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  /packages/apps/UnifiedEmail/src/com/google/android/mail/common/base/
UnicodeEscaper.java 89 * this method for efficiency. The base class implementation determines
132 * this method for efficiency by inlining the implementation of
  /toolchain/binutils/binutils-2.27/bfd/doc/
bfd.texinfo 109 their own use, for greater efficiency.
188 but loses efficiency when applied to formats such as S-records and
  /art/runtime/gc/accounting/
space_bitmap.h 232 // This bitmap itself, word sized for efficiency in scanning.
  /developers/build/prebuilts/gradle/WatchFace/Wearable/src/main/java/com/example/android/wearable/watchface/util/
Gles2ColoredTriangleList.java 208 * Creates a program to draw triangle lists. For optimal drawing efficiency, one program
  /developers/samples/android/wearable/wear/WatchFace/Wearable/src/main/java/com/example/android/wearable/watchface/util/
Gles2ColoredTriangleList.java 208 * Creates a program to draw triangle lists. For optimal drawing efficiency, one program
  /development/samples/browseable/WatchFace/Wearable/src/com.example.android.wearable.watchface/
Gles2ColoredTriangleList.java 208 * Creates a program to draw triangle lists. For optimal drawing efficiency, one program
  /external/ImageMagick/ImageMagick/script/
openmp.html 65 <p>It can be difficult to predict behavior in a parallel environment. Performance might depend on a number of factors including the compiler, the version of the OpenMP library, the processor type, the number of cores, the amount of memory, whether hyperthreading is enabled, the mix of applications that are executing concurrently with ImageMagick, or the particular image-processing algorithm you utilize. The only way to be certain of the optimal performance, in terms of the number of threads, is to benchmark. ImageMagick includes progressive threading when benchmarking a command and returns the elapsed time and efficiency for one or more threads. This can help you identify how many threads are the most efficient in your environment. Here is an example benchmark for threads 1-8:</p>
  /external/ImageMagick/www/
openmp.html 69 <p>It can be difficult to predict behavior in a parallel environment. Performance might depend on a number of factors including the compiler, the version of the OpenMP library, the processor type, the number of cores, the amount of memory, whether hyperthreading is enabled, the mix of applications that are executing concurrently with ImageMagick, or the particular image-processing algorithm you utilize. The only way to be certain of the optimal performance, in terms of the number of threads, is to benchmark. ImageMagick includes progressive threading when benchmarking a command and returns the elapsed time and efficiency for one or more threads. This can help you identify how many threads are the most efficient in your environment. Here is an example benchmark for threads 1-8:</p>
  /external/antlr/antlr-3.4/runtime/JavaScript/src/org/antlr/runtime/tree/
BaseTreeAdaptor.js 93 * efficiency.
  /external/antlr/antlr-3.4/runtime/ObjC/ANTLR.framework/Headers/
ANTLRBaseTreeAdaptor.h 112 * efficiency.
ANTLRTreeAdaptor.h 100 * efficiency.
  /external/antlr/antlr-3.4/runtime/ObjC/ANTLR.framework/Versions/A/Headers/
ANTLRBaseTreeAdaptor.h 112 * efficiency.
ANTLRTreeAdaptor.h 100 * efficiency.
  /external/antlr/antlr-3.4/runtime/ObjC/ANTLR.framework/Versions/Current/Headers/
ANTLRBaseTreeAdaptor.h 112 * efficiency.
ANTLRTreeAdaptor.h 100 * efficiency.
  /external/antlr/antlr-3.4/runtime/ObjC/Framework/
ANTLRBaseTreeAdaptor.h 104 * efficiency.
ANTLRTreeAdaptor.h 96 * efficiency.
  /external/chromium-trace/catapult/common/py_trace_event/py_trace_event/
trace_event.py 198 trace_event records traces into an in-memory buffer for efficiency. Flushing
  /external/flatbuffers/docs/source/
Compiler.md 86 at the cost of efficiency (object allocation). Recommended only to be used
  /external/guava/guava/src/com/google/common/collect/
AbstractMapBasedMultiset.java 54 * Cache the size for efficiency. Using a long lets us avoid the need for
  /external/guava/guava-gwt/src-super/com/google/common/collect/super/com/google/common/collect/
AbstractMapBasedMultiset.java 51 * Cache the size for efficiency. Using a long lets us avoid the need for
  /external/icu/android_icu4j/src/main/java/android/icu/impl/
Trie2_32.java 88 // Note: this expression could be refactored for slightly improved efficiency, but
  /external/icu/android_icu4j/src/main/java/android/icu/impl/number/
CompactData.java 217 // NOTE: This strategy for computing the number of zeros is a hack for efficiency.
  /external/icu/icu4c/source/i18n/
collationsettings.h 243 * are omitted for efficiency; they are handled by reorder(p) via the reorderTable.
  /external/icu/icu4j/main/classes/core/src/com/ibm/icu/impl/
Trie2_16.java 87 // Note: this expression could be refactored for slightly improved efficiency, but

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