One of my primary tasks right now is improving the speed of the Sphinx-4 recognizer. There are three battle-lines in this war on slowness: improving algorithms, improving application tuning, and optimizing the code. One of my primary tools in the war is Jfluid , a Java application profiler developed by the folks at Sun's research lab. JFluid works differently from other profilers ... instead of sampling your application periodically to find out where time is being spent, it instruments the byte codes. This has a number of advantages. First of all, the profiling results are exact, not approximate. Due to the vagaries of sampling, other profilers are apt to miss calls to some methods entirely. Since JFluid instruments the byte codes, it never misses a thing. If Jfluid says that a method has been called 1,232,123 times, you know that it really was. JFluid also lets you select a narrow subset of your application to profile. For instance, the typical recognition inner loop looks like this:
    while (!done) {
with a substantial fraction of the work taking place in growPaths(). With JFluid, you can turn on profiling for growPaths() and every method that is called (directly or indirectly) from growPaths() while leaving profiling off for scorePaths() and prunePaths(). Other profilers I've used require you to turn profiling on for the whole application which results in my having to wait much longer for answers as the profiler wastes time collecting data on scorePaths() and prunePaths().

JFluid is one of the best kept Java secrets. If you are working to improve your application's performance I highly recommend giving JFluid a try.


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