1. Optimization

2. CS352 - Software Engineering (AY2005)2 Introduction Optimization has goals that may appear to run counter to good software engineering practices. The goal of optimization is to generate code that is highly efficient in terms of: –Space usage –Execution time. There are means to produce code that is efficient that still satisfies the desirable properties of well engineered software: –Maintainable –Modular –Well structured –Etc

3. CS352 - Software Engineering (AY2005)3 The basics While is may seem obvious, the first step in producing efficient and optimized code is to be familiar with the programming language you are using. Take time to browse the API to find out what it provides. Take time to read a textbook (or two) to see what advice more expert users may have to pass on. Take time to read other people’s code. Take time to search the web for helpful advice –Remember to test the advice! Just because you found the information on the web (or in a textbook for that matter), does not mean it is correct. Take time to gain experience. –It is estimated that it takes about 10 years to gain all the necessary experience to be an expert programmer. –Consider a graduate degree. Take time to learn multiple languages and paradigms (even if we do not teach them to you).

4. CS352 - Software Engineering (AY2005)4 Software engineering Software engineering teaches us to: 1.Comment code. 2.Adhere to code conventions (standards). 3.Make use of libraries. 4.Provide small working examples illustrating how your code should be used. 5.Thoroughly test your code. 6.Back up your code. 7.Use tools to make our life easier. None of these (with the exception of point 3 sometimes) needs to be sacrificed in order to write efficient, correct and optimized code.

5. CS352 - Software Engineering (AY2005)5 Software engineering The software engineering lifecycle teaches us that there is more to more producing a program than writing the code. We need to: –Understand the problem/requirements. –Design a solution –Document our actions and our code. –Fully test the implementation to ensure that it meets the requirements (quality assurance). –Maintain the system.

6. CS352 - Software Engineering (AY2005)6 Requirements gathering This is the first place we start when we want to produce optimized code. We need to understand precisely what the problem is and design a solution to deliver exactly what is needed. –If we believe that the system will be reused and a more general solution is necessary, then that forms part of the requirements on the software. Determine the criteria that decides the solution is efficient: –Fast execution? –Minimized space utilization? –Remember the space/time tradeoff. Select appropriate data structures. Select appropriate algorithms. Test your hypothesis. Measure your success – hw else will you know you have succeeded?

7. CS352 - Software Engineering (AY2005)7 Data structures and algorithms We will look at some examples in the near future. We will see that understanding the problem is important and that we do not always have to produce the most general code to produce a solution that satisfies the requirements. Exercise: –Imagine you want to build a spell checker and that you have only limited memory available. –Think about how you will store the words so that you minimize space utilization. –Think about how you will store the words to ensure fast and efficient look-up. –Estimate how many words you would need in your dictionary for it to be effective and how much space your data structure would use to do this. We will examine this problem later.

8. CS352 - Software Engineering (AY2005)8 Understand your compiler Compilers for languages usually come with a collection of switches. These are flags that you set to influence of the behavior of the compiler (e.g., -o on the javac command under unix). –Use the man command on unix to find out more about the compiler flags available for javac. –Note that javac –O can has some bugs and sometimes generates incorrect bytecode!!!!! These flags often allow programmers to set the amount of optimization that the compiler performs on your behalf as it generates the bytecode. –These optimizations, such as loop unrolling etc, are performed by the compiler to decrease execution speed, or minimize space used (e.g., the size of the bytecode). These work with (are not a replacement for) careful selection of data structures and algorithms.

9. CS352 - Software Engineering (AY2005)9 Your code Loop invariant code motion: –If an expression inside a loop doesn't change after the loop is entered (i.e. it's invariant), calculate the value of the expression outside the loop and assign it to a temporary variable. Then use the temporary variable within the loop. –Note that we could also treat a.length as a loop invariant-- Speed improvments of 7-11% in tight loops have been observed, in both interpreted and JIT-compiled VMs. for (i = 0; i < a.length; i++) { float tmp = c * d; b[i] = a[i] + c * d; for (i = 0; i < a.length; i++) { } b[i] = a[i] + tmp; } –Don’t rely on the compiler to do the optimization for you – do is explicitly yourself.

