![]() ![]() Enough effort invested it is possible to match any of the other results of course. Threads - somewhat naive thread based implementation of the Pi computation.See bottom of this post for the benchmark source. I never use more threads as there are "real" cores. Intel dual socket six core (12 cores + Hyperthreading turned off).Each socket has 8 cores + 8 Hardware Threads (so overall 16 cores + 16 HW Threads) sending messages/scheduling Runnables to a thread pool, CAS, Locks, volatile r/w. overhead created by the concurrency control mechanics (e.g.cost of accessing shared data when the result of each job is added to one single result value.However if we compute PI by creating 1 million jobs, each computing a 0.100-loop slice of PI, we get an impression of: With this setup all solutions roughly would perform the same as there is no significant concurrent access and scheduling overhead. For maximum performance one would create one large job for each Core of the CPU used. Therefore N jobs are created, and the result of each job must be added to finally get an approximation of PI. The benchmark approximates the value of PI concurrently. Update: Jason Koch implemented a custom executor performing significantly better than the stock JDK executors. While I am writing this, I realize each of these patterns has its set of best-fit problem domains, so my initial intention using a single benchmark to compare performance of different concurrency models might be somewhat off :-). There is no silver bullet for concurrent programming, one still has to plan carefully and needs to know what's going on. Processing speed of interdependent consumers without growing queues It avoids high allocation rates and reduces the VM architectures better resulting in high throughput and superior This model seems to fit existing CPU, memory and Passing/copying thread-local data to some queue or process, the Disruptor keeps data in place andĪssures only one thread (consumer or producer) is owner of a data item While the CSP/Actor-Model realizes inter-thread communication by ![]() Actually these are the primitives (+CAS) used to build higher level concurrent models like those described above. Its Java's default to model concurrent execution. Sequencing is used to manage queue access and processing order. The disruptor is a bounded queue (implemented by a ring buffer) where producers add to the head of the queue (if slots are available, else the producer is blocked).Ĭonsumers access the queue at different points, so each consumer has its own read position (cursor) inside the queue. Therefore a simple benchmark of the most popular "alternative" concurrency models is done: Actors, CSP and Disruptor. So I am looking for alternative models to express concurrency. It can be a nightmare to spot them from production logs of large applications. Even if JMM is known, incorrect programming isn't obvious and will fail rarely. The subtleties of the Java Memory Model are not well known to most Java programmers.A programmer needs global awareness of an applications control flow and data access patterns in order to change the software without introducing errors. As a software project grows, it gets hard to safely modify the application.It is common they appear under special conditions (load, hardware) in production. Errors caused by invalid synchronization are timing dependent and hard to reproduce.Bad scaling due to "over-synchronization" or contention on common resources.It is well known this model suffers of a number of problems: In order to make use of modern multi core/socket hardware, Java offers threads and locks for concurrent programming. ![]()
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