Exception-Terminated Loops Loops and Switches
7.2 Exception-Terminated Loops
This is a technique for squeezing out the very last driblet of performance from loops. With this technique, instead of testing on each loop iteration to see whether the loop has reached its normal termination point, you use an exception generated at the end of the loop to halt the loop, thus avoiding the extra test on each run through the loop. I include this technique here mainly because it is a known performance-tuning technique, but I do not recommend using it, as I feel it is bad programming practice the phrase enough rope to hang yourself springs to mind. Ill illustrate the technique with some straightforward examples. The full class for testing the examples is listed later, after I discuss the test results. The tests themselves are very simple. Basically, each test runs two varieties of loops. The first variety runs a standard for loop as you normally write it: for int loopvar = 0; loopvar someMax; loopvar++ The second variety misses out the termination test in the for loop, thus making the loop infinite. But these latter loops are put inside a try-catch block to catch an exception that terminates the loop: try { for int loopvar = 0; ; loopvar++ ... exception is thrown when loop needs to terminate } catchException e {} The three tests I use are: • A loop that executes integer divisions. The unterminated variety throws an ArithmeticException when a division by zero occurs to terminate the loop. • A loop that initializes an array of integers. The unterminated variety throws an ArrayIndexOutOfBoundsException when the index of the array grows too large. • A loop that enumerates a Vector . The unterminated variety throws a NoSuchElementException when there are no more elements to enumerate. I found the results of my test runs summarized in Table 7-1 to be variable due to variations in memory allocation, disk paging, and garbage collection. The VMs using HotSpot technology could show quite variable behavior. The plain JDK 1.2 VM had a huge amount of trouble reclaiming memory for the later tests, even when I put in pauses and ran explicit garbage-collection calls more than once. For each set of tests, I tried to increase the number of loop iterations until the timings were over one second. For the memory-based tests, it was not always possible to achieve times of over a second: paging or out-of-memory errors were encountered. Table 7-1, Speedup Using Exception-Driven Loop Termination Speedups 1.21.2 no JIT 1.3
Parts
» OReilly.Java.performance tuning
» The Tuning Game System Limitations and What to Tune
» A Tuning Strategy Introduction
» Threading to Appear Quicker Streaming to Appear Quicker
» User Agreements Starting to Tune
» Setting Benchmarks Starting to Tune
» The Benchmark Harness Starting to Tune
» Taking Measurements Starting to Tune
» What to Measure Introduction
» Dont Tune What You Dont Need to Tune
» Measurements and Timings Profiling Tools
» Garbage Collection Profiling Tools
» Profiling Methodology Method Calls
» Java 2 cpu=samples Profile Output
» HotSpot and 1.3 -Xprof Profile Output
» JDK 1.1.x -prof and Java 2 cpu=old Profile Output
» Object-Creation Profiling Profiling Tools
» Monitoring Gross Memory Usage
» Replacing Sockets ClientServer Communications
» Performance Checklist Profiling Tools
» Garbage Collection Underlying JDK Improvements
» Replacing JDK Classes Underlying JDK Improvements
» VM Speed Variations VMs with JIT Compilers
» Other VM Optimizations Faster VMs
» Inline calls Remove dynamic type checks Unroll loops Code motion
» Literal constants are folded String concatenation is sometimes folded Constant fields are inlined
» Optimizations Performed When Using the -O Option
» Performance Effects From Runtime Options
» Compile to Native Machine Code
» Native Method Calls Underlying JDK Improvements
» Uncompressed ZIPJAR Files Underlying JDK Improvements
» Performance Checklist Underlying JDK Improvements
» Object-Creation Statistics Object Creation
» Pool Management Object Reuse
» Reusable Parameters Object Reuse
» String canonicalization Changeable objects
» Weak references Canonicalizing Objects
» Avoiding Garbage Collection Object Creation
» Preallocating Objects Lazy Initialization
» Performance Checklist Object Creation
» The Performance Effects of Strings
» Compile-Time Versus Runtime Resolution of Strings
» Converting bytes, shorts, chars, and booleans to Strings Converting floats to Strings
» Converting doubles to Strings
» Converting Objects to Strings
» Word-Counting Example Strings Versus char Arrays
» Line Filter Example HotSpot 1.0
» String Comparisons and Searches
» Sorting Internationalized Strings Strings
» The Cost of try-catch Blocks Without an Exception
» The Cost of try-catch Blocks with an Exception
» Using Exceptions Without the Stack Trace Overhead Conditional Error Checking
» no JIT 1.3 Variables Strings
» Method Parameters Performance Checklist
» Exception-Terminated Loops Loops and Switches
» no JIT 1.3 Loops and Switches
» Recursion Loops and Switches
» no HotSpot 1.0 2nd Loops and Switches
» Recursion and Stacks Loops and Switches
» Performance Checklist Loops and Switches
» Replacing System.out IO, Logging, and Console Output
» Logging From Raw IO to Smokin IO
» no JIT HotSpot 1.0 no JIT HotSpot 1.0 Serialization
» no IO, Logging, and Console Output
» Clustering Objects and Counting IO Operations
» Compression IO, Logging, and Console Output
» Performance Checklist IO, Logging, and Console Output
» Avoiding Unnecessary Sorting Overhead
» An Efficient Sorting Framework
» no HotSpot Better Than Onlogn Sorting
» User-Interface Thread and Other Threads
» Desynchronization and Synchronized Wrappers
» Avoiding Serialized Execution HotSpot 1.0
» no JIT no JIT HotSpot 1.0 Timing Multithreaded Tests
» Atomic Access and Assignment
» Free Load Balancing from TCPIP
» Load-Balancing Classes Load Balancing
» A Load-Balancing Example Load Balancing
» Threaded Problem-Solving Strategies Threading
» Collections Appropriate Data Structures and Algorithms
» Java 2 Collections Appropriate Data Structures and Algorithms
» Hashtables and HashMaps Appropriate Data Structures and Algorithms
» Cached Access Appropriate Data Structures and Algorithms
» Caching Example I Appropriate Data Structures and Algorithms
» Caching Example II Appropriate Data Structures and Algorithms
» Finding the Index for Partially Matched Strings
» Search Trees Appropriate Data Structures and Algorithms
» Comparing Communication Layers Distributed Computing
» Batching I Application Partitioning
» Compression Caching Low-Level Communication Optimizations
» Transfer Batching Low-Level Communication Optimizations
» Batching II Distributed Garbage Collection
» Performance Checklist Distributed Computing
» When Not to Optimize Tuning Class Libraries and Beans
» Scaling Design and Architecture
» Distributed Applications Design and Architecture
» Object Design Design and Architecture
» Use simulations and benchmarks Consider the total work done and the design overhead
» Tuning After Deployment When to Optimize
» User Interface Usability Training Server Downtime
» Performance Checklist When to Optimize
» Clustering Files Cached Filesystems RAM Disks, tmpfs, cachefs
» Disk Fragmentation Disk Sweet Spots
» RAM Underlying Operating System and Network Improvements
» Network Bottlenecks Network IO
» Performance Checklist Underlying Operating System and Network Improvements
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