fastest (low latency) method for Inter Process Communication between Java and C/C++

I have a Java app, connecting through TCP socket to a "server" developed in C/C++.

both app & server are running on the same machine, a Solaris box (but we're considering migrating to Linux eventually). type of data exchanged is simple messages (login, login ACK, then client asks for something, server replies). each message is around 300 bytes long.

Currently we're using Sockets, and all is OK, however I'm looking for a faster way to exchange data (lower latency), using IPC methods.

I've been researching the net and came up with references to the following technologies:

• shared memory
• pipes
• queues
• as well as what's referred as DMA (Direct Memory Access)

but I couldn't find proper analysis of their respective performances, neither how to implement them in both JAVA and C/C++ (so that they can talk to each other), except maybe pipes that I could imagine how to do.

can anyone comment about performances & feasibility of each method in this context ? any pointer / link to useful implementation information ?

---

EDIT / UPDATE

following the comment & answers I got here, I found info about Unix Domain Sockets, which seem to be built just over pipes, and would save me the whole TCP stack. it's platform specific, so I plan on testing it with JNI or either juds or junixsocket.

next possible steps would be direct implementation of pipes, then shared memory, although I've been warned of the extra level of complexity...

---

thanks for your help

Just tested latency from Java on my Corei5 2.8GHz, only single byte send/received, 2 Java processes just spawned, without assigning specific CPU cores with taskset:

TCP         - 25 microseconds
Named pipes - 15 microseconds

Now explicitly specifying core masks, like taskset 1 java Srv or taskset 2 java Cli:

TCP, same cores:                      30 microseconds
TCP, explicit different cores:        22 microseconds
Named pipes, same core:               4-5 microseconds !!!!
Named pipes, taskset different cores: 7-8 microseconds !!!!

so

TCP overhead is visible
scheduling overhead (or core caches?) is also the culprit

At the same time Thread.sleep(0) (which as strace shows causes a single sched_yield() Linux kernel call to be executed) takes 0.3 microsecond - so named pipes scheduled to single core still have much overhead

Some shared memory measurement: September 14, 2009 – Solace Systems announced today that its Unified Messaging Platform API can achieve an average latency of less than 700 nanoseconds using a shared memory transport. http://solacesystems.com/news/fastest-ipc-messaging/

P.S. - tried shared memory next day in the form of memory mapped files, if busy waiting is acceptable, we can reduce latency to 0.3 microsecond for passing a single byte with code like this:

MappedByteBuffer mem =
  new RandomAccessFile("/tmp/mapped.txt", "rw").getChannel()
  .map(FileChannel.MapMode.READ_WRITE, 0, 1);

while(true){
  while(mem.get(0)!=5) Thread.sleep(0); // waiting for client request
  mem.put(0, (byte)10); // sending the reply
}

Notes: Thread.sleep(0) is needed so 2 processes can see each other's changes (I don't know of another way yet). If 2 processes forced to same core with taskset, the latency becomes 1.5 microseconds - that's a context switch delay

P.P.S - and 0.3 microsecond is a good number! The following code takes exactly 0.1 microsecond, while doing a primitive string concatenation only:

int j=123456789;
String ret = "my-record-key-" + j  + "-in-db";

P.P.P.S - hope this is not too much off-topic, but finally I tried replacing Thread.sleep(0) with incrementing a static volatile int variable (JVM happens to flush CPU caches when doing so) and obtained - record! - 72 nanoseconds latency java-to-java process communication!

When forced to same CPU Core, however, volatile-incrementing JVMs never yield control to each other, thus producing exactly 10 millisecond latency - Linux time quantum seems to be 5ms... So this should be used only if there is a spare core - otherwise sleep(0) is safer.

The question was asked some time ago, but you might be interested in https://github.com/peter-lawrey/Java-Chronicle which supports typical latencies of 200 ns and throughputs of 20 M messages/second. It uses memory mapped files shared between processes (it also persists the data which makes it fastest way to persist data)

DMA is a method by which hardware devices can access physical RAM without interrupting the CPU. E.g. a common example is a harddisk controller which can copy bytes straight from disk to RAM. As such it's not applicable to IPC.

Shared memory and pipes are both supported directly by modern OSes. As such, they're quite fast. Queues are typically abstractions, e.g. implemented on top of sockets, pipes and/or shared memory. This may look like a slower mechanism, but the alternative is that you create such an abstraction.

Here's a project containing performance tests for various IPC transports:

http://github.com/rigtorp/ipc-bench

A late arrival, but wanted to point out an open source project dedicated to measuring ping latency using Java NIO.

Further explored/explained in this blog post. The results are(RTT in nanos):

Implementation, Min,   50%,   90%,   99%,   99.9%, 99.99%,Max
IPC busy-spin,  89,    127,   168,   3326,  6501,  11555, 25131
UDP busy-spin,  4597,  5224,  5391,  5958,  8466,  10918, 18396
TCP busy-spin,  6244,  6784,  7475,  8697,  11070, 16791, 27265
TCP select-now, 8858,  9617,  9845,  12173, 13845, 19417, 26171
TCP block,      10696, 13103, 13299, 14428, 15629, 20373, 32149
TCP select,     13425, 15426, 15743, 18035, 20719, 24793, 37877

This is along the lines of the accepted answer. System.nanotime() error (estimated by measuring nothing) is measured at around 40 nanos so for the IPC the actual result might be lower. Enjoy.

If you ever consider using native access (since both your application and the "server" are on the same machine), consider JNA, it has less boilerplate code for you to deal with.

I don't know much about native inter-process communication, but I would guess that you need to communicate using native code, which you can access using JNI mechanisms. So, from Java you would call a native function that talks to the other process.

In my former company we used to work with this project, http://remotetea.sourceforge.net/, very easy to understand and integrate.

Have you considered keeping the sockets open, so the connections can be reused?

Oracle bug report on JNI performance: http://bugs.java.com/bugdatabase/view_bug.do?bug_id=4096069

JNI is a slow interface and so Java TCP sockets are the fastest method for notification between applications, however that doesn't mean you have to send the payload over a socket. Use LDMA to transfer the payload, but as previous questions have pointed out, Java support for memory mapping is not ideal and you so will want to implement a JNI library to run mmap.