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Performance of short-running Java CLI application

I'm building a java CLI utility application that processes some data from a file.
Apart from reading from a file, all the operations are done in-memory. The in-memory processing part is taking a surprisingly long time so I tried profiling it but could not pinpoint any specific function that performed particularly bad.
I was afraid that JIT was not able to optimize the program during a single run, so I benchmarked how the runtime changes between the consecutive executions of the function with all the program logic (including reading the input file) and sure enough, the runtime for the in-memory processing part goes down for several executions and becomes almost 10 times smaller already on the 5th run.
I tried shuffling the input data before every execution, but it doesn't have any visible effect on this. I'm not sure if some caching may be responsible for this improvement or the JIT optimizations done during the program run, but since usually the program is ran once at time, it always shows the worst performance.
Would it be possible to somehow get a good performance during the first run? Is there a generic way to optimize performance for a short-running java applications?

You probably cannot optimize startup time and performance by changing your application1, 2. And especially for a small application3. And I certainly don't think there are "generic" ways to do it; i.e. optimizations that will work for all cases.
However, there are a couple of JVM features that should improve performance for a short-lived JVM.
Class Data Sharing (CDS) is a feature that allows JIT compiled classes to be cached in the file system (as a CDS archive) and which is then reused by later of runs of your application. This feature has been available since Java 5 (though with limitations in earlier Java releases).
The CDS feature is controlled using the -Xshare JVM option.
-Xshare:dump generates a CDS archive during the run
-Xshare:off -Xshare:on and -Xshare:auto control whether an existing CDS archive will be used.
The other way to improve startup times for a HotSpot JVM is (was) to use Ahead Of Time (AOT) compilation. Basically, you compile your application to a native code binary using the jaotc command, and then run the executable it produces rather than the java command. The jaotc command is experimental and was introduced in Java 9.
It appears that jaotc was not included in the Java 16 builds published by Oracle, and is scheduled for removal in Java 17. (See JEP 410: Remove the Experimental AOT and JIT Compiler).
The current recommended way to get AOT compilation for Java is to use the GraalVM AOT Java compiler.
1 - You could convert into a client-server application where the server "up" all of the time. However, that has other problems, and doesn't eliminate the startup time issue for the client ... assuming that is coded in Java.
2 - According to #apangin, there are some other application tweaks that may could make you code more JIT friendly, though it will depend on what you code is currently doing.
3 - It is conceivable that the startup time for a large (long running) monolithic application could be improved by refactoring it so that subsystems of the application can be loaded and initialized only when they are needed. However, it doesn't sound like this would work for your use-case.

You could have the small processing run as a service: when you need to run it, "just" make a network call to that service (easier if it's HTTP because there are easy way to do it in Java). That way, the processing itself stays in the same JVM and will eventually get faster when JIT kicks in.
Of course, because it could require significant development, that is only valid if the processing itself:
is called often
has arguments that are easy to pass to the service (usually serialized as strings)
has arguments that don't require too much data to pass to the service (e.g. several MB binary content)

If JVM generates machine code, then where are the code files?

I read some materials about JVM and bytecode. I think it would be more efficient if JVM can translate bytecode into platform dependent machine code in the first time run, instead of interpreting them all the time.
However, I could not find such files in my project folders. There are only bin and src folders, which contain *.class bytecodes and *.java source codes.
So my questions are:
If Java interprets bytecode all the time, why not translate bytecode to machine code after the first run?
If they do generate machine code, where are the files?

Not an option since the environment can change between runs (e.g. upgrade of JVM)
In memory (or serialized to disk when needed)

If Java interprets bytecode all the time, why not translate bytecode
to machine code after the first run?
There are pros and cons to both ahead of time (AOT) and just in time (JIT) compilation.
The main advantage of AOT is that the compiler is generally allowed to take longer, so it can perform more sophisticated analysis and optimization. Another advantage is that the compiler doesn't have to be present at runtime on the target machine. The disadvantages are everything else.
The main advantage of JIT is that the compiler is able to make optimizations based on information known only at runtime. In fact, it is even possible to unoptimize and reoptimize code when conditions change. Furthermore, the JIT doesn't have to waste time optimizing code that is never or rarely run, unlike the AOT compiler.
Some languages are designed to favor one approach over the other. For example, C/C++ are designed for AOT, while Java is designed for JIT (though it can be compiled AOT with some restrictions). For example, Java has a heavy emphasis on virtual getters and setters, possibly for classes not loaded until runtime. But the JIT can see and inline these functions at runtime. By contrast, if you used virtual methods for every field access in C++, you'd pay a huge performance penalty.

