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Posted by Corinna Cortes and Alfred Spector, Google Research

Googlers across the company actively engage with the scientific community by publishing technical papers, contributing open-source packages, working on standards, introducing new APIs and tools, giving talks and presentations, participating in ongoing technical debates, and much more. Our publications offer technical and algorithmic advances, feature aspects we learn as we develop novel products and services, and shed light on some of the technical challenges we face at Google.

In an effort to highlight some of our work, we periodically select a number of publications to be featured on this blog. We first posted a set of papers on this blog in mid-2010 and subsequently discussed them in more detail in the following blog postings. In a second round, we highlighted new noteworthy papers from the later half of 2010. This time we honor the influential papers authored or co-authored by Googlers covering all of 2011 — covering roughly 10% of our total publications.  It’s tough choosing, so we may have left out some important papers.  So, do see the publications list to review the complete group.

In the coming weeks we will be offering a more in-depth look at these publications, but here are some summaries:

Audio processing

“Cascades of two-pole–two-zero asymmetric resonators are good models of peripheral auditory function”, Richard F. Lyon,Journal of the Acoustical Society of America, vol. 130 (2011), pp. 3893-3904.
Lyon’s long title summarizes a result that he has been working toward over many years of modeling sound processing in the inner ear.  This nonlinear cochlear model is shown to be “good” with respect to psychophysical data on masking, physiological data on mechanical and neural response, and computational efficiency. These properties derive from the close connection between wave propagation and filter cascades. This filter-cascade model of the ear is used as an efficient sound processor for several machine hearing projects at Google.

Electronic Commerce and Algorithms

“Online Vertex-Weighted Bipartite Matching and Single-bid Budgeted Allocations”, Gagan Aggarwal, Gagan Goel, Chinmay Karande, Aranyak Mehta, SODA 2011.
The authors introduce an elegant and powerful algorithmic technique to the area of online ad allocation and matching: a hybrid of random perturbations and greedy choice to make decisions on the fly. Their technique sheds new light on classic matching algorithms, and can be used, for example, to pick one among a set of relevant ads, without knowing in advance the demand for ad slots on future web page views.

“Milgram-routing in social networks”, Silvio Lattanzi, Alessandro Panconesi, D. Sivakumar, Proceedings of the 20th International Conference on World Wide Web, WWW 2011, pp. 725-734.
Milgram’s “six-degrees-of-separation experiment” and the fascinating small world hypothesis that follows from it, have generated a lot of interesting research in recent years. In this landmark experiment, Milgram showed that people unknown to each other are often connected by surprisingly short chains of acquaintances. In the paper we prove theoretically and experimentally how a recent model of social networks, “Affiliation Networks”, offers an explanation to this phenomena and inspires interesting technique for local routing within social networks.

“Non-Price Equilibria in Markets of Discrete Goods”, Avinatan Hassidim, Haim Kaplan, Yishay Mansour, Noam Nisan, EC, 2011.
We present a correspondence between markets of indivisible items, and a family of auction based n player games. We show that a market has a price based (Walrasian) equilibrium if and only if the corresponding game has a pure Nash equilibrium. We then turn to markets which do not have a Walrasian equilibrium (which is the interesting case), and study properties of the mixed Nash equilibria of the corresponding games.

HCI

“From Basecamp to Summit: Scaling Field Research Across 9 Locations”, Jens Riegelsberger, Audrey Yang, Konstantin Samoylov, Elizabeth Nunge, Molly Stevens, Patrick Larvie, CHI 2011 Extended Abstracts.
The paper reports on our experience with a basecamp research hub to coordinate logistics and ongoing real-time analysis with research teams in the field. We also reflect on the implications for the meaning of research in a corporate context, where much of the value may be less in a final report, but more in the curated impressions and memories our colleagues take away from the the research trip.