10. CS352 - Software Engineering (AY2005)10 Your code Common subexpression elimination: –If an expensive expression (for example, the result of a method call) is used more than once within a block of code, calculate it once and put it into a temporary variable for subsequent reuse. double d = a * Math.sqrt (c);double tmp = Math.sqrt (c); double e = b * Math.sqrt (c); double d = a * tmp; double e = b * tmp;

11. CS352 - Software Engineering (AY2005)11 Your code strength reduction: –Use cheaper operations in place of expensive ones. For example, use compound assignment operators such as += instead of...=...+..., since they result in fewer bytecode instructions. –You can also use shifts instead of multiplication by powers of two, multiplication instead of exponentiation, etc, although mathematical optimizations of this type generally have little benefit unless you're using a just-in-time compiler. for (i = 0; i < a.length; i++) { a[i] = a[i] + x; a[i] += x; } –Adding extra reference variables to allow the compiler to eliminate opcodes or use faster bytecodes can also be considered a case of strength reduction. For example, if you're repeatedly accessing elements in a single row of a 2D array, make a 1D array variable that points to that row. Similarly, if you have a subclass that performs lots of operations on an object defined in its superclass, making a reference to the object in the subclass with super and then using that reference directly will enable the compiler to replace getfield opcodes with aload opcodes (FASTER).

12. CS352 - Software Engineering (AY2005)12 Your code Variable allocation: –For desperate optimizers only. The first four numeric variables or arguments in a method are accessed using via shorter bytecode instructions, although only three are usable in non-static methods. –If you declare your most frequently-used variables first (e.g., loop indices), the inner bytecode loops of your methods will be marginally shorter and possibly faster. –Note that although the number of bytecodes for the inner loop is the same, the length of the bytecode has decreased. int[] a = (int[]) pop (); int i; int[] b = (int[]) pop (); int[] a = (int[]) pop (); int[] dst = new int[a.length]; int[] b = (int[]) pop (); int i; int[] dst = new int[a.length];for (i = 0; i < a.length; i++) { dst[i] = a[i] + b[i]; }

13. CS352 - Software Engineering (AY2005)13 Your code Just-in-time compilers: –Make sure your users have a just-in-time compiler instead of a standard interpreted Java VM. JIT compilers typically improve the performance of non-graphical Java primitives by 10-30 times. Browsers with JIT compilers include the Win32 and Mac versions of Netscape Navigator 3.0 and Internet Explorer 3.0.

14. CS352 - Software Engineering (AY2005)14 Your code Exploiting multiprocessors: –If you have a multiprocessor and a Java VM that can spread threads across processors (and currently these are big ifs), you can improve performance by multithreading, either manually or through the use of a restructuring compiler such as JAVAR. Native methods: –If you're don't care about cross-platform portability, native methods will get you the speed of raw C (or Fortran, or C++, or...). Fallback code lets your program continue even if native methods aren't available. Translation into C: –There are currently four freely-available tools to translate Java into C: j2c from Japan, JCC from Nik Shaylor, Toba (formerly Juice) from Arizona, and Harissa (formally Salsa) from France. Toba and Harissa are both products of active research groups.

15. CS352 - Software Engineering (AY2005)15 Your code Graphics: –Use clipping to reduce the amount of work done in repaint(), double buffering to improve perceived speed, and image strips or compression to speed up downloading times. Animation in Java Applets from JavaWorld and Performing Animation from Sun are two good tutorials. Remember to use high-level primitives; it's much faster to call drawPolygon() on a bunch of points than looping with drawLine(). And if you have to draw a single pixel drawLine (x,y,x,y) may be faster than fillRect (x,y,1,1).

16. CS352 - Software Engineering (AY2005)16 Your code Input/output: –Use BufferedInputStream and BufferedOutputStream or equivalent buffered methods wherever possible; doing I/O a single byte at a time is generally too slow to be practical. Note that the JDK 1.0.2 I/O classes use lots of synchronization, so you might get better performance by using a single "bulk" call such as readFully and then interpreting the data yourself.

17. CS352 - Software Engineering (AY2005)17 Your code Synchronization: –In the JDK interpreter, calling a synchronized method is typically 10 times slower than calling an unsynchronized method. With JIT compilers, this performance gap has increased to 50-100 times. Avoid synchronized methods if you can -- if you can't, synchronizing on methods rather than on code blocks is slightly faster.

