new

diff --git a/BookGPU/BookGPU.tex b/BookGPU/BookGPU.tex
index 90baace9ffa724800317ac84b3fec5d1e2f1dca1..d96b4e9db4e767a71129d1f1d200c8f5a58d16e4 100755 (executable)
--- a/BookGPU/BookGPU.tex
+++ b/BookGPU/BookGPU.tex
@@ -173,14 +173,14 @@
 \author{Raphaël Couturier}
 
 \maketitle
 \author{Raphaël Couturier}
 
 \maketitle

-
+\cleardoublepage

 \frontmatter
 %\include{frontmatter/Foreword}
 \frontmatter
 %\include{frontmatter/Foreword}

-\include{frontmatter/preface}

 
 \tableofcontents
 \listoffigures
 \listoftables
 
 \tableofcontents
 \listoffigures
 \listoftables

+\include{frontmatter/preface}

 
 \mainmatter
 
 
 \mainmatter
 

diff --git a/BookGPU/Chapters/chapter1/ch1.tex b/BookGPU/Chapters/chapter1/ch1.tex
index c69a60ef581b17beb41d4ca26a4b702f4826c47c..fc891b5f7311338c3bf99c97290f99958366941e 100755 (executable)
--- a/BookGPU/Chapters/chapter1/ch1.tex
+++ b/BookGPU/Chapters/chapter1/ch1.tex
@@ -5,7 +5,7 @@
 \label{chapter1}
 
 \section{Introduction}\label{ch1:intro}
 \label{chapter1}
 
 \section{Introduction}\label{ch1:intro}

-
+``test"  "test" ``test''

 This chapter introduces the Graphics  Processing Unit (GPU) architecture and all
 the concepts needed to understand how GPUs  work and can be used to speed up the
 execution of some algorithms. First of all this chapter gives a brief history of
 This chapter introduces the Graphics  Processing Unit (GPU) architecture and all
 the concepts needed to understand how GPUs  work and can be used to speed up the
 execution of some algorithms. First of all this chapter gives a brief history of


@@ -113,7 +113,7 @@ Threads are used to  benefit from the large number of cores  of a GPU. These
 threads    are   different    from    traditional   threads    for a   CPU.     In
 Chapter~\ref{chapter2},  some  examples of  GPU  programming  will explain  the
 details of  the GPU  threads. Threads are gathered  into blocks  of 32
 threads    are   different    from    traditional   threads    for a   CPU.     In
 Chapter~\ref{chapter2},  some  examples of  GPU  programming  will explain  the
 details of  the GPU  threads. Threads are gathered  into blocks  of 32

-threads, called warps. These warps  are important when designing an algorithm
+threads, called ``warps''. These warps  are important when designing an algorithm

 for GPU.
 
 
 for GPU.
 
 

diff --git a/BookGPU/Chapters/chapter14/biblio14.bib b/BookGPU/Chapters/chapter14/biblio14.bib
index ec060bc56c807aca4217659fdeb486a3898b4b28..8ad0aaaa3ca1ce1f21d3c82544e366e6d71e2d7e 100644 (file)
--- a/BookGPU/Chapters/chapter14/biblio14.bib
+++ b/BookGPU/Chapters/chapter14/biblio14.bib
@@ -1,14 +1,14 @@
 
 @Book{succi-book,
        author =         {Succi, S.},
 
 @Book{succi-book,
        author =         {Succi, S.},

-       title =                          {The lattice Boltzmann equation and beyond},
+       title =                          {The lattice {B}oltzmann {E}quation and {B}eyond},

        publisher =      {Oxford University Press, Oxford},
        year =                           {2001},
 }
 
 @Article{desplat,
        author =                         {Desplat, J.-C.  and Pagonabarraga, I. and Bladon P.},
        publisher =      {Oxford University Press, Oxford},
        year =                           {2001},
 }
 
 @Article{desplat,
        author =                         {Desplat, J.-C.  and Pagonabarraga, I. and Bladon P.},

-       title =                          {LUDWIG: A parallel lattice-Boltzmann code for complex fluids},
+       title =                          {LUDWIG: A parallel lattice-{B}oltzmann code for complex fluids},

        journal =                {Comput. Phys. Comms.},
        year =                           {2001},
        volume =         {134},
        journal =                {Comput. Phys. Comms.},
        year =                           {2001},
        volume =         {134},


@@ -17,7 +17,7 @@
 
 @Article{aidun2010,
        author =                         { Aidun, C. K.   and  Clausen, J. R.},
 
