https://classmethod.connpass.com/event/55140/ ã®çºè¡¨è³æ Goã®ä¸¦è¡å¦çã«å¿ è¦ãªå¹¾ã¤ãã®æ©è½ã¨ããããã¤ãã£ããµã³ãã«ããç´¹ä»

https://classmethod.connpass.com/event/55140/ ã®çºè¡¨è³æ Goã®ä¸¦è¡å¦çã«å¿ è¦ãªå¹¾ã¤ãã®æ©è½ã¨ããããã¤ãã£ããµã³ãã«ããç´¹ä»
Goè¨èªã®ç¹å¾´ã¨ãã¦æããããæ©è½ã®1ã¤ã«ãã並åå¦çãæ¸ãã®ãç°¡åãã¨ãããã®ãããã¾ãã ããã§ä»åã¯ãGoã«ããã並åå¦çã®æ©è½ãç´¹ä»ãã¦ãããããããç¾ä»£ã®ã³ã³ãã¥ã¼ã¿ã¼ã§ã©ã®ããã«ãã¦ä¸¦åå¦çãå®ç¾ããã¦ããã®ããã¨ãããã¾ãã è¤æ°ã®ä»äºãåæã«è¡ãã¨ã¯ï¼ è¤æ°ã®ä»äºãè¡ããã¨ã表ãè¨èã«ã¯ä¸¦è¡ã¨ä¸¦åã®2ã¤ãããã¾ããããããã«ã¯æ¬¡ã®ãããªåºå¥ãããã¾ãã 並è¡å¦çï¼Concurrentï¼ ä¸¦è¡ï¼Concurrentï¼: CPUæ°ã»ã³ã¢æ°ã®éçãè¶ ãã¦è¤æ°ã®ä»äºãåæã«è¡ãã㨠ã»ãã®å°ãåã¾ã§ãã³ã³ãã¥ã¼ã¿ã¼ã«æè¼ããã¦ããCPUã¯ã³ã¢æ°ã1ã¤ãããªããã®ãæ®éã§ããã ãã®ãããªãä»ã§ã¯ããçµ¶æ» å±æ§ç¨®ã«ãªãã¤ã¤ããã·ã³ã°ã«ã³ã¢ã®ã³ã³ãã¥ã¼ã¿ã¼ã§ãã£ã¦ããã¤ã³ã¿ã¼ããããè¦ãªããWordã¨Excelãç«ã¡ä¸ãã¦ã¬ãã¼ããæ¸ãã¾ãã ãã®å ´åã«å¤§äºã«ãªãã®ã並è¡ï¼Concurr
mrubyã®VMã®ãã«ãã¹ã¬ãã対å¿ãgithubã«ã¦è°è«ããã¦ãã¾ãã multi-thread support on the RiteVM #1657 èªåãthread-safeãªVMã欲ãããªãã¨æã£ã¦ãã¾ããSTM32F4Discoveryã«FreeRTOSè¼ãã¦ä½¿ã£ã¦ã¿ããã 並è¡ã»ä¸¦åå¦çã®æ¦å½æ代? ãã¦ããã«ãã³ã¢ãæ®éã«ãªã£ãããWebã¢ããªã®C10Kåé¡ãããã®ã§ä¸¦è¡ã»ä¸¦åå¦çã¯æ¨ä»ã®ãããã¯ã§ãï¼å¤åï¼ã ãã ãã«ãã¹ã¬ããããã°ã©ãã³ã°ã¯é£ãããï¼ã¨ããã¯æããè¨ããã¦ãããã¨ã§ãã ã§ãããã¡ãã並è¡ã»ä¸¦åå¦çãæ¸ããããåºæ¥ãªãã®ããï¼ã¨ãããã¨ã§Erlang,go,Scala(Actor),EventMachine,Thread pool ,node.js,deferred,future,java.util.concurrentè²ã åºã¦ãã¾ãã ï¼è¨èªã¨ã©ã¤
ä¸¦è¡ (Concurrent) å¦çãå®è£ ããæ¹æ³ã¨ãã¦ã¹ã¬ããã¯é常ã«å¼·åãªãã¼ã«ã§ãã ã¹ã¬ããã使ãã°åæã«1ã¤ã®å¦çããè¡ããªãæ¢åã®ããã°ã©ã ã«å¤§ããªä¿®æ£ãå ãããã¨ãªãã 並è¡å¦çãå®è£ ãããã¨ãå¯è½ã§ãã ã¾ãã¤ãã³ãã¨ã³ã¼ã«ããã¯ãè¤éã«çµã¿åãããéåæçãªããã°ã©ã ã«æ¯ã¹ã¦ã åæçãªããã°ã©ã (ä¾ãã°ãã¡ã¤ã«ã®èªã¿è¾¼ã¿ã«ã³ã¼ã«ããã¯ãåºã¦ãããããªãæ®éã®ããã°ã©ã )㯠ããã°ã©ã ã®æµããèªç¶ã«æ¸ããã¨ãã§ãã å¯èªæ§ã»ä¿å®æ§ã»ãã¹ãããããã°ã®ããããã®é¢ã§é¥ãã«åªãã¦ãã¾ãã ã¹ã¬ããã使ãã¨ããã°ã©ã ãããã»ã©è¤éã»é£èªåã«ããã«ä¸¦è¡å¦çãå®è£ ã§ãã¾ãã ä¸æ¹ã§ã¹ã¬ããã使ã£ã並è¡å¦çã«ã¯æ¬ ç¹ãããã¾ãã æ¬ ç¹ã®1ã¤ã¯ãã¹ã¬ããã¢ãã«ã§ã¯1ã¤ã®å¦çã«å¯¾ãã¦1ã¤ã®ã¹ã¬ãããç¨æããã®ã§ã ã·ã¹ãã ã®ã¹ã¬ããæ°ã®ä¸éã§åæã«è¡ããå¦çã®æ°ã決ã¾ã£ã¦ãã¾ãç¹ã§ãã
