In java, is it more efficient to use byte or short instead of int and float instead of double?

Question

I've noticed I've always used int and doubles no matter how small or big the number needs to be. So in java, is it more efficient to use byte or short instead of int and float instead of double?

So assume I have a program with plenty of ints and doubles. Would it be worth going through and changing my ints to bytes or shorts if I knew the number would fit?

I know java doesn't have unsigned types but is there anything extra I could do if I knew the number would be positive only?

By efficient I mostly mean processing. I'd assume the garbage collector would be a lot faster if all the variables would be half size and that calculations would probably be somewhat faster too. ( I guess since I am working on android I need to somewhat worry about ram too)

(I'd assume the garbage collector only deals with Objects and not primitive but still deletes all the primitives in abandoned objects right? )

I tried it with a small android app I have but didn't really notice a difference at all. (Though I didn't "scientifically" measure anything.)

Am I wrong in assuming it should be faster and more efficient? I'd hate to go through and change everything in a massive program to find out I wasted my time.

Would it be worth doing from the beginning when I start a new project? (I mean I think every little bit would help but then again if so, why doesn't it seem like anyone does it.)

Answer 1

Am I wrong in assuming it should be faster and more efficient? I'd hate to go through and change everything in a massive program to find out I wasted my time.

Short answer

Yes, you are wrong. In most cases, it makes little difference in terms of space used.

It is not worth trying to optimize this ... unless you have clear evidence that optimization is needed. And if you do need to optimize memory usage of object fields in particular, you will probably need to take other (more effective) measures.

Longer answer

The Java Virtual Machine models stacks and object fields using offsets that are (in effect) multiples of a 32 bit primitive cell size. So when you declare a local variable or object field as (say) a byte, the variable / field will be stored in a 32 bit cell, just like an int.

There are two exceptions to this:

• long and double values require 2 primitive 32-bit cells
• arrays of primitive types are represent in packed form, so that (for example) an array of bytes hold 4 bytes per 32bit word.

So it might be worth optimizing use of long and double ... and large arrays of primitives. But in general no.

^{In theory, a JIT might be able to optimize this, but in practice I've never heard of a JIT that does. One impediment is that the JIT typically cannot run until after there instances of the class being compiled have been created. If the JIT optimized the memory layout, you could have two (or more) "flavors" of object of the same class ... and that would present huge difficulties.}

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Revisitation

Looking at the benchmark results in @meriton's answer, it appears that using short and byte instead of int incurs a performance penalty for multiplication. Indeed, if you consider the operations in isolation, the penalty is significant. (You shouldn't consider them in isolation ... but that's another topic.)

I think the explanation is that JIT is probably doing the multiplications using 32bit multiply instructions in each case. But in the byte and short case, it executes extra instructions to convert the intermediate 32 bit value to a byte or short in each loop iteration. (In theory, that conversion could be done once at the end of the loop ... but I doubt that the optimizer would be able to figure that out.)

Anyway, this does point to another problem with switching to short and byte as an optimization. It could make performance worse ... in an algorithm that is arithmetic and compute intensive.

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Secondary questions

I know java doesn't have unsigned types but is there anything extra I could do if I knew the number would be positive only?

No. Not in terms of performance anyway. (There are some methods in Integer, Long, etc for dealing with int, long, etc as unsigned. But these don't give any performance advantage. That is not their purpose.)

(I'd assume the garbage collector only deals with Objects and not primitive but still deletes all the primitives in abandoned objects right? )

Correct. A field of an object is part of the object. It goes away when the object is garbage collected. Likewise the cells of an array go away when the array is collected. When the field or cell type is a primitive type, then the value is stored in the field / cell ... which is part of the object / array ... and that has been deleted.

Answer 2

That depends on the implementation of the JVM, as well as the underlying hardware. Most modern hardware will not fetch single bytes from memory (or even from the first level cache), i.e. using the smaller primitive types generally does not reduce memory bandwidth consumption. Likewise, modern CPU have a word size of 64 bits. They can perform operations on less bits, but that works by discarding the extra bits, which isn't faster either.

The only benefit is that smaller primitive types can result in a more compact memory layout, most notably when using arrays. This saves memory, which can improve locality of reference (thus reducing the number of cache misses) and reduce garbage collection overhead.

Generally speaking however, using the smaller primitive types is not faster.