 @Article{aidun2010,
        author =                         { Aidun, C. K.   and  Clausen, J. R.},

-       title =                          {Lattice Boltzmann method for complex flows},
+       title =                          {Lattice {B}oltzmann method for complex flows},

        journal =                {Ann. Rev. Fluid Mech.},
        year =                           {2010},
        volume =         {42},
        journal =                {Ann. Rev. Fluid Mech.},
        year =                           {2010},
        volume =         {42},


@@ -27,7 +27,7 @@
 
 @Article{stratford2008,
        author =                         {Stratford, K. and Pagonabarraga, I.},
 
 @Article{stratford2008,
        author =                         {Stratford, K. and Pagonabarraga, I.},

-       title =                          {Parallel domain decomposition for lattice Boltzmann with moving particles},
+       title =                          {Parallel domain decomposition for lattice {B}oltzmann with moving particles},

        journal =                {Comput. Math. with Applications},
        year =                           {2008},
        volume =         {55},
        journal =                {Comput. Math. with Applications},
        year =                           {2008},
        volume =         {55},


@@ -36,7 +36,7 @@
 
 @Article{wei2004,
        author =                         {Wei, X. and Li, W. and  M\"uller, K.  and Kaufman, A. E.},
 
 @Article{wei2004,
        author =                         {Wei, X. and Li, W. and  M\"uller, K.  and Kaufman, A. E.},

-       title =                          {The lattice Boltzmann method for simulating gaseous phenomena},
+       title =                          {The lattice {B}oltzmann method for simulating gaseous phenomena},

        journal =                {IEEE Transactions on Visualization and Computer Graphics},
        year =                           {2004},
        volume =         {10},
        journal =                {IEEE Transactions on Visualization and Computer Graphics},
        year =                           {2004},
        volume =         {10},


@@ -45,7 +45,7 @@
 
 @Article{zhu2006,
        author =                         {Zhu, H. and  Liu, X. and  Liu, Y.  and Wu, E.},
 
 @Article{zhu2006,
        author =                         {Zhu, H. and  Liu, X. and  Liu, Y.  and Wu, E.},

-       title =                          {Simulation of miscible binary mixtures based on lattice Boltzmann method},
+       title =                          {Simulation of miscible binary mixtures based on lattice {B}oltzmann method},

        journal =                {Comp. Anim. Virtual Worlds},
        year =                           {2006},
        volume =         {17},
        journal =                {Comp. Anim. Virtual Worlds},
        year =                           {2006},
        volume =         {17},


@@ -54,7 +54,7 @@
 
 @Article{zhao2007,
        author =                         {Zhao, Y.},
 
 @Article{zhao2007,
        author =                         {Zhao, Y.},

-       title =                          {Lattice Boltzmann based PDE solver on the GPU},
+       title =                          {Lattice {B}oltzmann based {PDE} solver on the {GPU}},

        journal =                {Visual Comput.},
        year =                           {2008},
        volume =         {24},
        journal =                {Visual Comput.},
        year =                           {2008},
        volume =         {24},


@@ -63,7 +63,7 @@
 
 @Article{toelke2010,
        author =                         {T\"olke, J.},
 
 @Article{toelke2010,
        author =                         {T\"olke, J.},

-       title =                          {Implementation of a lattice Boltzmann kernel using the compute unified device architecture developed by nVIDIA},
+       title =                          {Implementation of a lattice {B}oltzmann kernel using the compute unified device architecture developed by {NVIDIA}},

        journal =                {Comput. Visual Sci.},
        year =                           {2010},
        volume =         {13},
        journal =                {Comput. Visual Sci.},
        year =                           {2010},
        volume =         {13},


@@ -73,7 +73,7 @@
 
 @InProceedings{fan2004,
        author =                         { Fan, Z. and  Qiu, F. and  Kaufman, A. and Yoakum-Stover, S.},
 
 @InProceedings{fan2004,
        author =                         { Fan, Z. and  Qiu, F. and  Kaufman, A. and Yoakum-Stover, S.},

-       title =                          {GPU cluster for high performance computing},
+       title =                          {{GPU} cluster for high performance computing},

        booktitle = {Proceedings of ACM/IEEE Supercomputing Conference},
        pages =                  {47--59},
        year =           {2004},
        booktitle = {Proceedings of ACM/IEEE Supercomputing Conference},
        pages =                  {47--59},
        year =           {2004},


@@ -84,7 +84,7 @@
 
 @Article{myre2011,
        author =                         { Myre, J. and  Walsh, S. D. C. and  Lilja, D. and Saar, M. O.},
 