18. CS352 - Software Engineering (AY2005)18 Your code Exceptions: –You should only use exceptions where you really need them- -- not only do they have a high basic cost, but their presence can hurt compiler analysis. The costs of Strings: –The String concatenation operator + looks innocent but involves a lot of work: a new StringBuffer is created, the two arguments are added to it with append(), and the final result is converted back with a toString(). This costs both space and time. In particular, if you're appending more than one String, consider using a StringBuffer directly instead.

19. CS352 - Software Engineering (AY2005)19 Your code Using API classes: –Use classes from the Java API when they offer native machine performance that you can't match using Java. For example, arraycopy() is much faster than using a loop to copy an array of any significant size. Replacing API classes: –Sometimes API classes do more than you need, with a corresponding increase in execution time; for these you can write specialized versions that do less but run faster. For example, in one application where I needed a container to store lots of arrays I replaced the original Vector with a faster dynamic array of objects. As another example, Paul Houle has produced a set of random-number generators that are much faster than Math.random() (and have quality guarantees too).

20. CS352 - Software Engineering (AY2005)20 Your code Overriding API methods: –If you're using a class from the Java API and are seeing performance problems with one method, try defining a subclass which overrides that method with your own (hopefully more efficient) version. Avoiding expensive constructs: –Sometimes Java constructs are so expensive that it can be worth making your data structures or code a little more complex to work around the problem. For example, you can add a type id number to objects to avoid paying the cost of an instanceof (this also allows you to use the result in a switch). Similarly, in a long inheritance tree you can avoid casting by including a method that returns a value of the type you would otherwise cast to.

21. CS352 - Software Engineering (AY2005)21 Your code Avoiding expensive data structures: –In a similar manner to the constructs above, expensive Java data structures can be replaced with simpler ones at the cost of some extra code complexity. For example, it can be up to twice as expensive to access a two-dimensional array as a one-dimensional array, due to the extra indirections. Know your switches: –A switch statement is compiled into one of two bytecodes, depending on the sparsity of the cases you're switching on. The first, where the numbers are close together, uses a fast direct lookup. The second, where the numbers are further apart, uses a slower search through a table. Look at the bytecode your code is compiled into to find which you're using. This is particularly important if you're trying to replace a sequence of if statements with a switch.

22. CS352 - Software Engineering (AY2005)22 Your code Function inlining: –Java compilers can only inline a method if it is final, private, or static (It has been noted that javac will only inline if a method has no local variables). If your code spends lots of time calling a method that has none of these modifiers, consider writing a version that is final.

23. CS352 - Software Engineering (AY2005)23 Your code Reusing objects: –It takes a long time to create an object (see Java microbenchmarks for exactly how long), so it's often worth updating the fields of an old object and reusing it rather than creating a new object. For example, rather than creating a new Font object in your paint method you can declare it as an instance object, initialize it once, and then just update it when necessary in paint. Similarly, rather than allowing the garbage collector to deal with objects you've removed from a linked list, you can store them in a free list, to be reused the next time you need to add a new object. This can be particularly important for graphics objects like Rectangles, Points and Fonts. See also "Not using garbage collection", from JavaWorld.Java microbenchmarksNot using garbage collection High-level optimizations: –For a higher-level approach to optimizing the structure of object- oriented code, the online book "Object-Oriented System Development" has a chapter on performance optimization.Object-Oriented System Developmentperformance optimization

24. CS352 - Software Engineering (AY2005)24 Tools Profiling: –To profile a (single-threaded) application, use java -prof. To profile an applet, use java -prof sun.applet.AppletViewer myfile.html. The profile file can then be analyzed using a tool such as Profile Viewer or HyperProf. You can also use the profiling tools built into an IDE such as VisionSoft Note that commercial profilers such as Optimize It! can profile both time and memory.

25. CS352 - Software Engineering (AY2005)25 Tools Disassembly: –Use javap -c to see the bytecode that your Java is compiled into: javac -O test.java javap -c test | more To understand the bytecode, read the Java VM spec.