“User-Defined Motion Gestures for Mobile Interaction”, Jaime Ruiz, Yang Li, Edward Lank, CHI 2011: ACM Conference on Human Factors in Computing Systems, pp. 197-206.
Modern smartphones contain sophisticated sensors that can detect rich motion gestures — deliberate movements of the device by end-users to invoke commands. However, little is known about best-practices in motion gesture design for the mobile computing paradigm. We systematically studied the design space of motion gestures via a guessability study that elicits end-user motion gestures to invoke commands on a smartphone device. The study revealed consensus among our participants on parameters of movement and on mappings of motion gestures onto commands, by which we developed a taxonomy for motion gestures and compiled an end-user inspired motion gesture set. The work lays the foundation of motion gesture design—a new dimension for mobile interaction.

Information Retrieval

“Reputation Systems for Open Collaboration”, B.T. Adler, L. de Alfaro, A. Kulshrestra, I. Pye, Communications of the ACM, vol. 54 No. 8 (2011), pp. 81-87.
This paper describes content based reputation algorithms, that rely on automated content analysis to derive user and content reputation, and their applications for Wikipedia and google Maps. The Wikipedia reputation system WikiTrust relies on a chronological analysis of user contributions to articles, metering positive or negative increments of reputation whenever new contributions are made. The Google Maps system Crowdsensus compares the information provided by users on map business listings and computes both a likely reconstruction of the correct listing and a reputation value for each user. Algorithmic-based user incentives ensure the trustworthiness of evaluations of Wikipedia entries and Google Maps business information.

Machine Learning and Data Mining

“Domain adaptation in regression”, Corinna Cortes, Mehryar Mohri, Proceedings of The 22nd International Conference on Algorithmic Learning Theory, ALT 2011.
Domain adaptation is one of the most important and challenging problems in machine learning.  This paper presents a series of theoretical guarantees for domain adaptation in regression, gives an adaptation algorithm based on that theory that can be cast as a semi-definite programming problem, derives an efficient solution for that problem by using results from smooth optimization, shows that the solution can scale to relatively large data sets, and reports extensive empirical results demonstrating the benefits of this new adaptation algorithm.

“On the necessity of irrelevant variables”, David P. Helmbold, Philip M. Long, ICML, 2011
Relevant variables sometimes do much more good than irrelevant variables do harm, so that it is possible to learn a very accurate classifier using predominantly irrelevant variables.  We show that this holds given an assumption that formalizes the intuitive idea that the variables are non-redundant.  For problems like this it can be advantageous to add many additional variables, even if only a small fraction of them are relevant.

“Online Learning in the Manifold of Low-Rank Matrices”, Gal Chechik, Daphna Weinshall, Uri Shalit, Neural Information Processing Systems (NIPS 23), 2011, pp. 2128-2136.
Learning measures of similarity from examples of similar and dissimilar pairs is a problem that is hard to scale. LORETA uses retractions, an operator from matrix optimization, to learn low-rank similarity matrices efficiently. This allows to learn similarities between objects like images or texts when represented using many more features than possible before.

Machine Translation

“Training a Parser for Machine Translation Reordering”, Jason Katz-Brown, Slav Petrov, Ryan McDonald, Franz Och, David Talbot, Hiroshi Ichikawa, Masakazu Seno, Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing (EMNLP ’11).
Machine translation systems often need to understand the syntactic structure of a sentence to translate it correctly. Traditionally, syntactic parsers are evaluated as standalone systems against reference data created by linguists. Instead, we show how to train a parser to optimize reordering accuracy in a machine translation system, resulting in measurable improvements in translation quality over a more traditionally trained parser.

“Watermarking the Outputs of Structured Prediction with an application in Statistical Machine Translation”, Ashish Venugopal,Jakob Uszkoreit, David Talbot, Franz Och, Juri Ganitkevitch, Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing (EMNLP).
We propose a general method to watermark and probabilistically identify the structured results of machine learning algorithms with an application in statistical machine translation. Our approach does not rely on controlling or even knowing the inputs to the algorithm and provides probabilistic guarantees on the ability to identify collections of results from one’s own algorithm, while being robust to limited editing operations.