 @Article{myre2011,
        author =                         { Myre, J. and  Walsh, S. D. C. and  Lilja, D. and Saar, M. O.},

-       title =                          {Performance analysis of single-phase, multiphase, and multicomponent lattice Boltzmann fluid flow simulations on GPU clusters},
+       title =                          {Performance analysis of single-phase, multiphase, and multicomponent lattice {B}oltzmann fluid flow simulations on {GPU} clusters},

        journal =                {Concurrency Computat.: Pract. Exper.},
        year =                           {2011},
        volume =         {23},
        journal =                {Concurrency Computat.: Pract. Exper.},
        year =                           {2011},
        volume =         {23},


@@ -94,7 +94,7 @@
 
 @Article{obrecht2011,
        author =                         { Obrecht, C. and  Kuznik, F. and  Tourancheau, B.  and Roux, J.-J.},
 
 @Article{obrecht2011,
        author =                         { Obrecht, C. and  Kuznik, F. and  Tourancheau, B.  and Roux, J.-J.},

-       title =                          {Multi-GPU implementation of the lattice Boltzmann method},
+       title =                          {Multi-{GPU} implementation of the lattice {B}oltzmann method},

        journal =                {Comput. Math. with Applications},
        year =                           {2013},
        volume =         {65},
        journal =                {Comput. Math. with Applications},
        year =                           {2013},
        volume =         {65},


@@ -103,7 +103,7 @@
 
 @Article{bernaschi2010,
        author =                         {Bernaschi, M. and Fatica, M. and  Melchionna, S. and Succi, S. and Kaxiras, E.},
 
 @Article{bernaschi2010,
        author =                         {Bernaschi, M. and Fatica, M. and  Melchionna, S. and Succi, S. and Kaxiras, E.},

-       title =                          {A flexible high-performance lattice Boltzmann GPU code for the
+       title =                          {A flexible high-performance lattice {B}oltzmann {GPU} code for the

 simulations of fluid flow in complex geometries},
        journal =                {Concurrency Computat.: Pract. Exper.},
        year =                           {2010},
 simulations of fluid flow in complex geometries},
        journal =                {Concurrency Computat.: Pract. Exper.},
        year =                           {2010},


@@ -113,8 +113,8 @@ simulations of fluid flow in complex geometries},
 
 @Article{xian2011,
        author =                         { Xian, W.  and Takayuki, A.},
 
 @Article{xian2011,
        author =                         { Xian, W.  and Takayuki, A.},

-       title =                          {Multi-GPU performance of incompressible flow computation by
-lattice Boltzmann method on GPU cluster},
+       title =                          {Multi-{GPU} performance of incompressible flow computation by
+lattice {B}oltzmann method on {GPU} cluster},

        journal =                {Parallel Comput.},
        year =                           {2011},
        volume =         {37},
        journal =                {Parallel Comput.},
        year =                           {2011},
        volume =         {37},


@@ -125,7 +125,7 @@ lattice Boltzmann method on GPU cluster},
 @Article{feichtinger2011,
        author =                         {Feichtinger, C. and Habich, J. and K\"ostler, H. and  Hager, G. and   R\"ude, U.  and
  Wellein, G.},
 @Article{feichtinger2011,
        author =                         {Feichtinger, C. and Habich, J. and K\"ostler, H. and  Hager, G. and   R\"ude, U.  and
  Wellein, G.},

-       title =                          {A flexible patch-based lattice Boltzmann parallelization approach for heterogeneous GPU-CPU clusters},
+       title =                          {A flexible patch-based lattice {B}oltzmann parallelization approach for heterogeneous {GPU-CPU} clusters},

        journal =                {Parallel Computing},
        year =                           {2011},
        volume =         {37},
        journal =                {Parallel Computing},
        year =                           {2011},
        volume =         {37},


@@ -134,7 +134,7 @@ lattice Boltzmann method on GPU cluster},
 
 @Article{wellein2006,
        author =                         {Wellein, G. and Zeiser, T. and Hager, G.  and Donath, S.},
 
 @Article{wellein2006,
        author =                         {Wellein, G. and Zeiser, T. and Hager, G.  and Donath, S.},

-       title =                          {On the single processor performance of simple lattice Boltzmann kernels},
+       title =                          {On the single processor performance of simple lattice {B}oltzmann kernels},

        journal =                {Computers and Fluids},
        year =                           {2006},
        volume =         {35},
        journal =                {Computers and Fluids},
        year =                           {2006},
        volume =         {35},


