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optimization - What can I do in Java code to optimize for CPU caching?

When writing a Java program, do I have influence on how the CPU will utilize its cache to store my data? For example, if I have an array that is accessed a lot, does it help if it's small enough to fit in one cache line (typically 128 byte on a 64-bit machine)? What if I keep a much used object within that limit, can I expect the memory used by it's members to be close together and staying in cache?

Background: I'm building a compressed digital tree, that's heavily inspired by the Judy arrays, which are in C. While I'm mostly after its node compression techniques, Judy has CPU cache optimization as a central design goal and the node types as well as the heuristics for switching between them are heavily influenced by that. I was wondering if I have any chance of getting those benefits, too?

Edit: The general advice of the answers so far is, don't try to microoptimize machine-level details when you're so far away from the machine as you're in Java. I totally agree, so felt I had to add some (hopefully) clarifying comments, to better explain why I think the question still makes sense. These are below:

There are some things that are just generally easier for computers to handle because of the way they are built. I have seen Java code run noticeably faster on compressed data (from memory), even though the decompression had to use additional CPU cycles. If the data were stored on disk, it's obvious why that is so, but of course in RAM it's the same principle.

Now, computer science has lots to say about what those things are, for example, locality of reference is great in C and I guess it's still great in Java, maybe even more so, if it helps the optimizing runtime to do more clever things. But how you accomplish it might be very different. In C, I might write code that manages larger chunks of memory itself and uses adjacent pointers for related data.

In Java, I can't (and don't want to) know much about how memory is going to be managed by a particular runtime. So I have to take optimizations to a higher level of abstraction, too. My question is basically, how do I do that? For locality of reference, what does "close together" mean at the level of abstraction I'm working on in Java? Same object? Same type? Same array?

In general, I don't think that abstraction layers change the "laws of physics", metaphorically speaking. Doubling your array in size every time you run out of space is a good strategy in Java, too, even though you don't call malloc() anymore.

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The key to good performance with Java is to write idiomatic code, rather than trying to outwit the JIT compiler. If you write your code to try to influence it to do things in a certain way at the native instruction level, you are more likely to shoot yourself in the foot.

That isn't to say that common principles like locality of reference don't matter. They do, but I would consider the use of arrays and such to be performance-aware, idiomatic code, but not "tricky."

HotSpot and other optimizing runtimes are extremely clever about how they optimize code for specific processors. (For an example, check out this discussion.) If I were an expert machine language programmer, I'd write machine language, not Java. And if I'm not, it would be unwise to think that I could do a better job of optimizing my code than the experts.

Also, even if you do know the best way to implement something for a particular CPU, the beauty of Java is write-once-run-anywhere. Clever tricks to "optimize" Java code tend to make optimization opportunities harder for the JIT to recognize. Straight-forward code that adheres to common idioms is easier for an optimizer to recognize. So even when you get the best Java code for your testbed, that code might perform horribly on a different architecture, or at best, fail to take advantages of enhancements in future JITs.

If you want good performance, keep it simple. Teams of really smart people are working to make it fast.


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