“Inducing Sentence Structure from Parallel Corpora for Reordering”, John DeNero, Jakob Uszkoreit, Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing (EMNLP).
Automatically discovering the full range of linguistic rules that govern the correct use of language is an appealing goal, but extremely challenging.  Our paper describes a targeted method for discovering only those aspects of linguistic syntax necessary to explain how two different languages differ in their word ordering.  By focusing on word order, we demonstrate an effective and practical application of unsupervised grammar induction that improves a Japanese to English machine translation system.

Multimedia and Computer Vision

“Kernelized Structural SVM Learning for Supervised Object Segmentation”, Luca Bertelli, Tianli Yu, Diem Vu, Burak Gokturk,Proceedings of IEEE Conference on Computer Vision and Pattern Recognition 2011.
The paper proposes a principled way for computers to learn how to segment the foreground from the background of an image given a set of training examples. The technology is build upon a specially designed nonlinear segmentation kernel under the recently proposed structured SVM learning framework.

“Auto-Directed Video Stabilization with Robust L1 Optimal Camera Paths”, Matthias Grundmann, Vivek Kwatra, Irfan Essa,IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2011).
Casually shot videos captured by handheld or mobile cameras suffer from significant amount of shake. Existing in-camera stabilization methods dampen high-frequency jitter but do not suppress low-frequency movements and bounces, such as those observed in videos captured by a walking person. On the other hand, most professionally shot videos usually consist of carefully designed camera configurations, using specialized equipment such as tripods or camera dollies, and employ ease-in and ease-out for transitions. Our stabilization technique automatically converts casual shaky footage into more pleasant and professional looking videos by mimicking these cinematographic principles. The original, shaky camera path is divided into a set of segments, each approximated by either constant, linear or parabolic motion, using an algorithm based on robust L1 optimization. The stabilizer has been part of the YouTube Editor (youtube.com/editor) since March 2011.

“The Power of Comparative Reasoning”, Jay Yagnik, Dennis Strelow, David Ross, Ruei-Sung Lin, International Conference on Computer Vision (2011).
The paper describes a theory derived vector space transform that converts vectors into sparse binary vectors such that Euclidean space operations on the sparse binary vectors imply rank space operations in the original vector space. The transform a) does not need any data-driven supervised/unsupervised learning b) can be computed from polynomial expansions of the input space in linear time (in the degree of the polynomial) and c) can be implemented in 10-lines of code. We show competitive results on similarity search and sparse coding (for classification) tasks.

NLP

“Unsupervised Part-of-Speech Tagging with Bilingual Graph-Based Projections”, Dipanjan Das, Slav Petrov, Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics (ACL ’11), 2011, Best Paper Award.
We would like to have natural language processing systems for all languages, but obtaining labeled data for all languages and tasks is unrealistic and expensive. We present an approach which leverages existing resources in one language (for example English) to induce part-of-speech taggers for languages without any labeled training data. We use graph-based label propagation for cross-lingual knowledge transfer and use the projected labels as features in a hidden Markov model trained with the Expectation Maximization algorithm.

Networks

“TCP Fast Open”, Sivasankar Radhakrishnan, Yuchung Cheng, Jerry Chu, Arvind Jain, Barath Raghavan, Proceedings of the 7th International Conference on emerging Networking EXperiments and Technologies (CoNEXT), 2011.
TCP Fast Open enables data exchange during TCP’s initial handshake. It decreases application network latency by one full round-trip time, a significant speedup for today’s short Web transfers. Our experiments on popular websites show that Fast Open reduces the whole-page load time over 10% on average, and in some cases up to 40%.

“Proportional Rate Reduction for TCP”, Nandita Dukkipati, Matt Mathis, Yuchung Cheng, Monia Ghobadi, Proceedings of the 11th ACM SIGCOMM Conference on Internet Measurement 2011, Berlin, Germany – November 2-4, 2011.
Packet losses increase latency of Web transfers and negatively impact user experience. Proportional rate reduction (PRR) is designed to recover from losses quickly, smoothly and accurately by pacing out retransmissions across received ACKs during TCP’s fast recovery. Experiments on Google Web and YouTube servers in U.S. and India demonstrate that PRR reduces the TCP latency of connections experiencing losses by 3-10% depending on response size.

