这两百场会议中,一、 学习的目的

2019-07-15 作者:小鱼儿玄机30码姐妹   |   浏览(169)

目前影响机房部分温度过高的原因是:气流组织不合理;机房内部的气流分部混乱,不能形成空气有序的循环;局部风量分配不足。为解决这些问题,必须重新组织气流结构,使其有效对流,带走热量。采用管道精确送风,存在机柜间距离过小,正常管道影响布线及维护工作,管道过细不好风阻过大,达不到精确送风效果。

预告丨2018年值得关注的200场机器学习会议,200场

2017年马上就要过去了,这一年你的收获怎么样?在学习的过程中,独自学习与向别人学习同样重要,其中通过各种会议了解AI行业研究成果是个不错的提高自己的方法。对于专注于机器学习的伙伴来说,2018年有哪些值得关注的会议呢?以下内容来源于Alex Kistenev的总结,建议收藏!

 

按国家总计,这两百场会议中,有80场在美国举办,29场在英国举办,12场在加拿大举办,并且大部分会议在北美举办。

 

按城市总计,这两百场会议中,有28场在伦敦举办,20场在旧金山举办,10场在纽约举办。

 

以下大会列表按照举办时间列出。

 

一月

11–13 Jan, Data Science & Management of Data (CoDS-COMAD). Goa, India.

16–18 Jan, International Conference on Agents and Artificial Intelligence (ICAART). Funchal, Madeira, Portugal.

18 Jan, Alternative Data Conference. New York, USA.

17–19 Jan, Global Artificial Intelligence Conference. Santa Clara, USA.

17–19 Jan, AI NEXTCon. Seattle, USA.

18–19 Jan, AI in Healthcare Summit. Boston, USA.

19–21 Jan, International Conference on Control Engineering and Artificial Intelligence (CCEAI). Boracay, Philippines.

23 Jan, Women in Machine Intelligence Dinner. San Francisco, USA.

25 Jan, Beyond Machine’s Deep Learning Bootcamp. Berlin, Germany.

25–26 Jan, AI Assistant Summit San Francisco. San Francisco, USA.

25–26 Jan, Deep Learning Summit San Francisco. San Francisco, USA.

25–26 Jan, Artificial Intelligence & Machine Learning 101. Chicago, USA.

25–26 Jan, AI on a Social Mission Conference. Montreal, Canada.

27 Jan, Data Day Texas. Austin, USA.

27–30 Jan, Applied Machine Learning Days. Lausanne, Switzerland.

28–29 Jan, International conference on Computers, Data Management and Technology Applications (ICCDMTA). Cairo, Egypt.

30–31 Jan, The AI Congress London. London, UK.

31 Jan, Chatbot Summit. Tel Aviv, Israel.

31 Jan — 1 Feb, Age of AI. San Francisco, USA.

31 Jan — 3 Feb, rstudio::conf 2018. San Diego, USA.

 

二月

2–7 Feb, AAAI Conference. New Orleans, USA.

3–8 Feb, Developer Week. San Francisco, USA.

5–6 Feb, Artificial Intelligence Dev Conference at DeveloperWeek. Oakland, USA.

5–6 Feb, Conversational Interaction Conference. San Jose, USA.

5–7 Feb, Applied AI Summit. London, UK.

6–7 Feb, Predictive Analytics Innovation Summit. San Diego, USA.

6–8 Feb, Chief Data & Analytics Officer Winter. Miami, USA.

7–8 Feb, Big Data & Analytics Summit Canada. Toronto, Canada.

8 Feb, AI Evolution. New York, NY, USA.

8–9 Feb, DataScience Salon Miami. Miami, USA.

14–17 Feb, International Research Conference Robophilosophy. Vienna, Austria.

20 Feb, Women in AI Dinner London. London, UK.

22 Feb, Bottish. Online.

22 Feb, AI Inside Summit. Vienna, Austria.

26–28 Feb, International Conference on Machine Learning and Computing (ICMLC). Macau, China.

27 Feb, AI 4 Business. Lint, Belgium.

27–28 Feb, Gartner Data & Analytics Summit. Sydney, Australia.

 

三月

5–6 Mar, European Artificial Intelligence Innovation Summit. London, UK.

5–8 Mar,ACM/IEEE International Conference on Human Robot Interaction (HRI). Chicago, USA.

