Sam Newman Building Distributed Resilient Systems
Forthcoming book focusing on making both teams and software more resilient Distributed systems come in many shapes and sizes, and are increasingly a major part of how we build and deliver software. But distributed systems create challenges. On the face of it, they appear to offer the ability to create more stable software. No longer should a single machine dying take our system off line, right? Un
ABCI上ã§pytorch distributed data parallelã«ã‚ˆã‚‹ãƒžãƒ«ãƒãƒŽãƒ¼ãƒ‰å¦ç¿’ - Qiita
ãªã‚“ã®è¨˜äº‹? pytorchã®DistributedDataParallelã«ã¤ã„ã¦ã®æ—¥æœ¬èªžè¨˜äº‹ãŒã‚ã¾ã‚Šã«ã‚‚ãªã‹ã£ãŸãŸã‚ï¼Œç´ äººãŒã¾ã¨ã‚ã¾ã—ãŸï¼Ž 並列処ç†ãŒã‚ã‹ã‚‰ãªã„人ã«ã‚ˆã‚‹ï¼Œã‚ã‹ã‚‰ãªã„人ã®ãŸã‚ã®ï¼Œã¨ã‚Šã‚ãˆãšä½¿ãˆã‚Œã°ã„ã„ã‚„çš„ãªDDPã®è§£èª¬ã§ã™ï¼Ž 基本的ã«ABCIã§ã®å®Ÿè¡Œã‚’å‰æã«æ›¸ã‹ã‚Œã¦ã„ã¾ã™ãŒï¼Œãれ以外ã®ç’°å¢ƒã®äººãŸã¡ã«ã‚‚å‚考ã«ãªã‚Œã°å¹¸ã„ã§ã™ï¼Ž ã¯ã˜ã‚ã« ãŠãªã˜ã¿ã®æ©Ÿæ¢°å¦ç¿’フレームワークã§ã‚ã‚‹pytorch．気軽ã«DataParallelã§ä¸¦åˆ—処ç†ã®å¦ç¿’ã‚‚ã§ãã¾ã™ï¼Ž ã§ã™ãŒfacebookãªã©ã®ä¸€æµã®æ©Ÿæ¢°å¦ç¿’エンジニアãŸã¡ã¯DistributedDataParallelãªã‚‹ã‚‚ã®ã‚’使ã£ãŸå®Ÿè£…ãŒã¡ã‚‰ã»ã‚‰ã¿ã‚‰ã‚Œã¾ã™ï¼Ž ãã“ã§pytorchã®è§£èª¬è¨˜äº‹ã‚’èªã‚€ã‚ã‘ã§ã™ãŒï¼Œã“ã‚ŒãŒã³ã£ãã‚Šã™ã‚‹ã»ã©ã‚ã‹ã‚‰ãªã„． ã¨ã„ã†ã‚ã‘ã§ï¼ŒABCI上ã§ã®DistributedDataParallel(以下DDP)ã®ä½¿ã„方を自
Writing Distributed Applications with PyTorch — PyTorch Tutorials 2.6.0+cu124 documentation
Learn Get Started Run PyTorch locally or get started quickly with one of the supported cloud platforms Tutorials Whats new in PyTorch tutorials Learn the Basics Familiarize yourself with PyTorch concepts and modules PyTorch Recipes Bite-size, ready-to-deploy PyTorch code examples Intro to PyTorch - YouTube Series Master PyTorch basics with our engaging YouTube tutorial series
The OpenTracing project
# Start Jaeger locally $ docker run -d -p 6831:6831/udp -p 16686:16686 jaegertracing/all-in-one:latest $ export DOCKER_IP=`docker-machine ip $(docker-machine active)` $ cd $GOPATH/src # Grab a simple, self-contained OpenTracing example $ go get github.com/opentracing-contrib/examples/go $ cd github.com/opentracing-contrib/examples/go $ go run ./trivial.go $DOCKER_IP # Visualize the tracing instrum
Distributed Systems 3rd edition (2017) | DISTRIBUTED-SYSTEMS.NET
This page refers to the 3rd edition of Distributed Systems For this third edition of “Distributed Systems,†the material has been thoroughly revised and extended, integrating principles and paradigms into nine chapters: Introduction Architectures Processes Communication Naming Coordination Replication Fault tolerance Security A separation has been made between basic material and more specific subj
Scheduling on large clusters - Google's Borg and Omega, YARN, Mesos