To demonstrate that, behold the following benchmark:

public class Benchmark {      public static void benchmark(String label, Code code) {         print(25, label);                  try {             for (int iterations = 1; ; iterations *= 2) { // detect reasonable iteration count and warm up the code under test                 System.gc(); // clean up previous runs, so we don't benchmark their cleanup                 long previouslyUsedMemory = usedMemory();                 long start = System.nanoTime();                 code.execute(iterations);                 long duration = System.nanoTime() - start;                 long memoryUsed = usedMemory() - previouslyUsedMemory;                                  if (iterations > 1E8 || duration > 1E9) {                      print(25, new BigDecimal(duration * 1000 / iterations).movePointLeft(3) + " ns / iteration");                     print(30, new BigDecimal(memoryUsed * 1000 / iterations).movePointLeft(3) + " bytes / iteration\n");                     return;                 }             }         } catch (Throwable e) {             throw new RuntimeException(e);         }     }          private static void print(int desiredLength, String message) {         System.out.print(" ".repeat(Math.max(1, desiredLength - message.length())) + message);     }          private static long usedMemory() {         return Runtime.getRuntime().totalMemory() - Runtime.getRuntime().freeMemory();     }      @FunctionalInterface     interface Code {         /**          * Executes the code under test.          *           * @param iterations          *            number of iterations to perform          * @return any value that requires the entire code to be executed (to          *         prevent dead code elimination by the just in time compiler)          * @throws Throwable          *             if the test could not complete successfully          */         Object execute(int iterations);     }      public static void main(String[] args) {         benchmark("long[] traversal", (iterations) -> {             long[] array = new long[iterations];             for (int i = 0; i < iterations; i++) {                 array[i] = i;             }             return array;         });         benchmark("int[] traversal", (iterations) -> {             int[] array = new int[iterations];             for (int i = 0; i < iterations; i++) {                 array[i] = i;             }             return array;         });         benchmark("short[] traversal", (iterations) -> {             short[] array = new short[iterations];             for (int i = 0; i < iterations; i++) {                 array[i] = (short) i;             }             return array;         });         benchmark("byte[] traversal", (iterations) -> {             byte[] array = new byte[iterations];             for (int i = 0; i < iterations; i++) {                 array[i] = (byte) i;             }             return array;         });                  benchmark("long fields", (iterations) -> {             class C {                 long a = 1;                 long b = 2;             }                          C[] array = new C[iterations];             for (int i = 0; i < iterations; i++) {                 array[i] = new C();             }             return array;         });         benchmark("int fields", (iterations) -> {             class C {                 int a = 1;                 int b = 2;             }                          C[] array = new C[iterations];             for (int i = 0; i < iterations; i++) {                 array[i] = new C();             }             return array;         });         benchmark("short fields", (iterations) -> {             class C {                 short a = 1;                 short b = 2;             }                          C[] array = new C[iterations];             for (int i = 0; i < iterations; i++) {                 array[i] = new C();             }             return array;         });         benchmark("byte fields", (iterations) -> {             class C {                 byte a = 1;                 byte b = 2;             }                          C[] array = new C[iterations];             for (int i = 0; i < iterations; i++) {                 array[i] = new C();             }             return array;         });          benchmark("long multiplication", (iterations) -> {             long result = 1;             for (int i = 0; i < iterations; i++) {                 result *= 3;             }             return result;         });         benchmark("int multiplication", (iterations) -> {             int result = 1;             for (int i = 0; i < iterations; i++) {                 result *= 3;             }             return result;         });         benchmark("short multiplication", (iterations) -> {             short result = 1;             for (int i = 0; i < iterations; i++) {                 result *= 3;             }             return result;         });         benchmark("byte multiplication", (iterations) -> {             byte result = 1;             for (int i = 0; i < iterations; i++) {                 result *= 3;             }             return result;         });     } } 

Run with OpenJDK 14 on my Intel Core i7 CPU @ 3.5 GHz, this prints:

     long[] traversal     3.206 ns / iteration      8.007 bytes / iteration       int[] traversal     1.557 ns / iteration      4.007 bytes / iteration     short[] traversal     0.881 ns / iteration      2.007 bytes / iteration      byte[] traversal     0.584 ns / iteration      1.007 bytes / iteration           long fields    25.485 ns / iteration     36.359 bytes / iteration            int fields    23.126 ns / iteration     28.304 bytes / iteration          short fields    21.717 ns / iteration     20.296 bytes / iteration           byte fields    21.767 ns / iteration     20.273 bytes / iteration   long multiplication     0.538 ns / iteration      0.000 bytes / iteration    int multiplication     0.526 ns / iteration      0.000 bytes / iteration  short multiplication     0.786 ns / iteration      0.000 bytes / iteration   byte multiplication     0.784 ns / iteration      0.000 bytes / iteration 

As you can see, the only significant speed savings occur when traversing large arrays; using smaller object fields yields negligible benefit, and computations are actually slightly slower on the small datatypes.

Overall, the performance differences are quite minor. Optimizing algorithms is far more important than the choice of primitive type.