26. CS352 - Software Engineering (AY2005)26 Tools Timing: –Write a timing harness to wrap around code fragments so that you can benchmark them. You can either adapt the old thread-based HotJava Performance Tests, or just use a simple loop. Note that system.currentTimeMillis() returns the time of day, not the process time, so all benchmarking should be done on an idle machine. Call system.gc() before every timing run to minimize inconsistent results due to garbage collection in the middle of a run. On systems with sub-millisecond clocks you can use native methods to access them (e.g., gettimeofday() or getrusage() on Unix systems).HotJava Performance Tests

27. CS352 - Software Engineering (AY2005)27 Tools Memory use: –You can write a memory-use harness in just the same way you'd write a timing harness, replacing calls to system.currentTimeMillis() with calls to: long freemem () { System.gc(); return Runtime.getRuntime().freeMemory(); }

28. CS352 - Software Engineering (AY2005)28 Optimizing for space Reducing code size is particularly important for Java applets, since it directly affects the time taken to download an applet. Use JAR (or zip, or CAB) files: –To avoid the overhead of loading individual class and data files, JDK 1.1 supports Java archive (JAR) files. Previously, JDK 1.02 and Netscape Navigator 3.0 supported zip files, while Microsoft Internet Explorer 3.0 supported CAB files. Don't reinvent API classes: –Use or extend a class from the Java API wherever possible. Sun has written the classes so that you don't have to.

29. CS352 - Software Engineering (AY2005)29 Optimizing for space Exploit inheritance: –Use inheritance in your own code: the more methods you can inherit, the less code you have to write. Turn on compiler optimization: –Use javac -O. This inlines functions (which makes the bytecode bigger) and removes line numbers (which makes it smaller). Unless you use lots of inlinable functions, the removal of line numbers will dominate and your bytecode will get smaller. However, note that things can sometimes be inlined when they shouldn't!!

30. CS352 - Software Engineering (AY2005)30 Optimizing for space Separate out common code: –Put code that is used in several different places into its own method (the reverse of inlining code for speed). Don't initialize big arrays: –Although array initialization is a single statement in Java, the generated bytecode inserts one element at a time. If you've got a big array, this requires a lot of bytecode. You can save space by storing your data in a String and then parsing it into your array at runtime.

31. CS352 - Software Engineering (AY2005)31 Optimizing for space Dates are big (not just broken) –Date objects take a surprising amount of space for something with such limited functionality. If you're storing a lot of them, considering using longs instead, and recreating Date objects from them as necessary. Use short names: –The names of visible entities (i.e., class, method and instance variable names) are listed in full in the class file, so using short names actually saves space. Code obfuscators such as Hashjava, Jobe, Obfuscate and Jshrink will rewrite your class files to use shorter (and incomprehensible) names.

32. CS352 - Software Engineering (AY2005)32 Optimizing for space Put static final constants in interfaces: –Constants defined using static final are included in the class file as well as being inlined. If you instead define them in an interface that you then implement, you can avoid this extra space overhead.

33. CS352 - Software Engineering (AY2005)33 Optimizing for space Watch for string concatenation: –Using + as a string concatenation operator will result in a method call if the operands are not compile-time constants. Unrolling a loop to eliminate string concatenation can therefore save space. Again, this might not be worth the effort. For example, the following loop is compiled into 48 bytes of bytecode: for (int i = 0; i < 3; i++){ imgs[i] = getImage (getCodeBase(), "G" + i + ".gif"); } –By unrolling the loop we eliminate the runtime concatenations and reduce the size of the bytecode to 39 bytes: imgs[0] = getImage (getCodeBase(), "G0.gif"); imgs[1] = getImage (getCodeBase(), "G1.gif"); imgs[2] = getImage (getCodeBase(), "G2.gif"); –Note that the three instances of getCodeBase() are a good candidate for common subexpression elimination.common subexpression elimination

34. CS352 - Software Engineering (AY2005)34 Discussion You were asked to think about the space and time needs for a spelling checker. The ability to estimate with a reasonable degree of accuracy is an essential skill. These “back of an envelope” calculations will give you a guide to the expected performance or resource needs of your proposed solution BEFORE you implement it and discover that it doesn’t work. Lets discuss the expected space and time needs of the various approaches that the class has considered for the implementation of a spelling checker (which is really just a searching algorithm…).