Advanced Go Concurrency Patterns Sameer Ajmani Google Video This talk was presented at Google I/O in May 2013. Watch the talk on YouTube 2 Get ready 3 Go supports concurrency In the language and runtime, not a library. This changes how you structure your programs. 4 Goroutines and Channels Goroutines are independently executing functions in the same address space. go f() go g(1, 2) Channels are ty
GHCã¯ã並è¡ããã°ã©ãã³ã°ããã³ä¸¦åããã°ã©ãã³ã°ã«å¯¾å¿ããããã®ãHaskellã¸ã®å¤§è¦æ¨¡ãªæ¡å¼µãããã¤ãå®è£ ãã¦ãããã¾ãç¨èªãã¯ã£ããããã¦ãããã 並åæ§(parallelism)ã¨ã¯ãå®è¡æ§è½ã®åä¸ãç®çã¨ãã¦ãHaskellããã°ã©ã ãè¤æ°ã®ããã»ããµä¸ã§èµ°ããããã¨ã§ãããçæ³çã«ã¯ãããã¯ä¸å¯è¦ã«ãæå³ãå¤æ´ãããã¨ãªãçºãããã¹ãã§ããã 並è¡æ§(concurrency)ã¨ã¯ãããããIOãè¡ãè¤æ°ã®ã¹ã¬ããã使ã£ã¦ããã°ã©ã ãå®è£ ãããã¨ã§ããã確ãã«ä¸¦è¡Haskellããã°ã©ã ã¯ä¸¦åãªæ©æ¢°ä¸ã§èµ°ããããã¨ãã§ãããã並è¡æ§ã使ãã®ã¯ã第ä¸ç®çã¨ãã¦å®è¡æ§è½ãå¾ãããã§ã¯ãªãããããå½è©²ããã°ã©ã ãæ¸ãããã®æãåç´ã§æãç´æ¥çãªæ¹æ³ã ããã§ãããã¹ã¬ããã¯å ¥åºåãè¡ãã®ã§ãããã°ã©ã ã®æå³ã¯å¿ ç¶çã«é決å®çãªãã®ã«ãªãã
1 Haskell kazu@iij.ad.jp 2 (parallel) (concurrent) 3 4 5 6 7 Haskell 8 OS 9 Haskell 10 Haskell 11 Haskell Haskell 12 Haskell 13 Haskell 14 ) N 15 map map Google MapReduce 16 Java puzzles.parallel().map(e -> solve(e)); // Scala puzzles.par.map(solve); // Haskell map solve puzzles âusingâ parList rseq ) 17 % ghc -O2 -threaded foo.hs % ./foo +RTS -N2 18 Repa Accelerate GPU NVIDIA GPU CUDA 19 h x = do
Concurrent and Distributed Applications with Akka, Java and Scala The document discusses concurrency and distribution in applications using Akka, Java and Scala. It covers key concepts like actors, messages and message passing in Akka. It describes how actors encapsulate state and behavior, communicate asynchronously via message passing and provide built-in concurrency without shared state or lock
