Download to read offline
Uploaded byArtur Gajowy
Gpars - the coolest bits
The document discusses GPars, a Groovy library designed for high-level parallelism abstractions, which can be utilized in Java and is open source. It covers various parallelism approaches, including parallel collections, asynchronous functions, and message passing through agents, emphasizing the importance of stateless and side-effect free iteration bodies. The content also critiques the use of actors, arguing for alternatives and presenting demonstrations of GPars functionalities.
More Related Content
Similar to Gpars - the coolest bits
Gpars - the coolest bits
- 1.
- 2.
- 3. GPars Groovy ParallelSystems - multiple high-level parallelism abstractions - Java-usable - GAE-usable - part of Groovy SDK - open source (Apache 2 License) - Grooovy documentation
- 4. GPars Groovy ParallelSystems Team: Václav Pech, Dierk König, Russel Winder, Alex Tkachman, Paul King, Jon Kerridge, Rafał Sławik and others
- 5. One Ring torule them all... Parallelism approach in GPars (originally?) found in implemented using Parallel collections Scala, Java jsr-166y / JDK5 executors jsr-166y Fork/Join (sugar) Java jsr-166y Actors Erlang, Scala java.util.concurrent Software Transactional Memory Clojure, Scala Multiverse Agents Clojure java.util.concurrent CSP CSP :) Dataflow* or JCSP Dataflow and extensions: Linda, Verilog, Agilent Vee, Pipelines, Kanbanflow Scala, Unreal Engine jsr-166y / JDK5 executors (?) Composable asynchronous functions ? jsr-166y / JDK5 executors
- 7. Our focus Parallelismapproach in GPars (originally?) found in implemented using Parallel collections Scala, Java jsr-166y / JDK5 executors jsr-166y Fork/Join (sugar) Java jsr-166y Actors Erlang, Scala java.util.concurrent Software Transactional Memory Clojure, Scala Multiverse Agents Clojure java.util.concurrent CSP CSP :) Dataflow* or JCSP Dataflow and extensions: Linda, Verilog, Agilent Vee, jsr-166y / JDK5 executors Pipelines, Kanbanflow Scala, Unreal Engine (?) Composable asynchronous functions ? jsr-166y / JDK5 executors
- 8. Demo time! EnablingGPars GDSL in Intellij IDEA
- 9. Demo time! Parallelcollections - withPool / enhancer - makeConcurrent / makeSequential / asParallel - GParsPool + ParallelEnhancer / GParsExecutorsPool + GParsExecutorsPoolEnhancer - Map-Reduce (Fork / Join pool only)
- 10. Things to consider/ a warning... In this approach, your iteration body must be: - stateless - side-effect free - constrained to the current element Else - welcome to concurrency hell...
- 11. Demo time! Agents - updating immutable / mutable - syntax equivalents for .send - copy method - parallel behaviour - error handling - parallel groups, daemon threads shutting down
- 12. Agents - whatelse is there - listeners - validators validation gotchas - non-closure sends - prefer composition over inheritance - sendAndAwait
- 13. Agents - Q A Questions? - what if I want to check a condition before updating state? - how do I 'lock' the state?
- 14. Demo time! ComposableAsynchronous Functions - @AsyncFun / asyncFun() - async funs return DataflowVariable-s - blocking @AsyncFun-s for convenience - rest of the docs: instantiation variants, pool configuration
- 15. Bonus: on parallelism flavours
- 16. Choosing an approach Task parallelism Independent Async closures, Futures, whatever... Dependent Random / Unknown Dataflow Functional / Linear Composable asynchronous functions, Dataflow tasks, CSP Hierarchical / Recursive Fork / Join Shared state Agents, STM
- 17. Choosing an approach Data parallelism Geometrical / Linear Parallel collections Hierarchical / Recursive Fork / Join Streamed (regular) Pipeline DSL, Dataflow, CSP Event-driven (irregular) Actors
- 18. From GPARS UserGuide
- 19. TL;DR Parallel collections Async functions Dataflow Agents Message passing - CSP - Dataflow - Actors
- 20. Also: Bashing actorsa little :) Actors are overrated Dierk König
- 21. Also: Bashing actorsa little :) Why there were no Actors in Clojure* ● complex ● no efficient sharing even for immutable structures ● reduce flexibility ● do not really distribute well from single to many machines * a purposefully exaggerating summary by me
- 22. Slides since Morpheusbased on ● Václav Pech - GPars How To Guide ● Paul King - Concurrency with GPars ● GPars User Guide - Applicability of concepts ● GPars docs - Concepts compared ● Dierk König - Concurrent programming for you and me ● my personal biases :)
- 23. Recap - GParsis quite a lib :) - Be sure to try Dataflows - Actors are overrated ;)
- 24.
- 25.