5–8 Mar, O’Reilly Strata Data Conference. San Jose, USA.

5–8 Mar, Gartner Data & Analytics Summit. Grapevine, USA.

7–8 Mar, Big Data & Analytics Innovation Summit. Singapore.

7–8 Mar, AI and Sentiment Analysis in Finance. Hong Kong.

7–11 Mar, ACM IUI. Tokyo, Japan.

8 Mar, The Conversational Interface Conference. London, UK

12–14 Mar, Winter Conference on Applications of Computer Vision (WACV). Lake Tahoe, USA.

13–14 Mar, Sentiment Analysis Bangalore 2018. Bangalore, India.

15–16 Mar, AI Assistant Summit London. London, UK.

15–16 Mar, Deep Learning in Retail & Advertising Summit London. London, UK.

15–16 Mar, Big Data & Analytics Innovation Summit. Melbourne, Australia.

15–16 Mar, Artificial Intelligence & Machine Learning 101. Boston, USA.

18–21 Mar, Shoptalk. Las Vegas, USA.

19–21 Mar, Gartner Data & Analytics Summit. London, UK.

19–22 Mar, IBM Think. Las Vegas, USA.

20 Mar, The AI Customer Summit. London, UK.

20–21 Mar, AI & Robotics: Compliance, Liability & Risk Management. San Francisco, USA.

20–22 Mar, Analytics and Data Summit. Redwood Shores, USA.

22 Mar, Data Innovation Summit. Stockholm, Sweden.

22 Mar, Innovation Summit 2018 America. Chicago, USA.

22 Mar, AI & Robotics Director’s Forum. London, UK.

23–25 Mar, Machine Learning Prague 2018. Prague, Czech Republic.

26–29 Mar, GPU Technology Conference. Silicon Valley, USA.

26–27 Mar, EmTech Digital 2018. San Francisco, USA.

29–31 Mar, International Conference on Advanced Computational Intelligence (ICACI). Xiamen, China.

 

四月

5–6 Apr,  Future of Information and Communication Conference (FICC). Singapore.

8–11 Apr, AnacondaCON 2018. Austin, TX, USA.

9–11 Apr,  International Conference on Artificial Intelligence and Statistics (AISTATS). Lanzarote, Canary Islands.

9–11 Apr, SpeechTEK. Washington, USA.

10–13 Apr, O’Reilly Artificial Intelligence Conference Beijing. Beijing, China

12 Apr, Applied Artificial Intelligence Conference. San Francisco, USA.

12 Apr, AI World Forum. San Francisco, USA.

15–20 Apr,  ICASSP 2018. Calgary, Canada.

16–17 Apr, Artificial Intelligence. Las Vegas, USA.

16–17 Apr, Automation and Robotics. Las Vegas, USA.

17–19 Apr, Monage. Mountain View, USA.

18–19 Apr, AI Expo Global. London, UK.

18–19 Apr, Big Data & Analytics Innovation Summit. Hong Kong.

19 Apr, AI Conference Moscow. Moscow, Russia.

19–20 Apr, Big Data Innovation Summit. San Francisco, USA.

22–27 Apr, Enterprise Data World (EDW). San Diego, USA.

23–25 Apr, RPA & AI Summit. Copenhagen, Denmark.

23–27 Apr, The Web Conference. Lyon, France.

24–28 Apr, IEEE International Conference on Soft Robotics (RoboSoft). Livorno, Italy.

25–27 Apr, European Symposium on Artificial Neural Networks. Bruges, Belgium.

26–27 Apr, Big Data & AI Leaders Summit. Sydney, Australia.

29 Apr — 2 May, O’Reilly Artificial Intelligence Conference New York. New York, USA.

30 Apr — 3 May,  International Conference on Learning Representations (ICLR). Vancouver, Canada.

30 Apr — 3 May, TalkRobot. New Orleans, USA.

 

五月

1–2 May, F8 — Facebook Developer Conference. San Diego, USA.

1–4 May, Accelerate AI: Open Data Science Conference East. Boston, USA

3–4 May, AI Congress Vegas. Las Vegas, USA.

3–4 May, The Data Science Conference. Chicago, USA.

3–5 May, SIAM International Conference on Data Mining (SDM18). San Diego, USA.

