从Google在OSDI'04上发表了Map/Reduce这篇Paper；到Yahoo！在06年雇佣Doug Cotting，
投入对Hadoop最大的关注，以期提高其计算能力对抗Google；再到CMU CS的系主任发表Tec
h report提出DISC（Data-Intensive Super Computing,在最近一次的Hadoop summit上，
他演讲的slides将Super改成了Scalable）的概念，以及Intel、IBM与Stanford、CMU合作
基于Hadoop搞云计算。Map/Reduce引入的并行计算模型得到了前所未有的关注和应用。
究竟什么是Map/Reduce，为什么需要Map/Reduce，孟岩（此孟岩非彼孟岩，此孟岩是财帮
子的创始人之一）的这篇文章：Map Reduce - the Free Lunch is not over?阐述得很清
楚。（http://www.mengyan.org/blog/archives/2006/11/15/138.html）
随着du-core，multi-core甚至Stanford在做的1024核的出现，我们的Programming Model
会慢慢从OOP转到COP（concurrency-oriented programming）上来。而如何抽象这种progr
amming model的转化，让程序员更加方便的编写并行化程序利用多核甚至分布式系统的计
算能力，成为了很多研究的热点。Map/Reduce就是在这方面做出了不错的努力，这是它的
价值！
于是，在Map/Reduce发表没多久中，很多基于multi-core甚至GPU上的研究也在火热的展开
。
Phoenix： from Stanford
"Evaluating MapReduce for Multi-core and Multiprocessor Systems" —
paper by Colby Ranger, Ramanan Raghuraman, Arun Penmetsa, Gary Bradski, and
Christos Kozyrakis; from Stanford University
很有趣的是，这篇在当年会议上被推荐为best paper的论文居然出自于Stanford开的一门
课”Advanced Processor Design”上的project。（强大的stanford学生啊！）
Mars：from Hongkong University Science and Technology
（GPGPU很猖獗啊~）
# "Mars: A MapReduce Framework on Graphics Processors" — paper by Bingsheng
He, Wenbin Fang, Qiong Luo, Naga K. Govindaraju, Tuyong Wang; from Hong Kong
University of Science and Technology
Cell B.E. Architecture: from University of Wisconsin-Madison（不愧是CS
Architecture No 1的学校啊！）
# "MapReduce for the Cell B.E. Architecture" — paper by Marc de Kruijf and
Karthikeyan Sankaralingam; from University of Wisconsin-Madison
此外，还有一些项目也在应用Map/Reduce的思想。
QtConcurrent ：http://labs.trolltech.com/page/Projects/Threads/QtCo
ncurrent
Open Source C++ MapReduce (non-distributed) implementation from Trolltech
Skynet：http://skynet.rubyforge.org/
Ruby Map/Reduce Framework
最牛的不是语言，不是代码，而是思想！还有Simplified的哲学！
学术界的力量也是不可低估的，很多很神奇很美妙的东西都来自于学术界。大家要好好珍
惜还在学习、做研究的机会。
Thanks to map/Reduce!
Thanks to lisp&other fp!
Thanks to lambda calculus!
Thanks to Alonzo Church!
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