@@ -143,7 +143,7 @@ lattice Boltzmann method on GPU cluster},
 
 @Article{pohl2003,
        author =                         { Pohl, T. and  Kowarschik, M. and Wilke, J. and Igelberger, K.  and R\"ude, U.},
 
 @Article{pohl2003,
        author =                         { Pohl, T. and  Kowarschik, M. and Wilke, J. and Igelberger, K.  and R\"ude, U.},

-       title =                          {Optimization and profiling of the cache performance of parallel lattice Boltzmann code},
+       title =                          {Optimization and profiling of the cache performance of parallel lattice {B}oltzmann code},

        journal =                {Parallel Process Lett.},
        year =                           {2003},
        volume =         {13},
        journal =                {Parallel Process Lett.},
        year =                           {2003},
        volume =         {13},


@@ -152,7 +152,7 @@ lattice Boltzmann method on GPU cluster},
 
 @Article{mattila2007,
        author =                         {Mattila, K. and Hyv\"aluoma, J. and Rossi, T. and Aspn\"as M. and  Westerholm, J.},
 
 @Article{mattila2007,
        author =                         {Mattila, K. and Hyv\"aluoma, J. and Rossi, T. and Aspn\"as M. and  Westerholm, J.},

-       title =                          {An efficient swap algorithm for the lattice Boltzmann method},
+       title =                          {An efficient swap algorithm for the lattice {B}oltzmann method},

        journal =                {Comput. Phys. Comms.},
        year =                           {2007},
        volume =         {176},
        journal =                {Comput. Phys. Comms.},
        year =                           {2007},
        volume =         {176},


@@ -163,7 +163,7 @@ lattice Boltzmann method on GPU cluster},
 
 @Article{wittmann2012,
        author =                         {Wittmann, M. and Zeiser, T. and  Hager, G.  and Wellein, G.},
 
 @Article{wittmann2012,
        author =                         {Wittmann, M. and Zeiser, T. and  Hager, G.  and Wellein, G.},

-       title =                          {Comparison of different propagation steps for lattice Boltzmann methods},
+       title =                          {Comparison of different propagation steps for lattice {B}oltzmann methods},

        journal =                {Comput. Math with Appl.},
        year =                           {2012},
        note =           {doi:10.1016/j.camwa.2012.05.002},
        journal =                {Comput. Math with Appl.},
        year =                           {2012},
        note =           {doi:10.1016/j.camwa.2012.05.002},


@@ -171,7 +171,7 @@ lattice Boltzmann method on GPU cluster},
 
 @Article{walshsaar2012,
        author =                         {Walsh, S. D. C. and Saar, M. O.},
 
 @Article{walshsaar2012,
        author =                         {Walsh, S. D. C. and Saar, M. O.},

-       title =                          {Developing extensible lattice Boltzmann simulators for general-purpose graphics-processing units},
+       title =                          {Developing extensible lattice {B}oltzmann simulators for general-purpose graphics-processing units},

        journal =                {Comm. Comput. Phys.},
        year =                           {2013},
        volume =         {13},
        journal =                {Comm. Comput. Phys.},
        year =                           {2013},
        volume =         {13},


@@ -181,7 +181,7 @@ lattice Boltzmann method on GPU cluster},
 
 @InProceedings{williams2011,
        author =                         {Williams, S. and  Oliker, L. and  Carter, J. and Shalf, J.},
 
 @InProceedings{williams2011,
        author =                         {Williams, S. and  Oliker, L. and  Carter, J. and Shalf, J.},

-       title =                          {Extracting ultra-scale lattice Boltzmann performance via
+       title =                          {Extracting ultra-scale lattice {B}oltzmann performance via

 hierarchical and distributed auto-tuning},
        booktitle = {International Conference for High Performance Computing, Networking, Storage and Analysis (SC) },
        pages =                  {1--12},
 hierarchical and distributed auto-tuning},
        booktitle = {International Conference for High Performance Computing, Networking, Storage and Analysis (SC) },
        pages =                  {1--12},


@@ -194,7 +194,7 @@ hierarchical and distributed auto-tuning},
 
 @Article{ch14:stratford-jsp2005,
        author =                         {Stratford, K. and Adhikari, R. and Pagonabarraga, I. and Desplat, J.-C.},
 
 @Article{ch14:stratford-jsp2005,
        author =                         {Stratford, K. and Adhikari, R. and Pagonabarraga, I. and Desplat, J.-C.},