Security and Privacy

“Automated Analysis of Security-Critical JavaScript APIs”, Ankur Taly, Úlfar Erlingsson, John C. Mitchell, Mark S. Miller, Jasvir Nagra, IEEE Symposium on Security & Privacy (SP), 2011.
As software is increasingly written in high-level, type-safe languages, attackers have fewer means to subvert system fundamentals, and attacks are more likely to exploit errors and vulnerabilities in application-level logic. This paper describes a generic, practical defense against such attacks, which can protect critical application resources even when those resources are partially exposed to attackers via software interfaces.  In the context of carefully-crafted fragments of JavaScript, the paper applies formal methods and semantics to prove that these defenses can provide complete, non-circumventable mediation of resource access; the paper also shows how an implementation of the techniques can establish the properties of widely-used software, and find previously-unknown bugs.

“App Isolation: Get the Security of Multiple Browsers with Just One”, Eric Y. Chen, Jason Bau, Charles Reis, Adam Barth, Collin Jackson, 18th ACM Conference on Computer and Communications Security, 2011.
We find that anecdotal advice to use a separate web browser for sites like your bank is indeed effective at defeating most cross-origin web attacks.  We also prove that a single web browser can provide the same key properties, for sites that fit within the compatibility constraints.

Speech

“Improving the speed of neural networks on CPUs”, Vincent Vanhoucke, Andrew Senior, Mark Z. Mao, Deep Learning and Unsupervised Feature Learning Workshop, NIPS 2011.
As deep neural networks become state-of-the-art in real-time machine learning applications such as speech recognition, computational complexity is fast becoming a limiting factor in their adoption. We show how to best leverage modern CPU architectures to significantly speed-up their inference.

“Bayesian Language Model Interpolation for Mobile Speech Input”, Cyril Allauzen, Michael Riley, Interspeech 2011.
Voice recognition on the Android platform must contend with many possible target domains – e.g. search, maps, SMS. For each of these, a domain-specific language model was built by linearly interpolating several n-gram LMs from a common set of Google corpora. The current work has found a way to efficiently compute a single n-gram language model with accuracy very close to the domain-specific LMs but with considerably less complexity at recognition time.

Statistics

“Large-Scale Parallel Statistical Forecasting Computations in R”, Murray Stokely, Farzan Rohani, Eric Tassone, JSM Proceedings, Section on Physical and Engineering Sciences, 2011.
This paper describes the implementation of a framework for utilizing distributed computational infrastructure from within the R interactive statistical computing environment, with applications to timeseries forecasting. This system is widely used by the statistical analyst community at Google for data analysis on very large data sets.

Structured Data

“Dremel: Interactive Analysis of Web-Scale Datasets”, Sergey Melnik, Andrey Gubarev, Jing Jing Long, Geoffrey Romer, Shiva Shivakumar, Matt Tolton, Communications of the ACM, vol. 54 (2011), pp. 114-123.
Dremel is a scalable, interactive ad-hoc query system. By combining multi-level execution trees and columnar data layout, it is capable of running aggregation queries over trillion-row tables in seconds. Besides continued growth internally to Google, Dremel now also backs an increasing number of external customers including BigQuery and UIs such as AdExchange front-end.

“Representative Skylines using Threshold-based Preference Distributions”, Atish Das Sarma, Ashwin Lall, Danupon Nanongkai, Richard J. Lipton, Jim Xu, International Conference on Data Engineering (ICDE), 2011.
The paper adopts principled approach towards representative skylines and formalizes the problem of displaying k tuples such that the probability that a random user clicks on one of them is maximized. This requires mathematically modeling (a) the likelihood with which a user is interested in a tuple, as well as (b) how one negotiates the lack of knowledge of an explicit set of users. This work presents theoretical and experimental results showing that the suggested algorithm significantly outperforms previously suggested approaches.

“Hyper-local, directions-based ranking of places”, Petros Venetis, Hector Gonzalez, Alon Y. Halevy, Christian S. Jensen,PVLDB, vol. 4(5) (2011), pp. 290-30.
Click through information is one of the strongest signals we have for ranking web pages. We propose an equivalent signal for raking real world places: The number of times that people ask for precise directions to the address of the place. We show that this signal is competitive in quality with human reviews while being much cheaper to collect, we also show that the signal can be incorporated efficiently into a location search system.