It doesn't interpret code all the time. Interpreted code is translated into byte code after some time. You can tweak this "time" using -XX:CompileThreshold= (default is 10000) or you can turn off compilation completely.
In memory. There's a special area in memory called "Code cache". You can see how methods a compiled into the cache and how they are evicted from the cache using -XX:+PrintCompilation. The size of the cache is also configurable, see -XX:ReservedCodeCacheSize=.

Well, the JVM has preprocessed data but only for its own classes. Given the size of the JRE library and the fact that it usually doesn’t change, it’s a big win (you might look for files called classes.jsa).
However, even these files are not containing native code but only easier-to-process byte code.
The big point about code generation in Hot Spot JVMs is that they don’t compile code on a class or method basis as you seem to think. These JVMs compile code fragments spanning multiple interacting methods as the interaction is discovered during the self-profiling. These code blocks may span methods from the JRE, the extension libraries, 3rd party libraries in your class path and your application classes and hence are only valid for this specific combination.
During the compilation the information gathered about your program’s behavior will be used, e.g. code paths not taken might be elided and conditionals might be asserted to evaluate to a certain result as they did in previous evaluations. This yields to a high performance but it might happen that the JVM has to drop the code even during the same execution when one of the assertions does not hold anymore, e.g. the program might take a code path it didn’t before or a new class has been loaded into the JVM which extends a class whose code has been optimized as-if having no subclasses, etc.
So if optimized and compiled code might be rendered obsolete even within the same environment, it is even much likelier to be obsolete in the next execution. In the end, the JVM would have to check whether the old code is still appropriate which might turn out to be even costlier than simply gathering the new environment’s data and program behavior.

What are the differences in JIT between Java and .Net

I know Microsoft .NET uses the CLR as a JIT compiler while Java has the Hotspot. What Are the differences between them?

They are very different beasts. As people pointed out, the CLR compiles to machine code before it executes a piece of MSIL. This allows it in addition to the typical dead-code elimination and inlining off privates optimizations to take advantage of the particular CPU architecture of the target machine (though I'm not sure whether it does it). This also incurs a hit for each class (though the compiler is fairly fast and many platform libraries are just a thin layer over the Win32 API).
The HotSpot VM is taking a different approach. It stipulates that most of the code is executed rarely, hence it's not worth to spend time compiling it. All bytecode starts in interpreted mode. The VM keeps statistics at call-sites and tries to identify methods which are called more than a predefined number of times. Then it compiles only these methods with a fast JIT compiler (C1) and swaps the method while it is running (that's the special sauce of HS). After the C1-compiled method has been invoked some more times, the same method is compiled with slow, but sophisticated compiler and the code is swapped again on the fly.
Since HotSpot can swap methods while they are running, the VM compilers can perform some speculative optimizations that are unsafe in statically compiled code. A canonical example is static dispatch / inlining of monomorphic calls (polymorphic method with only one implementation). This is done if the VM sees that this method always resolves to the same target. What used to be complex invocation is reduced to a few CPU instructions guard, which are predicted and pipelined by modern CPUs. When the guard condition stops being true, the VM can take a different code path or even drop back to interpreting mode. Based on statistics and program workload, the generated machine code can be different at different time. Many of these optimizations rely on the information gathered during the program execution and are not possible if you compile once whan you load the class.
This is why you need to warm-up the JVM and emulate realistic workload when you benchmark algorithms (skewed data can lead to unrealistic assesment of the optimizations). Other optimizations are lock elision, adaptive spin-locking, escape analysis and stack allocation, etc.
That said, HotSpot is only one of the VMs. JRockit, Azul, IBM's J9 and the Resettable RVM, - all have different performance profiles.