-       title =                          {Lattice Boltzmann for Binary Fluids with Suspended Colloids},
+       title =                          {Lattice {B}oltzmann for Binary Fluids with Suspended Colloids},

        journal =                {J. Stat. Phys.},
        year =                           {2005},
        volume =         {121},
        journal =                {J. Stat. Phys.},
        year =                           {2005},
        volume =         {121},


@@ -204,7 +204,7 @@ hierarchical and distributed auto-tuning},
 
 @Article{ladd1994,
        author =                         {Ladd, A. J. C.},
 
 @Article{ladd1994,
        author =                         {Ladd, A. J. C.},

-       title =                          {Numerical simulations of particle suspensions via a discretized Boltzmann equation. Part 1. Theoretical foundation and Part II. Numerical results},
+       title =                          {Numerical simulations of particle suspensions via a discretized {B}oltzmann equation. {P}art 1. Theoretical foundation and {P}art II. {N}umerical results},

        journal =                {J. Fluid Mech.},
        year =                           {1994},
        volume =         {271},
        journal =                {J. Fluid Mech.},
        year =                           {1994},
        volume =         {271},


@@ -215,7 +215,7 @@ hierarchical and distributed auto-tuning},
 
 @Article{nguyen2002,
        author =                         {Nguyen, N.-Q. and Ladd, A. J. C.},
 
 @Article{nguyen2002,
        author =                         {Nguyen, N.-Q. and Ladd, A. J. C.},

-       title =                          {Lubrication corrections for lattice Boltzmann simulations of particle suspensions},
+       title =                          {Lubrication corrections for lattice {B}oltzmann simulations of particle suspensions},

        journal =                {Phys. Rev. E},
        year =                           {2002},
        volume =         {66},
        journal =                {Phys. Rev. E},
        year =                           {2002},
        volume =         {66},


@@ -244,7 +244,7 @@ hierarchical and distributed auto-tuning},
 
 @Article{ch14:immersed-lb,
        author =                         {Feng, Z.-G. and  Michaelides, E. E},
 
 @Article{ch14:immersed-lb,
        author =                         {Feng, Z.-G. and  Michaelides, E. E},

-       title =                          {The immersed boundary-lattice Boltzmann method for solving
+       title =                          {The immersed boundary-lattice {B}oltzmann method for solving

 fluid-particles interaction problem},
        journal =                {J. Comp. Phys.},
        year =                           {2004},
 fluid-particles interaction problem},
        journal =                {J. Comp. Phys.},
        year =                           {2004},

diff --git a/BookGPU/Chapters/chapter14/ch14.tex b/BookGPU/Chapters/chapter14/ch14.tex
index 1acb0807d6fbee3870c139747cad7e500e2815f8..2ce9331300ab9c7fbaa4e4182c9edf49f10b96c0 100755 (executable)
--- a/BookGPU/Chapters/chapter14/ch14.tex
+++ b/BookGPU/Chapters/chapter14/ch14.tex
@@ -13,14 +13,14 @@ The lattice Boltzmann (LB) method \index{Lattice Boltzmann method} (for an overv
 dynamics problems.  It provides a way to solve the incompressible
 isothermal Navier-Stokes equations and has the attractive features of
 being both explicit in time and local in space. This makes the LB
 dynamics problems.  It provides a way to solve the incompressible
 isothermal Navier-Stokes equations and has the attractive features of
 being both explicit in time and local in space. This makes the LB

-method wellsuited to parallel computation. Many efficient parallel
+method well suited to parallel computation. Many efficient parallel

 implementations of the LB method have been undertaken, typically using
 a combination of distributed domain decomposition and the Message
 Passing Interface (MPI). However, the potential
 performance benefits offered by GPUs has motivated a new ``mixed-mode''
 approach to address very large problems. Here, fine-grained
 parallelism is implemented on the GPU, while MPI is reserved for
 implementations of the LB method have been undertaken, typically using
 a combination of distributed domain decomposition and the Message
 Passing Interface (MPI). However, the potential
 performance benefits offered by GPUs has motivated a new ``mixed-mode''
 approach to address very large problems. Here, fine-grained
 parallelism is implemented on the GPU, while MPI is reserved for

-largerscale parallelism.  This mixed mode is of increasing interest
+larger scale parallelism.  This mixed mode is of increasing interest

 to application programmers at a time when many supercomputing services
 are moving
 toward clusters of GPU accelerated nodes. The design questions which
 to application programmers at a time when many supercomputing services
 are moving
 toward clusters of GPU accelerated nodes. The design questions which


