X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/book_gpu.git/blobdiff_plain/4932967a1c684dc3f7ed04c19144101278b79972..2ce2baf7820f44ab044b4df98722576116551e57:/BookGPU/Chapters/chapter16/ch16.tex

diff --git a/BookGPU/Chapters/chapter16/ch16.tex b/BookGPU/Chapters/chapter16/ch16.tex
index bfa5d6c..a08c901 100644
--- a/BookGPU/Chapters/chapter16/ch16.tex
+++ b/BookGPU/Chapters/chapter16/ch16.tex
@@ -1,11 +1,9 @@
-\chapterauthor{X.-X. Liu}{Dept. Electrical Engineering,
-  University  of California, Riverside, CA 92521}
-\chapterauthor{S. X.-D. Tan}{Dept. Electrical Engineering,
-  University  of California, Riverside, CA 92521}
-\chapterauthor{H. Wang}{Univ. of Electronics Science and Technology of China,
+\chapterauthor{Xuexin Liu, Sheldon Xiang-Dong Tan}{Department of Electrical Engineering,
+  University  of California, Riverside, CA, USA}
+%\chapterauthor{Sheldon Xiang-Dong Tan}{Dept. Electrical Engineering,  University  of California, Riverside, CA 92521}
+\chapterauthor{Hai Wang}{University of Electronics Science and Technology of China,
   Chengdu, Sichuan, China}
-\chapterauthor{H. Yu}{School of Electrical \& Electronic Engineering,
-  Nanyang Technological University, Singapore}
+\chapterauthor{Hao Yu}{School of Electrical \& Electronic Engineering, Nanyang Technological University, Singapore}
 
 %  \thanks{
 %    This research was supported in part by NSF grants under
@@ -20,7 +18,7 @@
 %\renewcommand{\algorithmicensure}{\textbf{Output:}}
 %\renewcommand{\algorithmiccomment}[1]{\% \textit{#1}}
 
-\chapter[GPU-Accelerated Envelope-Following Method]{A GPU-Accelerated Envelope-Following Method for Switching Power Converter Simulation}
+\chapter[GPU-accelerated envelope-following method]{A GPU-accelerated envelope-following method for switching power converter simulation}
 
 % \section{Abstract}
 % % Power converters have seen a surge of new trends and novel
@@ -54,21 +52,22 @@
 \input{Chapters/chapter16/gpu.tex}
 \input{Chapters/chapter16/exp.tex}
 
+\clearpage
 \section{Summary}
 \label{sec:summary}
-In this chapter, we present a new envelope-following method for
+In this chapter, we have presented a new envelope-following method for
 transient analysis of switching power converters.  First, the
-computationally expensive step, the solving of Newton update equation,
+computationally expensive step, the solving of the Newton update equation,
 has been parallelized on CUDA-enabled GPU platforms with iterative
 GMRES solver to boost performance of the analysis method.  To further
-speed up the GMRES solving for Newton update equation, we have
+speed up the GMRES solving for the Newton update equation, we have
 employed the matrix-free Krylov basis generation technique.  The
 proposed method also applies the more robust Gear-2 integration to
 compute the sensitivity matrix.  Experimental results from several
 integrated on-chip power converters have shown that the proposed GPU
 envelope-following algorithm can lead to about 10$\times$ speedup
 compared to its CPU counterpart, and 100$\times$ faster than the
-traditional envelope-following methods while still keeps the similar
+traditional envelope-following methods while still keep the similar
 accuracy.
 
 
@@ -76,7 +75,7 @@ accuracy.
 \begin{Glossary}
 \item[Envelope-Following] In transient simulation of switching power circuits,
 nodal voltage waveforms in neighboring high frequency clock cycles are similar,
-but not exactly the duplicates. Envelope-following technique approximates
+but not exactly duplicates. Envelope-following technique approximates
 the slowly changing transient trend over a lot of clock cycles
 without calculating waveforms in all cycles.
 \end{Glossary}