8 May, Prepare.ai Conference. St. Lous, USA.

9–10 May, Train AI. San Francisco, USA.

9–10 May, Machine Learning Innovation Summit. San Francisco, USA.

15–17 May, Business of Bots 2018. San Francisco, USA.

16–18 May, Colombian Conference on Applications in Computational Intelligence (ColCACI). Medellin, Columbia.

16–19 May, IEEE International Conference on Simulation, Modeling, and Programming for Autonomous Robots (SIMPAR). Brisbane, Australia.

17 May, Rise of AI Conference 2018. Berlin, Germany.

20–24 May, Data Disrupt. New York, USA.

21–25 May, The International Conference on Robotics and Automation (ICRA). Brisbane, Australia.

21–24 May, O’Reilly Strata Data Conference London. London, UK.

21–24 May, Chief Analytics Officer — Spring. San Francisco, USA.

22–23 May, Gartner Data & Analytics Summit. São Paulo, Brazil.

23–24 May, LDV Vision Summit. New York, USA.

24–25 May, Deep Learning Summit Boston. Boston, USA.

31 May — 1 Jun, dotAI. Paris, France.

 

六月

1–6 Jun, Conference of the North American Chapter of the Association for Computational Linguistics (NAACL). New Orleans, USA.

3–6 Jun,  Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD). Melbourne, Australia.

3–7 Jun, Predictive Analytics World Las Vegas. Las Vegas, USA.

4 Jun, Data Science Salon New York. New York, USA.

5–6 Jun, Gartner Data & Analytics Summit. Mumbai, India.

6–7 Jun, Machine Intelligence Summit Hong Kong. Hong Kong.

11–12 Jun, CogX London 2018: Festival of All Things AI. London, UK.

12–13 Jun, AI Toronto. Toronto, Canada.

12–13 Jun, Predictive analytics World Industry 4.0. Munich, Germany.

12–14 Jun, AI Summit London. London, UK.

14–15 Jun, AI & Machine Learning for Clinical Trial and R&D Advancements. Philadelphia, USA.

14–15 Jun, Gartner Data & Analytics Summit. Tokyo, Japan.

14–19 Jun, International Conference on Machine Learning and Data Mining (MLDM). New York, USA.

18–23 Jun, CVPR 2018. Salt Lake City, USA.

20–21 Jun, Conference on Big Data Analysis and Data Mining. Rome, Italy.

20–22 Jun, Distributed Computing and Artificial Intelligence (DCAI). Toledo, Spain.

24–29 Jun,  International Conference on Automated Planning and Scheduling (ICAPS). Delft, The Netherlands.

25–28 Jun, International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems (IEA-AIE). Montreal, Canada.

26–29 Jun, International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research (CPAIOR). Delft, The Netherlands.

26–30 Jun, Robotics: Science and Systems (RSS). Pittsburgh, USA.

27–28 Jun, AI, Machine Learning and Sentiment Analysis Applied to Finance. London, UK.

28 Jun, AI for CxOs Dinner San Francisco. San Francisco, USA.

29 Jun, The 4th Research and Applied AI Summit. London, UK.

TBA Jun, ML Conference. Munich, Germany.

 

七月

1 Jul, AI Talk at SVIEF. Santa Clara, USA.

5–8 Jul,  The Conference on Human Computation and Crowdsourcing (HCOMP). Zurich, Switzerland.

5–9 Jul, COLT 2018. Stockholm, Sweden.

8–12 Jul, Conference on Research and Development in Information Retrieval (SIGIR). Detroit, USA.

9–11 Jul, Applied AI Summit. London, UK.

10–11 Jul, Mobile Beat. San Francisco, USA.

10–12 Jul, Computing Conference. London, UK.

10–15 Jul, International Conference on Machine Learning (ICML). Stockholm, Sweden.

10–15 Jul, International Conference on Autonomous Agents and Multiagent Systems (AAMAS). Stockholm, Sweden.

11–15 Jul,  Industrial Conference on Data Mining (ICDM). New York, USA.

13–19 Jul,  International Joint Conference on Artificial Intelligence and the European Conference on Artificial Intelligence (IJCAI-ECAI). Stockholm, Sweden.

14–19 Jul,  International Conference on Machine Learning and Data Mining (MLDM). New York, USA.

15–20 Jul,  Annual Meeting of the Association for Computational Linguistics (ACL). Melbourne, Australia.