@@ -156,9 +156,9 @@ site, may be thought of as follows. A matrix-vector multiplication
 ${\cal M}_{ij}f_j$ is used to transform the distributions into the
 hydrodynamic quantities, where ${\cal M}_{ij}$ is a constant 19x19
 matrix related to the choice of
 ${\cal M}_{ij}f_j$ is used to transform the distributions into the
 hydrodynamic quantities, where ${\cal M}_{ij}$ is a constant 19x19
 matrix related to the choice of

-$\mathbf{c}_i$. The nonconserved hydrodynamic quantities are then
+$\mathbf{c}_i$. The non-conserved hydrodynamic quantities are then

 relaxed toward their (known) equilibrium values and are transformed
 relaxed toward their (known) equilibrium values and are transformed

-back to new postcollision distributions via the inverse transformation
+back to new post-collision distributions via the inverse transformation

 ${\cal M}^{-1}_{ij}$. This gives rise to the need for a minimum of $2\times 19^2$
 floating point multiplications per lattice site. (Additional operations are
 required to implement, for example, the force $\mathbf{f}(\mathbf{r})$.)
 ${\cal M}^{-1}_{ij}$. This gives rise to the need for a minimum of $2\times 19^2$
 floating point multiplications per lattice site. (Additional operations are
 required to implement, for example, the force $\mathbf{f}(\mathbf{r})$.)


@@ -193,12 +193,13 @@ Listing~\ref{ch14:listing1}: the fact that consecutive loads are from
 consecutive memory addresses allows the prefetcher to engage fully.
 (The temporary scalar \texttt{a\_tmp} allows caching of the
 intermediate accumulated value in the innermost loop.)  A variety of
 consecutive memory addresses allows the prefetcher to engage fully.
 (The temporary scalar \texttt{a\_tmp} allows caching of the
 intermediate accumulated value in the innermost loop.)  A variety of

-standard sequential optimisations are relevant for the collision stage
+standard sequential optimizations are relevant for the collision stage

 (loop unrolling, inclusion of SIMD operations, and so on
 \cite{wellein2006}).  For example, the collision stage in
 \textit{Ludwig} includes explicit SIMD code, which is useful if the
 (loop unrolling, inclusion of SIMD operations, and so on
 \cite{wellein2006}).  For example, the collision stage in
 \textit{Ludwig} includes explicit SIMD code, which is useful if the

-compiler on a given platform cannot identify it.  The propagation
-stage is separate and is organised as a ``pull'' (again, various
+compiler on a given platform cannot identify the appropriate vectorization.
+The propagation
+stage is separate and is organized as a ``pull'' (again, various

 optimizations have been considered, e.g.,
 \cite{pohl2003,mattila2007,wittmann2012}).  No further optimization is
 done here beyond ensuring that the ordering of the discrete velocities
 optimizations have been considered, e.g.,
 \cite{pohl2003,mattila2007,wittmann2012}).  No further optimization is
 done here beyond ensuring that the ordering of the discrete velocities


@@ -206,7 +207,7 @@ allows memory access to be as efficient as possible. While these
 optimizations are important, it should be remembered that for some
 complex fluid problems, the hydrodynamics embodied in the LB
 calculation is a relatively small part of the total computational cost
 optimizations are important, it should be remembered that for some
 complex fluid problems, the hydrodynamics embodied in the LB
 calculation is a relatively small part of the total computational cost

-(at the 10\%level in some cases).  This means optimization effort may
+(at the 10\% level in some cases).  This means optimization effort may

 be better concentrated elsewhere.
 
 
 be better concentrated elsewhere.
 
 


@@ -249,7 +250,7 @@ involving relevant data can take place, and so on. We note that only
 For the D3Q19 model, this reduces the volume of data traffic from 19 to
 5 of the $f_i(\mathbf{r};t)$ per lattice site at each edge. In the CPU
 version, the necessary transfers are implemented in place using
 For the D3Q19 model, this reduces the volume of data traffic from 19 to
 5 of the $f_i(\mathbf{r};t)$ per lattice site at each edge. In the CPU
 version, the necessary transfers are implemented in place using

-a vector of appropriately strided MPI datatypes for each direction.
+a vector of MPI datatypes with appropriate stride for each direction.

 
 
 \section{Single GPU implementation}\label{ch14:sec:singlegpu}
 
 
 \section{Single GPU implementation}\label{ch14:sec:singlegpu}


@@ -301,7 +302,7 @@ of CUDA threads. As the matrix ${\cal M}_{ij}$ is constant, it is
 assigned to the fast {\it constant} on-chip device memory.
 
 For the propagation stage, the GPU implementation adds a second time
 assigned to the fast {\it constant} on-chip device memory.
 
