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XlaBuilder is the C++ API for building up XLA computations -- conceptually this is like building up a function, full of various operations, that you could execute over and over again on different input data.

Some background, XLA serves as an abstraction layer for creating executable blobs that run on various target accelerators (CPU, GPU, TPU, IPU, ...), conceptually kind of an "accelerator virtual machine" with conceptual similarities to earlier systems like PeakStream or the line of work that led to ArBB.

The XlaBuilder is a way to enqueue operations into a "computation" (similar to a function) that you want to run against the various set of accelerators that XLA can target. The operations at this level are often referred to as "High Level Operations" (HLOs).

The returned XlaOp represents the result of the operation you've just enqueued. (Aside/nerdery: this is a classic technique used in "builder" APIs that represent the program in "Static Single Assignment" form under the hood, the operation itself and the result of the operation can be unified as one concept!)

XLA computations are very similar to functions, so you can think of what you're doing with an XlaBuilder like building up a function. (Aside: they're called "computations" because they do a little bit more than a straightforward function -- conceptually they are coroutines that can talk to an external "host" world and also talk to each other via networking facilities.)

So the fact XlaOps can't be used across XlaBuilders may make more sense with that context -- in the same way that when building up a function you can't grab intermediate results in the internals of other functions, you have to compose them with function calls / parameters. In XlaBuilder you can Call another built computation, which is a reason you might use multiple builders.

As you note, you can choose to inline everything into one "mega builder", but often programs are structured as functions that get composed together, and ultimately get called from a few different "entry points". XLA currently aggressively specializes for the entry points it sees API users using, but this is a design artifact similar to inlining decisions, XLA can conceptually reuse computations built up / invoked from multiple callers if it thought that was the right thing to do. Usually it's most natural to enqueue things into XLA however is convenient for your description from the "outside world", and allow XLA to inline and aggressively specialize the "entry point" computations you've built up as you execute them, in Just-in-Time compilation fashion.

Those samples depend on JDK internals.

Looks like since JDK 9 and JDK-8152907, Math.log is no longer intrinsified into C2 intermediate representation. Instead, a direct call to a quick LIBM-backed stub is made. This is usually faster for the code that actually uses the result. Notice how measureCorrect is faster in JDK 17 output in your case.

But for JMH samples, it limits the the compiler optimizations around the Math.log, and dead code / folding samples do not work properly. The fix it to make samples that do not rely on JDK internals without a good reason, and instead use a custom written payload.

This is being done in JMH here:

• https://bugs.openjdk.java.net/browse/CODETOOLS-7903094
• https://github.com/openjdk/jmh/pull/60

The following works by subclassing the relevant class, and duplicating code with the relevant changes. We also have to subclass the Client class, to overwrite the place where the gateway/websocket class is used. This results in a lot of duplicated code, however it does work, and requires neither dirty monkey-patching nor editing the library source code.

However, it does come with many of the same problems as editing the library source code - mainly that as the library is updated, this code will become out of date (if you're using the archived and obsolete version of the library, you have bigger problems instead).

To measure the branch you are interested in and particularly the scenario when while loop becomes hot, I've used the following benchmark:

Jim Rogers already discussed using inheritance. You can also use composition if you like by creating an internal non tagged type (which allows defaults), make the Operand.Instance type tagged private, have the private implementation use the internal non tagged version, and just add what operations you need to set and get the operands:

Usually I'd say your question is quite broad and the use case very tricky and requires a lot of not so trivial steps to approach. But I see you also have put quite an effort in research and your question so I'll try to do the same (little Christmas Present) ;)

In general I think generics is not what you want to use here. Generics always require compile time constant parameters.

As I am only on the phone and don't know I can't give you a full solution right now but I hope I can bring you into the right track.

I think the simplest thing would rather be a common interface such as e.g.

Parentheses are not needed here:

The problem here is that if you remove your Var from the shared variable, what would be left there? What happens if any other copy of your Arc is left somewhere and it tries to access the now removed object?

There are several possible answers to that question:

If that is the case, you can use Arc::try_unwrap() to get to the inner mutex. Then another into_inner() to get the real value.

I'm unsure as to the cause of that log message, but I do see that you are returning a response from your function before it completes all of its work. In a deployed function, as soon as the function returns, all further actions should be treated as if they will never be executed as documented here. An "inactive" function might be terminated at any time, is severely throttled and any network calls you make (like setting data in the RTDB) may never be executed.

I know you are new to this, but its a good habit to get into now: don't assume the person calling your function is you. Check for problems like missing query parameters and dodgy data before you blindly action something. The Admin SDK bypasses your database's security rules and if you are not careful a malicious user can cause some damage (e.g. a user that updates /users/$theirUid/roles/admin to true).