Skip to main content

Posts

Why I don't like System.gc()

I wrote this for internal-to-my-company consumption, but I couldn't find a reasonable place to put it. And then I remembered I had a blog. The question to me was whether is ever made sense to do a System.gc() , and, more specifically, whether it made sense to do System.gc() followed by System.runFinalization() . I can't claim it is always wrong. It suffers from what some people call the Politician's syllogism : Something must be done, this is something, therefore we must do it. There's no control over GC other than a big red button labeled "System.gc()", so this is always the something that must be done. In practice, the biggest problem with System.gc() is that what it does is rather unpredictable. In fact, there's no guarantee that it will do anything. In fact, Hotspot has a -XX:DisableExplicitGC flag to stop it from doing anything. So, it can sometimes solve an immediate problem in a system-dependent way, but you are introducing a signi...
Recent posts

Lightweight Asynchronous Sampling Profiler

I finally got off of my lazy elbows and wrote a proof-of-concept sampling profiler for public consumption based on the Hotspot JVM's AsyncGetCallTrace interface. The benefit of using this interface to write a profiler is that it can gather stack traces asynchronously. This avoids the inaccuracies of only being able to profile code at safe points, and the overhead of having to stop the JVM to gather a stack trace. The result is a more accurate profiler that avoids the 10-20% overhead of something like hprof. For a more thorough explanation as to why this is interesting, see my 2010 writeup on the subject . Another feature of the profiler is that it will tell you what stack traces are being executed, rather than, like many sampling Java profilers, what stack traces could be executed. That is, with traditional profilers, if you stop the VM and ask it for stack traces, it will tell you all of the stack traces from all of the threads that are not currently blocked. This prof...

Transactional Hardware on x86

While I'm posting anyway, I might as well mention the big concurrency news of the day: the new transactional memory specification from Intel. Transactional memory sounds a lot like what it is. Your code begins a transaction and continues to execute it until it ends, performing some memory writes along the way. If there are no conflicting transactions (i.e., transactions that write to the same memory that your code wrote) executing at the same time as yours, your transaction will end normally and commit your memory writes. If there are conflicting transactions, your transaction will abort and roll back your writes. Transactional memory on x86 will come in two flavors: Hardware Lock Elision (HLE), which consists of XACQUIRE and XRELEASE instruction prefixes. These can optimistically turn lock regions into transactions. What's the advantage? Well, transactions can execute concurrently, as long as they aren't writing to the same memory. Locks are serialized: only one ...

Update to the Allocation Instrumenter

A couple of years ago, I open-sourced a tool that lets you instrument all of the allocations in your Java program . Some quick updates today: It now supports JDK7. You can now optionally use it to instrument constructors of a particular type, instead of allocations. So, if you wanted to find out where your Thread s were being instantiated, you could instrument them with a callback that invokes Thread.dumpStack(). I know that most of the readers of this blog are more interested in concurrency, and that it has been a very, very long time since I posted. The spirit is willing, but the flesh is insanely busy... I have it in mind to do a post that discusses a bunch of strategies for doing efficient non-blocking concurrency in C++, because the attempts are very amusing, but I haven't had the chance to sit down and do it.

Scala / Java Shootout

I should probably comment on this paper from my colleague Robert Hundt , where he writes the same benchmark in Java, Scala, Go, Python and C++ ( TL;DR here ). Short version: Initially, C++ was faster than Scala, and Scala was faster than Java. I volunteered to make some improvements, which ended up with the C++ and Java implementations being about the same speed. Some C++ hackers then went and improved the C++ benchmark by another ~6x, and I didn't think I should go down that road. Imagine my surprise when I got this email from a friend of mine this morning: Date: Fri, 3 Jun 2011 03:20:48 -0700 Subject: Java Tunings To: Jeremy "Note that Jeremy deliberately refused to optimize the code further, many of the C++ optimizations would apply to the Java version as well." Slacker. Gee, thanks for making me look good, Robert. (Actually, I had approved that language, but I didn't realize anyone would actually read the paper. :) ) Anyway, I was not just being obdurate here;...

Java Puzzlers@Google I/O

Josh Bloch and I gave one of his Java Puzzlers talk at Google I/O this year. If you hate Java, you can waste a perfectly good hour listening to us make unfunny jokes at its expense.

Cliff Click in "A JVM Does What?"

Cliff Click gave a very good talk at Google last week. For your viewing enjoyment: The slides are available here . (For those who watched it: The inventors of bytecode were in the audience. I think he was just used to making that joke elsewhere.)