 For the propagation stage, the GPU implementation adds a second time

-level of distribution values. The datadependencies inherent in the
+level of distribution values. The data dependencies inherent in the

 propagation mean that the in-place propagation of the CPU version
 cannot be parallelized effectively without the additional time level.
 As both time levels may remain resident on the GPU, this is not a
 propagation mean that the in-place propagation of the CPU version
 cannot be parallelized effectively without the additional time level.
 As both time levels may remain resident on the GPU, this is not a


@@ -350,7 +351,8 @@ complication is that halo transfers between GPUs must be staged
 through the host (in the future, direct GPU-to-GPU data transfers via
 MPI may be possible, obviating the need for these steps). This
 means host MPI sends must be preceded by appropriate device-to-host
 through the host (in the future, direct GPU-to-GPU data transfers via
 MPI may be possible, obviating the need for these steps). This
 means host MPI sends must be preceded by appropriate device-to-host

-transfers and host MPI receives must be followed by corresponding host-to-device transfers.
+transfers and host MPI receives must be followed by corresponding
+host-to-device transfers.

 
 %To execute on multiple GPUs in parallel we decompose the problem using
 %the existing high-level parallelisaton framework: each MPI task acts
 
 %To execute on multiple GPUs in parallel we decompose the problem using
 %the existing high-level parallelisaton framework: each MPI task acts


@@ -393,7 +395,7 @@ retrieved by the host, these can be exchanged using MPI between
 hosts at the same time as kernels for packing and retrieving of
 data for the second coordinate direction are
 executed. This
 hosts at the same time as kernels for packing and retrieving of
 data for the second coordinate direction are
 executed. This

-overlapping must respect the synchronisation required to ensure
+overlapping must respect the synchronization required to ensure

 that data values at the corners of the subdomain are transferred
 correctly.
 We use a separate CUDA stream for each coordinate direction:
 that data values at the corners of the subdomain are transferred
 correctly.
 We use a separate CUDA stream for each coordinate direction:


@@ -503,7 +505,7 @@ scaling for the larger systems.
 \begin{figure}[t]
 \centering
 %\includegraphics[width=10cm]{Chapters/chapter14/figures/bbl}
 \begin{figure}[t]
 \centering
 %\includegraphics[width=10cm]{Chapters/chapter14/figures/bbl}

-\includegraphics[width=10cm]{Chapters/chapter14/figures/colloid_new}
+\includegraphics[width=10cm]{Chapters/chapter14/figures/colloid_new_gray}

 \caption[A two-dimensional schematic picture of spherical particles on the lattice.]{
 A two-dimensional schematic picture of spherical particles on the lattice.
 Left: a particle is allowed
 \caption[A two-dimensional schematic picture of spherical particles on the lattice.]{
 A two-dimensional schematic picture of spherical particles on the lattice.
 Left: a particle is allowed


@@ -541,11 +543,11 @@ to efficient GPU implementation of an LB code such as \textit{Ludwig}.
 In this section, we give a brief overview of the essential features
 of the CPU implementation, and how the considerations raised in the
 previous sections---maximizing parallelism and minimising both
 In this section, we give a brief overview of the essential features
 of the CPU implementation, and how the considerations raised in the
 previous sections---maximizing parallelism and minimising both

-host-to-device and GPU to GPU data movement---shape the design decisions
+host-to-device and GPU-to-GPU data movement---shape the design decisions

 for a GPU implementation. We restrict our discussion to a simple fluid
 in this section; additional solid-fluid boundary conditions (e.g.,
 wetting at a fluid-fluid-solid contact line) usually arise elsewhere
 for a GPU implementation. We restrict our discussion to a simple fluid
 in this section; additional solid-fluid boundary conditions (e.g.,
 wetting at a fluid-fluid-solid contact line) usually arise elsewhere

-in the calculation broadly independent of the hydrodynamic boundary
+in the calculation and are broadly independent of the hydrodynamic boundary

 conditions which are described in what follows.
 
 Moving solid particles (here, spheres) are defined by a center position
 conditions which are described in what follows.
 