Akka Streams (0.7) talk for the Tokyo Scala User Group, hosted by Dwango. Akka streams are an reactive streams implementation which allows for asynchronous back-pressured processing of data in complext pipelines. This talk aims to highlight the details about how reactive streams work as well as some of the ideas behind akka streams.Read less
Yesod is a Haskell web framework for productive development of type-safe, RESTful, high performance web applications. As you may know, Michael and I released a set of packages for WAI 2.0 including Warp 2.x and fast-logger 2.x. They are much faster than their old versions. I will explain how I re-designed fast-logger in this article and how I improved the performance of Warp in the next one. The c
ï¼ä»¥ä¸ã¯go 1.2.xæç¹ã§ã®è©±ã§ããå°æ¥çã«ä»æ§ãããããã©ããã¯ãããã¾ããï¼ ãããèªãã§ãã¦ãããããã®æ°ã«ãã¦ãªã人å¤ããã ãããªã¼ã¨æã£ã¦ãæ¸ãã¦ã¿ã¾ããå ã®ãã¹ãã¯deferã®æåã«ã¤ãã¦èªã£ã¦ããããã«è¦åããããããã©ããããã¯è¦ã¯è¤æ°ã¹ã¬ããã§å®è¡ãããã³ã¼ãã«ã¤ãã¦ãããã°ã©ã çµäºæã«åæã¨ãåããããªããã¨ãã話ã ã¨æã£ãã®ã§ããã®ãã¹ãã®deferãæ£ããåããã«ã¯â¦ã¨ããã¨ããããã©ãããå½¢ã§goroutineå士ã§åæãåãæ¹æ³ãããã®ããä¸ä¾ãæ¸ãåºãã¦ããã¾ãã TL;DR; goã§ãããgoroutineãæ°è»½ã«ãããããã¨è¨ã£ã¦ãè¤æ°ã¹ã¬ããã§å¦çãè¡ããã¦ããã®ã§åæã¯ããã³ã¨ãããªãã¨ãã¡ã§ããã deferã®åºæ¬ goã§ã¯LLã®ããªã§ã³ã¼ããæ¸ããã®ã売ãã®ä¸ã¤ã§ãããã¡ã¢ãªç®¡çã¯ãã¦ããããã®ã®ãæ§ã ãªãªã½ã¼ã¹è§£æ¾ãå ¨ã¦èªåã¨ããããã§ã¯ãã
Android ã§éåæå¦çã£ã¦ããã¨ãçã£å ã« AsyncTask ãåºã¦ãããã§ããããªãã¹ããªã Java æ¨æºã®ãã«ãã¹ã¬ããAPI ã§ãã ExecutorService ã使ã£ãæ¹ãè¯ãã¨æã£ã¦ã¾ãã (2007å¹´ã®è¨äºã ãã©) Javaæè¡æåç· - ãJava SE 6å®å ¨æ»ç¥ã第49å Concurrency Utilitiesã®å¤æ´ç¹ ãã®1ï¼ITpro Android ã§åã㦠Java ãæ¸ããã®ã§ç´°ããä»æ§ãããåããããåå¼·ãã¦ãåãã確èªãã¦ã¿ã¾ããã 1. 1ã¤ã®ã¯ã¼ã«ã¹ã¬ããã«å®è¡ããã newSingleThreadExecutor ã§ã¯ã¼ã«ã¹ã¬ãããä¸ã¤æ㤠Executor ãçæãã¦ã2ã¤ã®ã¿ã¹ã¯(=éåæã§å®è¡ãããå¦ç)ãé ã«å®è¡ã public void singleThreadExecutorBasicTest() throws Excep