2. Scheduling on Large Clusters â— Goals o High Utilization o Honor User Defined constraints o Maintain High Efficiency â— Issues o Un-predictable load o Varying types of load o Increasing load and cluster size 3. Types of Schedulers â— Monolithic o Single Resource Manager and Scheduler o Google Borg â— Two Level o Single Resource Management and multiple schedulers o Mesos, Hadoop-on-Demand (HOD proje
Paxos
2. ⾃自⼰己紹介 lï¬â€¯ ä¹…ä¿â½¥ç”°å±•â¾è¡Œï¨ˆ(@nobu_k) lï¬â€¯ 製å“開発部 lï¬â€¯ Sedue/Bazil lï¬â€¯ (Jubatus) lï¬â€¯ ブル lï¬â€¯ 最近勉強ã—ã¦ã‚‹ã‚‚ã® lï¬â€¯ 開発⼿手法：è¦ä»¶å®šç¾©ãƒ»ç®¡ç†ï§¤ lï¬â€¯ 本 lï¬â€¯ Transactional Information Systems(@ノーãƒãƒ©ã‚¹) ‒  ç´„1年年ã§å¿µï¦£é¡˜ã®ãƒªã‚«ãƒãƒªãƒ¼ã¾ã§åˆ°é”ãƒ»ãƒ»ãƒ»ï¼ lï¬â€¯ 分散DB本 2 3. 今⽇日ã®è©± lï¬â€¯ Paxos lï¬â€¯ Consensus algorithm(protocol)ã®1㤠lï¬â€¯ ã‚‚ã®ã™ã”ã難ã—ã„ã“ã¨ã§æœ‰å(主ã«å…ƒè«–ï¥â½‚æ–‡ãŒ) lï¬â€¯ æµï§Šã‚Œ lï¬â€¯ Consensus lï¬â€¯ å•é¡Œè¨å®š lï¬â€¯ Paxos lï¬â€¯ (ã¡ã‚‡ã³ã£ã¨ã ã‘)Multi-Paxos lï¬â€¯ å‚考⽂文献紹介 lï¬â€¯ ⽇日本語ã®â½‚文献ãŒå°‘ãªãã€â½¤ç”¨èªžãŒæ€ªã—ã„ã§ã™ã™ã„ã¾ã›ã‚“ 3
The Network is Reliable - ACM Queue
July 23, 2014 Volume 12, issue 7 PDF The Network is Reliable An informal survey of real-world communications failures Peter Bailis, UC Berkeley Kyle Kingsbury, Jepsen Networks "The network is reliable" tops Peter Deutsch's classic list, "Eight fallacies of distributed computing" (https://blogs.oracle.com/jag/resource/Fallacies.html), "all [of which] prove to be false in the long run and all [of wh
GitHub - hashicorp/consul: Consul is a distributed, highly available, and data center aware solution to connect and configure applications across dynamic, distributed infrastructure.
Consul is a distributed, highly available, and data center aware solution to connect and configure applications across dynamic, distributed infrastructure. Website: https://www.consul.io Tutorials: HashiCorp Learn Forum: Discuss Consul provides several key features: Multi-Datacenter - Consul is built to be datacenter aware, and can support any number of regions without complex configuration. Servi
OpenStack Storage(Swift) èª¿æŸ»å ±å‘Šæ›¸ - ã‚¯ãƒªã‚¨ãƒ¼ã‚·ãƒ§ãƒ³ãƒ©ã‚¤ãƒ³æ ªå¼ä¼šç¤¾
2011å¹´1月18æ—¥ 1. æ¦‚è¦ Swift 㯠OpenStack プãƒã‚¸ã‚§ã‚¯ãƒˆãŒé–‹ç™ºã—ã¦ã„る分散オブジェクトストレージã§ã‚る。OpenStack ã¯ã€ã‚¯ãƒ©ã‚¦ãƒ‰ç’°å¢ƒã‚’構築ã™ã‚‹ãŸã‚ã®ã‚ªãƒ¼ãƒ—ンソースプãƒã‚¸ã‚§ã‚¯ãƒˆã§ã‚ã‚Šã€ä»®æƒ³ãƒžã‚·ãƒ³ã®ç®¡ç†ã‚’行ㆠNova ã¨ã€ã‚ªãƒ–ジェクトストレージ㮠Swift ãŒã‚る。Swift ã®ä½ç½®ã¥ã‘ã¨ã—ã¦ã¯ã€Nova ã®ä»®æƒ³ãƒžã‚·ãƒ³ ã®ã‚¤ãƒ¡ãƒ¼ã‚¸ã®ä¿å˜ãªã©ãŒæŒ™ã’られる。ã—ã‹ã—オブジェクトストレージã®æ©Ÿèƒ½ã¯ç‹¬ç«‹ã—ã¦ãŠã‚Šã€Nova 㨠関係ãªã利用ã™ã‚‹ã“ã¨ã‚‚å¯èƒ½ã§ã‚る。ç¾è¡Œã®ä»•æ§˜ã§ã¯ã€Nova ã¨é€£æºã™ã‚‹ã‚ˆã†ã«ã¯ãªã£ã¦ã„ãªã„ãŸã‚ã€ æœ¬å ±å‘Šæ›¸ã§ã¯ Swift ã®ã¿ã®åˆ©ç”¨ã‚’ä¸å¿ƒã«è¿°ã¹ã‚‹ã€‚ Swift ã®å…ƒã«ãªã£ãŸã®ã¯ã€Rackspace 社ã®é‹ç”¨ã™ã‚‹ CloudFiles ã¨ã„ã†ã‚µãƒ¼ãƒ“スã§ã‚ã£ãŸã€‚ç¾åœ¨ ã¯ã‚ªãƒ¼ãƒ—ンソースソフトウェアã¨ã—ã¦å…¬é–‹ã•ã‚Œã¦ãŠã‚Šã€é–‹ç™ºè¨€èªžã«ã¯ Python
Jubatusã«ãŠã‘る大è¦æ¨¡åˆ†æ•£ã‚ªãƒ³ãƒ©ã‚¤ãƒ³æ©Ÿæ¢°å¦ç¿’