Is it possible to write a decent java optimizer if information is lost in the translation to bytecode?

It occurred to me that when you write a C program, the compiler knows the source and destination platform (for lack of a better term) and can optimize to the machine it is building code for.
But in java the best the compiler can do is optimize to the bytecode, which may be great, but there's still a layer in the jvm that has to interpret the bytecode, and the farther the bytecode is away translation-wise from the final machine architecture, the more work has to be done to make it go.
It seems to me that a bytecode optimizer wouldn't be nearly as good because it has lost all the semantic information available from the original source code (which may already have been butchered by the java compiler's optimizer.)
So is it even possible to ever approach the efficiency of C with a java compiler?

Actually, a byte-code JIT compiler can exceed the performance of statically compiled languages in many instances because it can evaluate the byte code in real time and in the actual execution context. So the apps performance increases as it continues to run.

What Kevin said. Also, the bytecode optimizer (JIT) can also take advantage of runtime information to perform better optimizations. For instance, it knows what code is executing more (Hot-spots) so it doesn't spend time optimizing code that rarely executes. It can do most of the stuff that profile-guided optimization gives you (branch prediction, etc), but on-the-fly for whatever the target procesor is. This is why the JVM usually needs to "warm up" before it reaches best performance.

In theory both optimizers should behave 'identically' as it is standard practice for c/c++ compilers to perform the optimization on the generated assembly and not the source code so you've already lost any semantic information.

If you read the byte code, you may see that the compiler doesn't optimise the code very well. However the JIT can optimise the code so this really doesn't matter.
Say you compile the code on an x86 machine and new architecture comes along, lets call it x64, the same Java binary can take advantage of the new features of that architecture even though it might not have existed when the code was compiled. It means you can take old distributions of libraries and take advantage of the latest hardware specific optimisations. You cannot do this with C/C++.
Java can optimise inline calls for virtual methods. Say you have a virtual method with many different possible implementations. However, say one or two implementations are called most of the time in reality. The JIT can detect this and inline up to two method implementations but still behave correctly if you happen to call another implementation. You cannot do this with C/C++
Java 7 supports escape analysis for locked/synchronised objects, it can detect that an object is only used in a local context and drop synchronization for that object.
In the current versions of Java, it can detect if two consecutive methods lock the same object and keep the lock between them (rather than release and re-acquire the lock)
You cannot do this with C/C++ because there isn't a language level understanding of locking.

What are advantages of bytecode over native code? [closed]

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It seems like anything you can do with bytecode you can do just as easily and much faster in native code. In theory, you could even retain platform and language independence by distributing programs and libraries in bytecode then compiling to native code at installation, rather than JITing it.
So in general, when would you want to execute bytecode instead of native?

Hank Shiffman from SGI said (a long time ago, but it's till true):
There are three advantages of Java
using byte code instead of going to
the native code of the system:
Portability: Each kind of computer has its unique instruction
set. While some processors include the
instructions for their predecessors,
it's generally true that a program
that runs on one kind of computer
won't run on any other. Add in the
services provided by the operating
system, which each system describes in
its own unique way, and you have a
compatibility problem. In general, you
can't write and compile a program for
one kind of system and run it on any
other without a lot of work. Java gets
around this limitation by inserting
its virtual machine between the
application and the real environment
(computer + operating system). If an
application is compiled to Java byte
code and that byte code is interpreted
the same way in every environment then
you can write a single program which
will work on all the different
platforms where Java is supported.
(That's the theory, anyway. In
practice there are always small
incompatibilities lying in wait for
the programmer.)
Security: One of Java's virtues is its integration into the Web. Load
a web page that uses Java into your
browser and the Java code is
automatically downloaded and executed.
But what if the code destroys files,
whether through malice or sloppiness
on the programmer's part? Java
prevents downloaded applets from doing
anything destructive by disallowing
potentially dangerous operations.
Before it allows the code to run it
examines it for attempts to bypass
security. It verifies that data is
used consistently: code that
manipulates a data item as an integer
at one stage and then tries to use it
as a pointer later will be caught and
prevented from executing. (The Java
language doesn't allow pointer
arithmetic, so you can't write Java
code to do what we just described.
However, there is nothing to prevent
someone from writing destructive byte
code themselves using a hexadecimal
editor or even building a Java byte
code assembler.) It generally isn't
possible to analyze a program's
machine code before execution and
determine whether it does anything
bad. Tricks like writing
self-modifying code mean that the evil
operations may not even exist until
later. But Java byte code was designed
for this kind of validation: it
doesn't have the instructions a
malicious programmer would use to hide
their assault.
Size: In the microprocessor world RISC is generally preferable
over CISC. It's better to have a small
instruction set and use many fast
instructions to do a job than to have
many complex operations implemented as
single instructions. RISC designs
require fewer gates on the chip to
implement their instructions, allowing
for more room for pipelines and other
techniques to make each instruction
faster. In an interpreter, however,
none of this matters. If you want to
implement a single instruction for the
switch statement with a variable
length depending on the number of case
clauses, there's no reason not to do
so. In fact, a complex instruction set
is an advantage for a web-based
language: it means that the same
program will be smaller (fewer
instructions of greater complexity),
which means less time to transfer
across our speed-limited network.
So when considering byte code vs native, consider which trade-offs you want to make between portability, security, size, and execution speed. If speed is the only important factor, go native. If any of the others are more important, go with bytecode.
I'll also add that maintaining a series of OS and architecture-targeted compilations of the same code base for every release can become very tedious. It's a huge win to use the same Java bytecode on multiple platforms and have it "just work."