åå Java 7 ã使ãç°å¢è¨å®ãè¡ã£ãã®ã§ãã¤ãã§ã«ã¡ãã£ã¨ Java 7 ãããã£ã¦ã¿ã¾ã*1ããä»åè¦ã¦ããã®ã¯ java.util.concurrent ããã±ã¼ã¸ã«è¿½å ããã Fork/Join ãã¬ã¼ã ã¯ã¼ã¯ã§ãããFork/Join ã¯å¤§éã®è¨ç®ãå°ããé¨åã«åãã¦ãã«ãã¹ã¬ããã§è¨ç®ããææ³ã§ãã ã§ããã®è¨äºã§ã¯æ´æ°ã®ãªã¹ã (List<Integer>) ãåãåã£ã¦ãã®è¦ç´ å ¨ã¦ã®åãè¨ç®ããã³ã¼ããè¦ã¦ããã¾ãã åè URL Java ãã¥ã¼ããªã¢ã« ãFork/Joinã Javadoc ForkJoinPool ForkJoinTask RecursiveTask GPars Reference Documentation ã3.6. Fork-Joinã java.util.concurrent ããã±ã¼ã¸ ï¼ Java 7 Java 7 㧠Fork/Jo
ãã¼ã¿æ§é ã¨ã¢ã«ã´ãªãºã åå ¥é ã¯ããã« ã»ä¸¦{è¡|å} & {Lock|Wait}Free ã»ABA & ABA' ã»volatile ï¼ ã¡ã¢ãªããªã¢ ã»ããªããã£ã ã»CAS ã»MCAS ã»STM ã»ã¡ã¢ãªç®¡ç:free & GC ã»Toots List & Skiplist [åæ¹åList] ã»ãªã¹ã ã»ç´°ç²åº¦ãªã¹ã ã»Lazyãªã¹ã ã»Lock-Freeãªã¹ã ã»Lock-Freeãªã¹ã2 [SkipList] ã»ã¹ããããªã¹ã ã»Lazyã¹ããããªã¹ã ã»Lock-freeã¹ããããªã¹ã [åæ¹åList] Queue & PriorityQueue [UnBounded Queue] ã»Queue ã»CAS based Lock-Free Queue ã»LL/SC based Lock-Free Queue [Unbounded Priority Queue] ã»Heap
Red Hat (JBoss) - EAP Core Team Former contractor for Apple Inc Author - Netty in Action Apache Software Foundation Member Netty  / Vert.x Core-Developer and all things NIO Java and Scala Twitter: @normanmaurer Github: https://github.com/normanmaurer As always, only optimize if you really need! 1000 concurrent connections != high-scale If you only need to handle a few hundred connections use Block
ã©ã³ãã³ã°
ãç¥ãã
ã©ã³ãã³ã°
ãªãªã¼ã¹ãé害æ å ±ãªã©ã®ãµã¼ãã¹ã®ãç¥ãã
ææ°ã®äººæ°ã¨ã³ããªã¼ã®é ä¿¡
å¦çãå®è¡ä¸ã§ã
j次ã®ããã¯ãã¼ã¯
kåã®ããã¯ãã¼ã¯
lãã¨ã§èªã
eã³ã¡ã³ãä¸è¦§ãéã
oãã¼ã¸ãéã
{{#tags}}- {{label}}
{{/tags}}