Systems

“Power Management of Online Data-Intensive Services”, David Meisner, Christopher M. Sadler, Luiz André Barroso, Wolf-Dietrich Weber, Thomas F. Wenisch, Proceedings of the 38th ACM International Symposium on Computer Architecture, 2011.
Compute and data intensive Web services (such as Search) are a notoriously hard target for energy savings techniques. This article characterizes the statistical hardware activity behavior of servers running Web search and discusses the potential opportunities of existing and proposed energy savings techniques.

“The Impact of Memory Subsystem Resource Sharing on Datacenter Applications”, Lingjia Tang, Jason Mars, Neil Vachharajani, Robert Hundt, Mary-Lou Soffa, ISCA, 2011.
In this work, the authors expose key characteristics of an emerging class of Google-style workloads and show how to enhance system software to take advantage of these characteristics to improve efficiency in data centers. The authors find that across datacenter applications, there is both a sizable benefit and a potential degradation from improperly sharing micro-architectural resources on a single machine (such as on-chip caches and bandwidth to memory). The impact of co-locating threads from multiple applications with diverse memory behavior changes the optimal mapping of thread to cores for each application. By employing an adaptive thread-to-core mapper, the authors improved the performance of the datacenter applications by up to 22% over status quo thread-to-core mapping, achieving performance within 3% of optimal.

“Language-Independent Sandboxing of Just-In-Time Compilation and Self-Modifying Code”, Jason Ansel, Petr Marchenko, Úlfar Erlingsson, Elijah Taylor, Brad Chen, Derek Schuff, David Sehr, Cliff L. Biffle, Bennet S. Yee, ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI), 2011.
Since its introduction in the early 90′s, Software Fault Isolation, or SFI, has been a static code technique, commonly perceived as incompatible with dynamic libraries, runtime code generation, and other dynamic code. This paper describes how to address this limitation and explains how the SFI techniques in Google Native Client were extended to support modern language implementations based on just-in-time code generation and runtime instrumentation. This work is already deployed in Google Chrome, benefitting millions of users, and was developed over a summer collaboration with three Ph.D. interns; it exemplifies how Research at Google is focused on rapidly bringing significant benefits to our users through groundbreaking technology and real-world products.

“Thialfi: A Client Notification Service for Internet-Scale Applications”, Atul Adya, Gregory Cooper, Daniel Myers, Michael Piatek,Proc. 23rd ACM Symposium on Operating Systems Principles (SOSP), 2011, pp. 129-142.
This paper describes a notification service that scales to hundreds of millions of users, provides sub-second latency in the common case, and guarantees delivery even in the presence of a wide variety of failures.  The service has been deployed in several popular Google applications including Chrome, Google Plus, and Contacts.

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错失了智能手机市场初期的发展机遇后，曾经的山寨之王联发科已经彻底归来，智能型解决方案的出货量不断猛增，收入和利润也是节节攀升。

联发科总裁谢清江(Hsieh Ching-chiang)在昨日的投资者大会上表示，该公司的智能手机芯片在第三季度出货了3500-4000万颗，第四季度有望超过4000万颗。

分析人士则更加乐观，认为第四季度的出货量将会接近5000万颗。

谢清江表示，中国智能手机市场的迅猛发展，及其双核处理器的批量出货，都是取得这一成绩的关键因素。他还披露说，第三季度的出货量事实上已经超过了公司此前的预期，其中单核MT6575、双核MT6577所占比例最大，特别是后者已经获得了内地多家手机厂商的采纳。

谢清江称，联发科将于2013年第一季度出货其首款四核芯片MT6589，采用28nm工艺制造。

联发科第三季度收入294.7亿新台币(62.95亿元人民币)，同比增长26.1％，环比增长25.7％，其中中国内地智能手机市场贡献最大；净利润为49.4亿新台币(10.55亿元人民币)，环比增长47.2％；每股收益4.06新台币(0.87元人民币)，环比增长37.6％；毛利率41.2％，环比增加0.4个百分点。

