Eliminate common subexpressions Eliminate unnecessary assignments Rename classes, fields, and methods Reorder or change bytecodes
3.4.2.14 Eliminate common subexpressions
Eliminating common subexpressions is similar to code motion. In this case, though, the compiler identifies an expression that is common to more than one statement and does not need to be calculated more than once. The following example uses the same calculation twice to map two pairs of variables: z1 = x Maths.absy + x; z2 = x Maths.absy + y; After a compiler has analyzed this code to eliminate the common subexpression, the code becomes: int t1 = x Maths.absy; z1 = t1 + x; z2 = t1 + y;3.4.2.15 Eliminate unnecessary assignments
An optimizing compiler should eliminate any unnecessary assignments. The following example is very simplistic: int x = 1; x = 2; This should obviously be converted into one statement: int x = 2; Although you wont often see this type of example, it is not unusual for chained constructor s to repeatedly assign to an instance variable in essentially the same way. An optimizing compiler should eliminate all extra unnecessary assignments.3.4.2.16 Rename classes, fields, and methods
Some compilers rename classes, fields, and methods for various reasons, such as for obfuscating the code making the code difficult to understand if it were decompiled. Renaming especially to one- character names [6] can make everything compiled much smaller, significantly reducing classloading times and network download times. [6] For example, the DashO optimizer renames everything possible to one-character names.3.4.2.17 Reorder or change bytecodes
An optimizing compiler can reorder or change bytecode instructions to make methods faster. Normally, this reduces the number of instructions, but sometimes making an activity faster requires increasing the number of instructions. An example is where a switch statement is used with a list of unordered, nearly consecutive values for case statements. An optimizing compiler can reorder the case statements so that the values are in order, insert extra case s to make the values fully consecutive, and then use a faster switch bytecode to execute the switch statement. The optimization for switch statements is extensively covered in Chapter 7 . - 68 -3.4.2.18 Generate information to help a VM
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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