jm + threads   15

@tttthreads
Unroll a long twitter thread with a single tweet. I like it
unroll  threads  twitter  reading  ux  bots 
21 days ago by jm
Locking, Little's Law, and the USL
Excellent explanatory mailing list post by Martin Thompson to the mechanical-sympathy group, discussing Little's Law vs the USL:
Little's law can be used to describe a system in steady state from a queuing perspective, i.e. arrival and leaving rates are balanced. In this case it is a crude way of modelling a system with a contention percentage of 100% under Amdahl's law, in that throughput is one over latency.

However this is an inaccurate way to model a system with locks. Amdahl's law does not account for coherence costs. For example, if you wrote a microbenchmark with a single thread to measure the lock cost then it is much lower than in a multi-threaded environment where cache coherence, other OS costs such as scheduling, and lock implementations need to be considered.

Universal Scalability Law (USL) accounts for both the contention and the coherence costs.
http://www.perfdynamics.com/Manifesto/USLscalability.html

When modelling locks it is necessary to consider how contention and coherence costs vary given how they can be implemented. Consider in Java how we have biased locking, thin locks, fat locks, inflation, and revoking biases which can cause safe points that bring all threads in the JVM to a stop with a significant coherence component.
usl  scaling  scalability  performance  locking  locks  java  jvm  amdahls-law  littles-law  system-dynamics  modelling  systems  caching  threads  schedulers  contention 
29 days ago by jm
The Injector: A new Executor for Java
This honestly fits a narrow niche, but one that is gaining in popularity. If your messages take > 100μs to process, or your worker threads are consistently saturated, the standard ThreadPoolExecutor is likely perfectly adequate for your needs. If, on the other hand, you’re able to engineer your system to operate with one application thread per physical core you are probably better off looking at an approach like the LMAX Disruptor. However, if you fall in the crack in between these two scenarios, or are seeing a significant portion of time spent in futex calls and need a drop in ExecutorService to take the edge off, the injector may well be worth a look.
performance  java  executor  concurrency  disruptor  algorithms  coding  threads  threadpool  injector 
may 2015 by jm
Hack workaround to get JVM thread priorities working on Linux
As used in Cassandra ( http://grokbase.com/t/hbase/dev/13bf9kezes/about-xx-threadprioritypolicy-42 )!
if you just set the "ThreadPriorityPolicy" to something else than the legal values 0 or 1, [...] a slight logic bug in Sun's JVM code kicks in, and thus sets the policy to be as if running with root - thus you get exactly what one desire. The operating system, Linux, won't allow priorities to be heightened above "Normal" (negative nice value), and thus just ignores those requests (setting it to normal instead, nice value 0) - but it lets through the requests to set it lower (setting the nice value to some positive value).
cassandra  thread-priorities  threads  java  jvm  linux  nice  hacks 
january 2015 by jm
ExecutorService - 10 tips and tricks
Excellent advice from Tomasz Nurkiewicz' blog for anyone using java.util.concurrent.ExecutorService regularly. The whole blog is full of great posts btw
concurrency  java  jvm  threading  threads  executors  coding 
november 2014 by jm
Micro jitter, busy waiting and binding CPUs
pinning threads to CPUs to reduce jitter and latency. Lots of graphs and measurements from Peter Lawrey
pinning  threads  performance  latency  jitter  tuning 
march 2014 by jm
[JavaSpecialists 215] - StampedLock Idioms
a demo of Doug Lea's latest concurrent data structure in Java 8
doug-lea  concurrency  coding  java-8  java  threads 
december 2013 by jm
Lock-Based vs Lock-Free Concurrent Algorithms
An excellent post from Martin Thompson showing a new JSR166 concurrency primitive, StampedLock, compared against a number of alternatives in a simple microbenchmark.
The most interesting thing for me is how much the lock-free, AtomicReference.compareAndSet()-based approach blows away all the lock-based approaches -- even in the 1-reader-1-writer case. Its code is extremely simple, too: https://github.com/mjpt777/rw-concurrency/blob/master/src/LockFreeSpaceship.java
concurrency  java  threads  lock-free  locking  compare-and-set  cas  atomic  jsr166  microbenchmarks  performance 
august 2013 by jm
Java Concurrent Counters By Numbers
threadsafe counters in the JVM compared. AtomicLong, Doug Lea's LongAdder, a ThreadLocal counter, and a field-on-the-Thread-object counter int (via Darach Ennis). Nitsan's posts on concurrency are fantastic
counters  concurrency  threads  java  jvm  atomic 
june 2013 by jm
Functional Reactive Programming in the Netflix API with RxJava
Hmm, this seems nifty as a compositional building block for Java code to enable concurrency without thread-safety and sync problems.
Functional reactive programming offers efficient execution and composition by providing a collection of operators capable of filtering, selecting, transforming, combining and composing Observable's.

The Observable data type can be thought of as a "push" equivalent to Iterable which is "pull". With an Iterable, the consumer pulls values from the producer and the thread blocks until those values arrive. By contrast with the Observable type, the producer pushes values to the consumer whenever values are available. This approach is more flexible, because values can arrive synchronously or asynchronously.
concurrency  java  jvm  threads  thread-safety  coding  rx  frp  fp  functional-programming  reactive  functional  async  observable 
april 2013 by jm
Java tip: How to get CPU, system, and user time for benchmarking
a neat MXBean trick to get per-thread CPU usage in a running JVM (via Tatu Saloranta)
java  jvm  monitoring  cpu  metrics  threads 
november 2012 by jm
Thousands of Threads and Blocking I/O [PDF]
classic presentation from Paul Tyma of Mailinator regarding the java.nio (event-driven, non-threaded) vs java.io (threaded) model of server concurrency, backing up the scalability of threads on modern JVMs
java  async  io  jvm  linux  performance  scalability  threading  threads  server  nio  paul-tyma  mailinator  from delicious
july 2010 by jm
Good volcanic-ash links
European air traffic control Twitter feed and NOC site, via Boards.ie. The thread itself is a good reference, too
volcano  ash  vaac  twitter  boards.ie  threads  travel  air  holidays  from delicious
may 2010 by jm
Mindblowing Python GIL
'presentation about how the Python GIL actually works and why it's even worse than most people even imagine.' A good chunk btw could be rephrased as 'pthreads is worse than most people even imagine'. pretty awful data, though
python  gil  locking  synchronization  ouch  performance  tuning  coding  interpreters  threads  pthreads  from delicious
february 2010 by jm

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