联发科预计第四季度收入289-309亿新台币(61.7-66.0亿元人民币)，毛利率41-43％。

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http://linux.chinaunix.net/hellogcc2012/

2012年11月10日， 我们将来迎来2012年HelloGcc
WorkShop，这已经是ChinaUnix社区第三次和HelloGcc工作组合作，在国内为推广GNU
Gcc等相关技术交流而举办该项活动。今年我们继续选择北京中科院研究生院中关村教学楼作为我们的活动地点，欢迎大家积极参加！
（2010现场图片和PPT）（2011现场图片和PPT）

【活动简介】
HelloGcc工作组于2007年，由自由软件爱好者成立，旨在营造一个自由，开放，共享的技术社区，讨论和学习GNU底层系统工具，包括GCC，GDB，BINUTILS等。我们每年都会举办一次这样的技术讨论会，希望通过自由，开放，共享的方式来增进大家相互的交流。

如果你有什么问题，可以发送邮件到：hellogcc@freelists.org，或在ChinaUnix论坛的CPU与编译器板块发帖讨论相关活动事项！

【时间日程】

2012年11月10日（周六）下午
13:25 – 13:30——致谢、宣传
13:30 – 14:10——话题1＋提问
14:10 – 14:50——话题2＋提问
14:50 – 15:30——话题3＋提问
15:30 – 15:50——休息&自由讨论，抽奖环节
15:50 – 16:30——话题4＋提问
16:30 – 17:10——话题5＋提问
17:10 – 17:30——话题6＋提问
17:30 – 17:45——抽奖环节，合影

【演讲主题】

1、LLVM: Another Toolchain Platform
演讲者：杨勇勇
中国科学院自动化研究所在读博士生，三年级。感兴趣的领域包括：嵌入式系统开发平台、大规模数据计算、软件工程、编译优化技术、代码生成及调度算法、操作系统等等。
简介：自动化研究所下属的“国家专用集成电路设计与研究工程技术中心”目前正在开发一款面向极大数据量和运算量的SoC平台原型，负责数据处理的核心是一个自主设计、概念新颖的多运算核系统。本人负责的工作内容是构建该处理核心的软件工具链，包含C语言编译器、汇编器、反汇编器、链接器、调试器等。

我们选择LLVM作为编译工具的实现基础。该话题演讲讨论的是一套基本的软件开发平台，我们会介绍LLVM系统结构，如何实现一个LLVM的后端，以及通过LLVM的MC层整合汇编器/反汇编器，并在最后简单讨论链接器和符号调试器。

2、GCC上的空间优化
演讲者：陈振强 or 程斌
陈振强博士是ARM资深编译软件工程师并且是Linaro工具链工作组的成员。他在编译相关领域有多年的工作经验。他目前的工作重点是代码性能和空间优化；程斌是ARM编译软件工程师。他在编译及嵌入式相关领域有多年工作经验。他最近做了大量优化GCC代码空间的工作。
简介： 随着越来越多的工控机嵌入式开发人员使用GCC进行开发，GCC
生成代码的长度问题越来越得到重视。由于历史上GCC的空间优化不象性能优化那样活跃，我们认为GCC生成代码长度有更多的潜力改进以满足开发者的需求。最近一年我们重点做了GCC和库的空间优化和分析，这个演讲将介绍这些工作的方法，发现及成果。

3、淺談如何參與社群開發
演讲者：陳韋任，曾參與 LLVM 3.1 ARM 平台測試
简介：以輕鬆的方式，並以個人經驗分享如何參與社群開發。希望藉此吸引及鼓勵更多人參與開源軟件社群。