The performance of essentially any program will improve if it is compiled, executed with profiling, and the results fed back into the compiler for a second pass. The code paths which are actually used will be more aggressively optimized, loops unrolled to exactly the right degree, and the hot instruction paths arranged to maximize I$ hits.
All good stuff, yet it is almost never done because it is annoying to go through so many steps to build a binary.
This is the advantage of running the bytecode for a while before compiling it to native code: profiling information is automatically available. The result after Just-In-Time compilation is highly optimized native code for the specific data the program is processing.
Being able to run the bytecode also enables more aggressive native optimization than a static compiler could safely use. For example if one of the arguments to a function is noted to always be NULL, all handling for that argument can simply be omitted from the native code. There will be a brief validity check of the arguments in the function prologue, if that argument is not NULL the VM aborts back to the bytecode and starts profiling again.

Bytecode creates an extra level of indirection.
The advantages of this extra level of indirection are:
Platform independence
Can create any number of programming languages (syntax) and have them compile down to the same bytecode.
Could easily create cross language converters
x86, x64, and IA64 no longer need to be compiled as seperate binaries. Only the proper virtual machine needs to be installed.
Each OS simply needs to create a virtual machine and it will have support for the same program.
Just in time compilation allows you to update a program just by replacing a single patched source file. (Very beneficial for web pages)
Some of the disadvantages:
Performance
Easier to decompile

All good answers, but my hot-button has been hit - performance.
If the code being run spends all its time calling library/system routines - file operations, database operations, sending windows messages, then it doesn't matter very much if it's JITted, because most of the clock time is spent waiting for those lower-level operations to complete.
However, if the code contains things we usually call "algorithms", that have to be fast and don't spend much time calling functions, and if those are used often enough to be a performance problem, then JIT is very important.

I think you just answered your own question: platform independence. Platform-independent bytecode is produced and distributed to its target platform. When executed it's quickly compiled to native code either before execution begins, or simultaneously (Just In Time). The Java JVM and presumably the .NET runtimes operate on this principle.

Here: http://slashdot.org/developers/02/01/31/013247.shtml
Go see what the geeks of Slashdot have to say about it! Little dated, but very good comments!

Ideally you would have portable bytecode that compiles Just In Time to native code. I think the reason bytecode interpreters exist without JIT is due primarily to the practical fact that native code compilation adds complexity to a virtual machine. It takes time to build, debug, and maintain that additional component. Not everyone has the time or resources to make that commitment.
A secondary factor is safety. It's much easier to verify an interpreter won't crash than to guarantee the same for native code.
Third is performance. It can often take more time to generate machine code than to interpret bytecode for small pieces of code that only run once.

Portability and platform independence are probably the most notable advantages of bytecode over native code.