19–21 Jul, Multimedia & Artificial Intelligence. Rome, Italy.

23–24 Jul, International Conference on Data Mining (ICDM). Istanbul, Turkey.

31 Jul — 1 Aug, AI Summit Hong Kong. Hong Kong.

TBA Jul, Anthill Inside. Bangalore, India.

 

八月

12–16 Aug, SIGGRAPH 2018. Vancouver, Canada.

19–23 Aug,  KDD 2018. London, UK.

20–24 Aug,  IEEE International Conference on Automation Science and Engineering (CASE). Munich, Germany.

20–24 Aug, International Conference on Pattern Recognition (ICPR). Beijing, China.

20–25 Aug, International Conference on Computational Linguistics (COLING). Santa Fe, USA.

21–22 Aug, Artificial Intelligence, Robotics & IoT. Paris, France.

30–31 Aug, Computer science, Machine Learning and Big data analytics conference. Dubai, UAE.

 

九月

2–6 Sep,  Interspeech 2018. Hyderabad, India.

3–6 Sep,  British Machine Vision Conference (BMVC). Newcastle upon Tyne, UK.

4–7 Sep, O’Reilly Artificial Intelligence Conference San Francisco. San Francisco, USA.

6–7 Sep, Intelligent Systems Conference (IntelliSys). London, UK.

8–14 Sep, European Conference of Computer Vision (ECCV). Munich, Germany.

9–12 Sep, International Symposium Advances in Artificial Intelligence and Applications (AAIA). Poznan, Poland.

10–11 Sep, Robots and Deep Learning. Singapore.

11–12 Sep, Big Data Innovation Summit. Boston, USA.

11–14 Sep, O’Reilly Strata Data Conference New York. New York, USA.

17–18 Sep, International Conference on Human-Robot Interaction (ICHRI). Rome, Italy.

17–18 Sep, 2nd Artificial Intelligence Innovation Summit. San Francisco, USA.

18–20 Sept, International Joint Conference on Computational Intelligence (IJCCI). Seville, Spain.

18–20 Sep, AI Summit San Francisco. San Francisco, USA.

19–21 Sep, International Conference on Computer-Human Interaction Research and Applications (CHIRA). Seville, Spain.

20–21 Sep, Deep Learning in Healthcare Summit London. London, UK.

23–25 Sep, Auto AI. Berlin, Germany.

27–29 Sep, IEEE Workshop on Advanced Robotics and its Social Impacts (ARSO). Genova, Italy.

 

十月

1–2 Oct, AI Expo Europe. Amsterdam, The Netherlands.

1–5 Oct, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Madrid, Spain.

3–4 Oct, MACHINA Summit. London, UK.

5 Oct, BCS Machine Intelligence competition. London, UK.

8–11 Oct, O’Reilly Artificial Intelligence Conference London. London, UK.

10–11 Oct, World Summit AI. Amsterdam, The Netherlands.

15–17 Oct, Minds Mastering Machines [m3]. London, UK.

17–18 Oct, Nordic Data Science and Machine Learning Summit. Stockholm, Sweden.

17–18 Oct, Predictive Analytics World London. London, UK.

21–24 Oct, AI Deep Dive at Money 2020. Las Vegas, USA.

22–26 Oct, International Conference on Information and Knowledge Management (CKIM). Turin, Italy.

23 Oct, Women in AI Dinner Toronto. Toronto, Canada.

23–24 Oct, VB Summit. Berkeley, USA.

24–25 Oct, Predictive Analytics Innovation Summit. Chicago, USA.

25–26 Oct, Deep Learning Summit Toronto. Toronto, Canada.

31 Oct — 04 Nov, Open Data Science Conference West. San Francisco, USA.

 

十一月

1–2 Nov, Big Data & Analytics Innovation Summit. London, UK.

5–8 Nov, TalkRobot at Web Summit. Lisbon, Portugal.

13–14 Nov, Predictive Analytics World Berlin. Berlin, Germany.

13–15 Nov, AI Summit Cape Town. Cape Town, South Africa.

14–16 Nov, Big Data Spain. Madrid, Spain.

15–16 Nov, Future Technologies Conference 2018. Vancouver, Canada.

21–22 Nov, Big Data & Analytics Innovation Summit. Beijing, China.