4、更快的android模拟器
演讲者：康烁
简介： 我们使用了以LLVM为中间语言的动态二进制翻译技术作为我们全系统模拟器的指令执行引擎，并且根据全系统模拟的特点做了多种优化，最后给出相关性能分析以及性能测试数据。目前我们的全系统模拟器已经可以正确的运行android3.0系统，以及一些典型应用如Angry
Bird等。通过nbench，Dhrystone,
whetstone等性能测试用例的初步分析，指令执行速度比已有的android官方模拟器有一定提高。其中会和大家讨论和分析一些优化的技术：
* 混合执行的翻译策略问题
* TLB以及内存访问优化技术，包括我们实现的技术和qemu已有的技术
* 指令翻译块的划分等等。

5、KGTP，GDB 和 Linux
演讲者：朱辉 (teawater) KGTP和GDB开发者
简介：KGTP(http://code.google.com/p/kgtp/) 是一个 灵活 轻量级 实时 Linux 调试器 和
跟踪器。将对KGTP各种功能进行一些介绍。

6、MIPS SDK演示
演讲者：刘佳
简介：市面上不乏优秀的MIPS处理器，比如jz4770，但是相对于如火如荼的ARM，MIPS的生态环境显得比较薄弱，我将于近期免费提供一套MIPS
SDK下载，包含QT-Creator，GNU
Toolchain，QEMU，LLVM，MIPS-GNU/Linux，U-Boot，方便大家进行MIPS相关的开发。

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同学们，

你们久等了！ （鼓掌。。。）

如果说陌陌，微信其实火爆的本质就是OND，N夜情，我们这些宅男宅女工程师休闲的时候的利器应该是什么？

我们如何在这个声色犬马的年代，保持自己的尊严，同时还能解决我们的激素问题？ 我们拒绝那些无聊的OND！ Say， NO！

答案是：读图年代！

“读图年代－－读图咯”隆重发布，为社会打造读图嘉年华！ www DOT dutulo DOT com （读图咯）为你奉献美丽的视觉体验！美奂美轮！

“每日推荐” 为你每天用户推荐的美图，你每天疲劳的时候，中午休息的时候，晚上冲浪的时候，打开WWW，打开你的iPad，平板，Android手机，你久享受长寿的时光［注：科学数据表明，看美图（含美女）一张，长寿5分钟，while OND一定是折寿］

我们目前通过机器学习，数据挖掘，为广大的工程师朋友奉献了如下栏目：

喜欢北美购物的工程师们，我们为你们通过图片的方式，把最及时的北美的各种打折，优惠的商品信息全面啼血奉献。方便你们找同学，朋友在北美代购！

Last but apparently not least， 我们为在北美的同学完整打造新浪微博和鬼子的Facebook的互通。你可以一键把你喜欢的一个新浪weibo转发到你的Faebook的wall上，也可以在我们的”读图咯“完整的阅读你的Facebook feeds，然后一键转发到新浪weibo！！！ 首创weibo和Facebook的duplex messaging！ 为中美文化交流开辟了新篇章！

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II. 调查

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      根据北斗官网的报道，2012年10月25日23时33分，我国在西昌卫星发射中心用“长征三号丙”运载火箭，成功将第十六颗北斗导航卫星发射升空并送入预定转移轨道。这是一颗地球静止轨道卫星，将与先期发射的十五颗北斗导航卫星组网运行，形成区域服务能力。根据计划，北斗卫星导航系统将于明年初向亚太大部分地区提供正式服务。

      有点意外的是，这是一颗同步轨道卫星，因为之前已经发射过五颗同步轨道卫星，按照北斗的技术方案是已经够了。也许某颗同步卫星在天上需要个备份，这次就再打一颗。

      此次发射的北斗导航卫星和“长三丙”运载火箭，分别由中国航天科技集团公司所属中国空间技术研究院和中国运载火箭技术研究院研制。这是长征系列运载火箭的第170次发射。

      至此，北斗二代总共发射的十六颗星为：同步轨道卫星六颗，顺序为COMPASS－G2、COMPASS－G1、COMPASS－G3、 COMPASS－G4、COMPASS－G5、COMPASS－G6；中轨星五颗 COMPASS－MEO1、COMPASS－MEO2、COMPASS－MEO3、COMPASS－MEO4、COMPASS－MEO5；倾斜同步轨道五颗：COMPASS-IGS1、COMPASS-IGS2、 COMPASS-IGS3、COMPASS-IGS4、 COMPASS-IGS5。覆盖亚太区域，五颗中轨星也许够了；明年之后如果要逐步覆盖全球，就需要多打几颗MEO星了。