 Moving solid particles (here, spheres) are defined by a center position


@@ -556,7 +558,7 @@ where a discrete velocity propagation $\mathbf{c}_i \Delta t$ would
 intercept or cut the spherical shell (see Fig.~\ref{ch14:fig:bbl}).
 Hydrodynamic boundary conditions are then implemented via the standard
 approach of bounce-back on links \cite{ladd1994, nguyen2002}, where the
 intercept or cut the spherical shell (see Fig.~\ref{ch14:fig:bbl}).
 Hydrodynamic boundary conditions are then implemented via the standard
 approach of bounce-back on links \cite{ladd1994, nguyen2002}, where the

-relevant postcollision distribution values are reversed at the
+relevant post-collision distribution values are reversed at the

 propagation stage with an appropriate correction to allow for the
 solid body motion. The exchange of momentum at each link must then be
 accumulated around the entire particle surface to provide the net
 propagation stage with an appropriate correction to allow for the
 solid body motion. The exchange of momentum at each link must then be
 accumulated around the entire particle surface to provide the net


@@ -565,8 +567,8 @@ and torque on the sphere. The particle motion can then be updated in a
 molecular dynamics-like step.
 
 For the CPU implementation, a number of additional MPI communications
 molecular dynamics-like step.
 
 For the CPU implementation, a number of additional MPI communications

-are required: (1) to exchange the center position, radius, etc of each
-particle as it moves and (2), to allow the accumulation of the force
+are required: (1) to exchange the center position, radius, etc.\ of each
+particle as it moves and (2) to allow the accumulation of the force

 and torque for each particle (the links of which may be distributed
 between up to 8 MPI tasks in three dimensions). Appropriate marshaling
 of these data can provide an effective parallelization for relatively
 and torque for each particle (the links of which may be distributed
 between up to 8 MPI tasks in three dimensions). Appropriate marshaling
 of these data can provide an effective parallelization for relatively


@@ -579,7 +581,7 @@ With these features in mind, we can identify a number of competing
 concerns which are relevant to a GPU implementation:
 \begin{enumerate}
 \item
 concerns which are relevant to a GPU implementation:
 \begin{enumerate}
 \item

-Minimisation of host-device data transfer would argue for moving the
+Minimization of host-device data transfer would argue for moving the

 entire particle code to the GPU. However, the code in question involves
 largely conditional logic (e.g., identifying cut surface links) and
 irregular memory accesses (e.g., access to distribution elements around
 entire particle code to the GPU. However, the code in question involves
 largely conditional logic (e.g., identifying cut surface links) and
 irregular memory accesses (e.g., access to distribution elements around


@@ -603,10 +605,11 @@ particle information.
 
 
 We have implemented the second option as follows. For each subdomain,
 
 
 We have implemented the second option as follows. For each subdomain,

-a list of boundary-cutting links is assembled on the CPU which includes
-the identity of the relevant element of the distribution. This list,
+a list of boundary-cutting links is assembled on the CPU; the list includes
+the identity of the relevant element of the distribution in each case.
+This list,

 together with the particle information required to compute the correct
 together with the particle information required to compute the correct

-bounce-back term, are transferred to the GPU. The updates to the relevant
+bounce-back term, is transferred to the GPU. The updates to the relevant

 elements of the distribution can then take place on the GPU. The
 corresponding information to compute the update of the particle dynamics
 is returned
 elements of the distribution can then take place on the GPU. The
 corresponding information to compute the update of the particle dynamics
 is returned


@@ -741,7 +744,7 @@ we have tried to maintain the modular structure of the CPU where
 possible. For each data structure, such as the distribution, a separate
 analogue is maintained in both the CPU and GPU memory spaces. However,
 the GPU copy does not include the complete CPU structure: in
 possible. For each data structure, such as the distribution, a separate
 analogue is maintained in both the CPU and GPU memory spaces. However,
 the GPU copy does not include the complete CPU structure: in

-particular, nonintrinsic datatypes such as MPI datatypes are not
+particular, non-intrinsic datatypes such as MPI datatypes are not

 required on the GPU. Functions to marshal data between CPU and GPU
 are provided for each data structure, abstracting the underlying
 CUDA implementation. (This reasonably lightweight abstraction layer
 required on the GPU. Functions to marshal data between CPU and GPU
 are provided for each data structure, abstracting the underlying
 CUDA implementation. (This reasonably lightweight abstraction layer


@@ -934,7 +937,7 @@ complex fluid problems.
 
 
 % use section* for acknowledgement
 
 
 % use section* for acknowledgement

-\section*{Acknowledgments}
+\section{Acknowledgments}

 AG was supported by the CRESTA project, which has received
 funding from the European Community's Seventh Framework Programme
 (ICT-2011.9.13) under Grant Agreement no. 287703. KS was supported
 AG was supported by the CRESTA project, which has received
 funding from the European Community's Seventh Framework Programme
 (ICT-2011.9.13) under Grant Agreement no. 287703. KS was supported

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