1. Jubatusã«ãŠã‘る⼤大è¦æ¨¡åˆ†æ•£ オンライン機械å¦ç¿’ 2011/12/08 @⼤大è¦æ¨¡ãƒ‡ãƒ¼ã‚¿å‡¦ç†ï§¤å‹‰å¼·ä¼š æ ªå¼ä¼šç¤¾Preferred Infrastructure 海野 　裕也 (@unnonouno) 2. ⾃自⼰己紹介 lï¬â€¯ 海野 　裕也 (@unnonouno) lï¬â€¯ Preferred Infrastructure (PFI) ç ”ç©¶é–‹ç™ºéƒ¨â¾¨é–€ãƒªã‚µãƒ¼ãƒãƒ£ãƒ¼ lï¬â€¯ 社員20⼈人ãらㄠlï¬â€¯ 検索索・レコメンドエンジンSedueã®é–‹ç™ºãªã© lï¬â€¯ 専⾨門 lï¬â€¯ ⾃自然⾔言語処ç†ï§¤ lï¬â€¯ テã‚ストマイニング lï¬â€¯ Jubatusプãƒã‚¸ã‚§ã‚¯ãƒˆå†…ã§ã®å½¹å‰² lï¬â€¯ 主ã«ç‰¹å¾´æŠ½å‡ºã‚¨ãƒ³ã‚¸ãƒ³ã€æ©Ÿæ¢°å¦ç¿’エンジンã®ç ”究開発 2 3. Big Data ! lï¬â€¯ データã¯ã“ã‚Œã‹ã‚‰ã‚‚å¢—åŠ ã—続ã‘ã‚‹ 多ã„ã“ã¨ã‚ˆã‚Šå¢—ãˆã¦ã„ãã¨ã„ã†ã“ã¨ãŒé‡è¦ lï¬ ãƒ‡ãƒ¼ã‚¿é‡ï¥¾ã®å¤‰åŒ–ã«å¯¾å¿œã§ãるスケーラブルãªã‚·
What are the seminal papers in distributed systems? Why?
Answer (1 of 12): Note: this is slightly biased to the problems of scalable online processing systems (mostly data storage and messaging). As such I may be leaving out papers related to other (equally important) topics such as HPC, security in distributed systems and may be leaving out important ...
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fogus: 10 Technical Papers Every Programmer Should Read (At Least Twice)
Send More Paramedics λ λ λ Fogus' Thoughts on life, programming, and thinking ⤠c clj erl pl frink fth cl org pure icl qi ⤠Follow me on Twitter... or RSS... Run this blog in mobile 2024 2023 2022 2021 2020 2019 2018 2017 2016 2015 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005 2004 2003 2002 Sep 8, 2011 Let me preface this post by saying that no programmer should feel compelled to read any of
CSUR4703-42
42 Paxos Made Moderately Complex ROBBERT VAN RENESSE and DENIZ ALTINBUKEN, Cornell University This article explains the full reconfigurable multidecree Paxos (or multi-Paxos) protocol. Paxos is by no means a simple protocol, even though it is based on relatively simple invariants. We provide pseudocode and explain it guided by invariants. We initially avoid optimizations that complicate comprehens
Replication, atomicity and order in distributed systems
Replication, atomicity and order in distributed systems Distributed systems are an increasingly important topic in Computer Science. The difficulty and immediate applicability of this topic is what makes distributed systems rewarding to study and build. The goal of this post (and future posts on this topic) is to help the reader develop a basic toolkit they could use to reason about distributed sy
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pytorch-distributed-collective-communication/main.py at main · FrancescoSaverioZuppichini/pytorch-distributed-collective-communication
jax/jax/_src/distributed.py at main · google/jax
Amazon.com: Fault-tolerant Agreement in Synchronous Message-passing Systems (Synthesis Lectures on Distributed Computing Theory) (9781608455256): Michel Raynal, Nancy Lynch: Books
Google's Planet Scale Distributed Storage Patents
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