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就在作为舶来品的“云计算”热浪余热未消时，10月出版的最新一期《国际云计算杂志》（International Journal of Cloud Computing）以长达百余页的专辑形式介绍了我国科学家研制的新型云计算操作系统TransOS，给了IT业界一个“意外”，引起国际科技新闻界的广泛关注。

文章下载地址：http://pan.baidu.com/share/link?shareid=89396&uk=3389271398

在题为《TransOS：基于透明计算的云操作系统》的论文中，中国工程院院士、中南大学校长张尧学首次向国际业界全面介绍了新一代网络化操作系统TransOS：它将包含传统操作系统、应用程序和数据的“代码”全部存储在一台服务器（云）上，允许多台只装有少量代码的“裸机”连接访问，用户只需动态调用必要代码即可运行。在该组专辑其他文章中，来自清华大学、英特尔公司以及日本和加拿大的研究人员分别从数据管理、实现案例、移动和嵌入式设备上的应用及隐私保护模式等方面对该操作系统进行了详尽讨论。

TransOS基于“透明计算”的理念研制。该理念最早由张尧学于2004年提出，其核心是将存储与运算分离、将软件与硬件（终端）分离，通过有缓存的“流”式运算，将计算还原为“不知不觉、用户可控”的个性化服务。在这种模式下，操作系统被视为一种网络资源从终端“剥离”。

这一变化导致了诸多改变的发生，使TransOS成为了名符其实的“管理操作系统的操作系统”，它不仅占用资源更少、可靠性更高，更具有谷歌Chrome等类似云操作系统所不具备的跨平台、跨设备操作的优点，不仅可在个人电脑、服务器、智能手机、平板电脑乃至智能家电上运行，而且适用于苹果、谷歌、微软等公司开发的不同平台，从而打破了不同“云”之间的垄断和分割。

张尧学告诉记者，尽管TransOS对经典的冯·诺依曼计算机体系结构进行了“革命性改进”，但在网络足够快的条件下，用户几乎感觉不到后台这种变化的存在。

该组文章发表后，国际知名新闻媒体《每日科学》（ScienceDaily）、《技术视野》（TechEYE）, 《每日技术新闻》（TechNewsDaily）等媒体分别以《在云中的操作系统：TransOS或将取代传统桌面操作系统》，《中国人希望把计算机大脑放在云中》，《研究人员将操作系统推送到云中》等为题进行了报道。

对TransOS的应用前景，张尧学保持了谨慎的乐观。他向记者表示，TransOS目前还不会对现有的桌面式操作系统造成威胁，但会派生出许多新的终端、产生大量新的应用机会。他同时坦承，由于TransOS对网络带宽提出了更高要求，这将使对高速互联网的需求变得更为迫切。

张尧学 中国工程院院士，教授、博士生导师，中南大学校长（副部长级）。解放军总装备部军用计算机及软件技术专业组专家，国家信息化专家咨询委员会、计算机学会普适计算专委会委员，《International Journal of Wireless and Mobile Computing》、《Journal of Autonomic and Trusted Computing》、《Chinese Journal of Electronics等国内外学术期刊的编委。

文章摘要：云计算现在已经成为一个研究热点。在众多研究的问题中，云计算操作系统吸引了大量人们的关注。但是到目前为止，人们仍然无法回答什么是云计算操作系统、如何开发云计算操作系统。本文从透明计算的视角提出了一种云计算操作系统——TransOS，它将包含传统操作系统、应用程序和数据的“代码”全部存储在一台服务器（云）上，允许多台只装有少量代码的“裸机”连接访问，用户只需动态调用必要代码即可运行。TransOS管理所有的资源，为用户提供包括操作系统在内的完整的服务。本文首先介绍透明计算的概念作为本文的背景，介绍透明计算的特性。然后本文介绍了TransOS的设计结构，最后距离说明了TransOS的应用。

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