.6404 3 -## deSolve, compiled 790.4207 3</code></pre> -<p>We see that using the compiled model is by a factor of 9 faster than using the R version with the default ode solver, and it is even faster than the Eigenvalue based solution implemented in R which does not need iterative solution of the ODEs:</p> +## deSolve, not compiled 5501.7979 3 +## Eigenvalue based 975.0556 3 +## deSolve, compiled 840.3428 3</code></pre> +<p>We see that using the compiled model is by a factor of 7 faster than using the R version with the default ode solver, and it is even faster than the Eigenvalue based solution implemented in R which does not need iterative solution of the ODEs:</p> <pre class="r"><code>smb.1["median"]/smb.1["deSolve, compiled", "median"]</code></pre> <pre><code>## median -## deSolve, not compiled 9.029089 -## Eigenvalue based 1.200779 +## deSolve, not compiled 6.975037 +## Eigenvalue based 1.237210 ## deSolve, compiled 1.000000</code></pre> </div> -<div id="benchmark-for-a-model-that-can-not-be-solved-with-eigenvalues" class="section level1"> -<h1>Benchmark for a model that can not be solved with Eigenvalues</h1> +<div id="benchmark-for-a-model-that-can-not-be-solved-with-eigenvalues" class="section level2"> +<h2>Benchmark for a model that can not be solved with Eigenvalues</h2> <p>This evaluation is also taken from the example section of mkinfit.</p> <pre class="r"><code>FOMC_SFO <- mkinmod( - parent = list(type = "FOMC", to = "m1", sink = TRUE), - m1 = list(type = "SFO"))</code></pre> + parent = mkinsub("FOMC", "m1"), + m1 = mkinsub( "SFO"))</code></pre> <pre><code>## Compiling differential equation model from auto-generated C code...</code></pre> <pre class="r"><code>mb.2 <- microbenchmark( mkinfit(FOMC_SFO, FOCUS_2006_D, use_compiled = FALSE, quiet = TRUE), @@ -123,17 +127,22 @@ print(smb.1)</code></pre> smb.2 <- summary(mb.2)[-1] rownames(smb.2) <- c("deSolve, not compiled", "deSolve, compiled") print(smb.2)</code></pre> -<pre><code>## min lq mean median uq -## deSolve, not compiled 14.127630 14.245064 14.298201 14.362497 14.383486 -## deSolve, compiled 1.354744 1.362167 1.366362 1.369589 1.372171 +<pre><code>## min lq mean median uq +## deSolve, not compiled 11.815894 11.84960 12.03290 11.883305 12.141404 +## deSolve, compiled 1.387086 1.43514 1.45956 1.483194 1.495796 ## max neval -## deSolve, not compiled 14.404474 3 -## deSolve, compiled 1.374752 3</code></pre> +## deSolve, not compiled 12.399502 3 +## deSolve, compiled 1.508399 3</code></pre> <pre class="r"><code>smb.2["median"]/smb.2["deSolve, compiled", "median"]</code></pre> <pre><code>## median -## deSolve, not compiled 10.48672 -## deSolve, compiled 1.00000</code></pre> -<p>Here we get a performance benefit of a factor of 10.5 using the version of the differential equation model compiled from C code using the inline package!</p> +## deSolve, not compiled 8.011968 +## deSolve, compiled 1.000000</code></pre> +<p>Here we get a performance benefit of a factor of 8 using the version of the differential equation model compiled from C code using the inline package!</p> +<p>This vignette was built with mkin 0.9.37 on</p> +<pre><code>## R version 3.2.1 (2015-06-18) +## Platform: x86_64-pc-linux-gnu (64-bit) +## Running under: Debian GNU/Linux 8 (jessie)</code></pre> +<pre><code>## CPU model: Intel(R) Core(TM) i7-4710MQ CPU @ 2.50GHz</code></pre> </div> |