28–29 Nov, AI Expo North America. Santa Clara, USA.

29–30 Nov, AI Expo North America. Santa Clara, USA.

TBA Nov, AI & Robotics Main Event. London, UK.

 

十二月

3–8 Dec, NIPS. Montréal, Canada.

7 Dec, Machine Learning Innovation Summit. Dublin, Ireland.

2018 掌握好这几点方法学习Linux,一定比别人更快入门运维!,2018linux

2010年3月,英特尔发布至强5600处理器(代号Westmere-EP)的一个月之后,IBM在IDF大会上,亮相M3两款机架产品,随后5月,IBM在官网上公示了M3详细情况。

一、机房现存在的问题

**

如今有很多关于Linux的书籍,博客。大多数都会比较“粗暴“的将一大堆的命令塞给读者,从而使很多Linux初学者望而却步,未入其门就路过了。

下面给大家找了一下一个资深Linux用户关于学习Linux的一些建议:

随着Linux应用的扩展许多朋友开始接触Linux,根据学习Windwos的经验往往有一些茫然的感觉:不知从何处开始学起。作为一个 Linux系统管理员,我看了许多有关Linux的文档和书籍,并为学习Linux付出了许多艰苦的努力。当真正获得了一份正式的Linux系统管理工作后,我更加深刻地理解了Linux的灵魂:服务与多用户。Linux系统知识是非常广博的,但是只要掌握了重点知识,管理它并没有想象中的那么可怕。在下面我会将作为系统管理员的一些工作心得和总结出来的经验系统地介绍给大家。

一、 学习的目的

通过Linux的学习掌握UNIX的目的想必不用多说了,在这个网络人才身价倍增的年代,想靠技术吃饭又不想掌握网络和编程技术是不明智的。当一人第一次听说Linux并跃跃欲试的时候,总会提出几个?

它是什么(What)? 

为什么要用它(Why)? 

怎样学习它(How)?

做为开放源码运动的主要组成部分,Linux的应用越来越广泛,从我们平时的娱乐、学习,到商业、政府办公,再到大规模计算的应用。为了满足人们的需求,各种各样的、基于Linux的应用软件层出不穷。只要具备了LinuX的基本功,并具有了自学的能力之后,都可以通过长期的学习将专项内容予以掌握。

二、 从命令开始学习

常常有些朋友一接触Linux 就是希望构架网站,根本没有想到要先了解一下Linux 的基础。这是相当困难的。虽然Linux桌面应用发展很快,但是命令在Linux中依然有很强的生命力。Linux是一个命令行组成的操作系统,精髓在命令行,无论图形界面发展到什么水平这个原理是不会变的,Linux命令有许多强大的功能:从简单的磁盘操作、文件存取、到进行复杂的多媒体图象和流媒体文件的制作。这里笔者把它们中比较重要的和使用频率最多的命令,按照它们在系统中的作用分成几个部分介绍给大家,通过这些基础命令的学习我们可以进一步理解 Linux系统:

●**安装和登录命令:login、 shutdown、 halt、 reboot 、mount、umount 、chsh **文件处理命令:file、 mkdir、 grep、dd、 find、 mv 、ls 、diff、 cat、 ln
●**系统管理相关命令: df、 top、 free、 quota 、at、 lp、 adduser、 groupadd kill、 crontab、 tar、 unzip、 gunzip 、last ●网络操作命令:ifconfig、 ip 、ping 、 netstat 、telnet、 ftp、 route、 rlogin rcp 、finger 、mail 、nslookup ●系统安全相关命令:** passwd 、su、 umask 、chgrp、 chmod、chown、chattr、sudo、 pswho

三、 选择好的入门Linux书籍和相关视频

在各个Linux论坛中,我们看到最多的问题往往是某个新手,在安装或使用linux的过程中遇到一个具体的问题就开始提问,很多都是重复性的问题,甚至有不少人连基本的问题描述都不是很清楚。这说明很多初学linux的人还没有掌握基本功。怎样才能快速提高掌握linux的基本功呢? 

最有效的方法莫过于学习权威的linux工具书,工具书对于学习者而言是相当重要的。一本错误观念的工具书却会让新手整个误入歧途。编者不再这里做过多推荐,建议入门的童鞋们多在网上搜搜相关书籍的评价以及介绍,切记零基础的童鞋不要选择内容过深的书籍。

目前网络上也有很多免费的相关视频,建议没有接触过或者刚接触运维行业的童鞋先多去看看一些免费的基础视频或者参加一些线下的免费行业介绍讲座,这样才能知道该如何入门,如何着手学习或者选择什么方式学习,这都是很重要的。

四 、养成在命令行下工作的习惯

一定要养成在命令行下工作的习惯,要知道X-window只是运行在命令行模式下的一个应用程序。在命令行下学习虽然一开始进度较慢,但是熟悉后,您未来的学习之路将是以指数增加的方式增长的。从网管员来说,命令行实际上就是规则,它总是有效的,同时也是灵活的。即使是通过一条缓慢的调制解调器线路,它也能操纵几千公里以外地远程系统。

五、用Unix思维思考Linux

由于Linux是参照Unix的思想来设计的,理解和掌握它就必须以Unix的思维来进行,而不能以Windows思维。不可否认,windows 在市场上的成功很大一部分在于技术思想的独到之处。可是这个创新是在面对个人用户的前提下进行的,而面对着企业级的服务应用,它还是有些力不从心。多年来在计算机操作系统领域一直是二者独大:unix在服务器领域,Windows在个人用户领域。由此可见,用户需求决定了所采用的操作系统。不管什么原因,如果要学习Linux,那么首先要将思维从Windows的“这个小河” 中拖出来,放入Unix的海洋。

六 、学习shell和Python

对于Shell(中文名称壳),习惯Windows的读者肯定是非常陌生的,因为Windows只有一个“Shell”(如果可以说是Shell的话),那就是Windows自己。用一句话容易理解的解释就是,shell是用户输入命令与系统解释命令之间的中介。最直观的说法,一种Shell有一套自己的命令。举一个容易理解的例子,Linux的标准Shel是Bash Shel;Solaris的shell是B shell;Linux的Shell是以命令行的方式表现出来的。读者可能会不理解,Windows从命令行“进化”到了图形界面,那么Linux现在还使用命令行岂不是一种倒退?

当初刚刚接触Linux时就曾有过这种想法。可是后来发现,如果使用图形界面,那么分配给应用软件的资源就少了,在价格昂贵的服务器上,能够以较低的硬件配置实现同样的功能是非常重要的。

下面举例说明:

一台服务器有1GB内存,假设其中512MB用于处理图形界面,若要安装一个需要784MB内存的数据库软件,惟一的办法就是扩大内存。但是如果使用命令行,系统可能只需要64MB内存,其它的内存就可以供数据库软件使用了。使用命令行,不仅是内存,而且CPU及硬盘等资源的占用都要节省很多。

所以,作为服务器使用命令行是优点而不是缺点。既然Shell有这么多优点,就必须要学习它。

七、关注行业趋势更新技能

Linux运维的招聘要求感觉与往年同样薪资的招聘要求高了许多,又得会各种开源工具.还得懂K8S和docker。但凡15K以上的工资,都必须要会python,而且是要有一定的pythonweb开发能力,2016年这个时候一般的运维都是要求: shell/python/php,三选一,会点就行,但是2017年不一样了,python要具有一定的web开发能力才可以。如果不要求会python的,也势必要求shell很精通。

 这里给出一点小的技能提升的建议: 大致需要学习下这四个部分:

  • 自动化运维(Ansible,Puppet,Saltstack等)

  • Devops(Docker,K8s,Jenkins,Jira等), 

  • 云服务技术(虚拟化、OpenStack、AWS及阿里云各种产品服务架构等)

  • python

上面几条仅供参考,不一定适合所有人,具体的学习方法还有自己取舍了!

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M3是M2系列的升级版,其最大亮点是,采用了英特尔今年最新的六核处理器——Xeon 5600。IBM有两款双路机架产品最先享此殊荣:System x3550 M3 和x3650 M3。升级后的产品,与现有对应的机型x3550 M2 和x3650 M2,又有哪些差异不同和超越呢?本篇将带读者解开面纱,一探究竟。

机房现状:通化移动生产五楼交换机房安装了五台精密空调分别是:9AU16一台、9AU22两台、M40一台、M60一台,送风方式均为上送风,目前采用风帽直吹式送风。

一、IBM M2与M3两代服务器技术规格差异比较

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