-
1 some data
Научный термин: некоторые данные -
2 Included in Table 10 are some data on the amount of water formed
Универсальный англо-русский словарь > Included in Table 10 are some data on the amount of water formed
-
3 Data Analyzer Light
A component that performs some of the simpler data processing tasks for the Web Analytics Web Part. -
4 data processing
The manipulation of data to transform it into some desired result. -
5 data problems
-
6 Data Execution Prevention
"A security feature that monitors programs on a computer to determine if they use system memory safely. To do this, DEP software works alone or with compatible microprocessors to mark some memory locations as ""non-executable."" If a program tries to run code that is malicious or is not from a protected location, DEP closes the program and notifies you." -
7 some insight is provided into the ways these data influence ...
• дается некоторое понимание того, как эти данные влияют на...English-Russian dictionary of phrases and cliches for a specialist researcher > some insight is provided into the ways these data influence ...
-
8 modular data center
модульный центр обработки данных (ЦОД)
-
[Интент]Параллельные тексты EN-RU
[ http://dcnt.ru/?p=9299#more-9299]
Data Centers are a hot topic these days. No matter where you look, this once obscure aspect of infrastructure is getting a lot of attention. For years, there have been cost pressures on IT operations and this, when the need for modern capacity is greater than ever, has thrust data centers into the spotlight. Server and rack density continues to rise, placing DC professionals and businesses in tighter and tougher situations while they struggle to manage their IT environments. And now hyper-scale cloud infrastructure is taking traditional technologies to limits never explored before and focusing the imagination of the IT industry on new possibilities.
В настоящее время центры обработки данных являются широко обсуждаемой темой. Куда ни посмотришь, этот некогда малоизвестный аспект инфраструктуры привлекает все больше внимания. Годами ИТ-отделы испытывали нехватку средств и это выдвинуло ЦОДы в центр внимания, в то время, когда необходимость в современных ЦОДах стала как никогда высокой. Плотность серверов и стоек продолжают расти, все больше усложняя ситуацию для специалистов в области охлаждения и организаций в их попытках управлять своими ИТ-средами. И теперь гипермасштабируемая облачная инфраструктура подвергает традиционные технологии невиданным ранее нагрузкам, и заставляет ИТ-индустрию искать новые возможности.
At Microsoft, we have focused a lot of thought and research around how to best operate and maintain our global infrastructure and we want to share those learnings. While obviously there are some aspects that we keep to ourselves, we have shared how we operate facilities daily, our technologies and methodologies, and, most importantly, how we monitor and manage our facilities. Whether it’s speaking at industry events, inviting customers to our “Microsoft data center conferences” held in our data centers, or through other media like blogging and white papers, we believe sharing best practices is paramount and will drive the industry forward. So in that vein, we have some interesting news to share.
В компании MicroSoft уделяют большое внимание изучению наилучших методов эксплуатации и технического обслуживания своей глобальной инфраструктуры и делятся результатами своих исследований. И хотя мы, конечно, не раскрываем некоторые аспекты своих исследований, мы делимся повседневным опытом эксплуатации дата-центров, своими технологиями и методологиями и, что важнее всего, методами контроля и управления своими объектами. Будь то доклады на отраслевых событиях, приглашение клиентов на наши конференции, которые посвящены центрам обработки данных MicroSoft, и проводятся в этих самых дата-центрах, или использование других средств, например, блоги и спецификации, мы уверены, что обмен передовым опытом имеет первостепенное значение и будет продвигать отрасль вперед.
Today we are sharing our Generation 4 Modular Data Center plan. This is our vision and will be the foundation of our cloud data center infrastructure in the next five years. We believe it is one of the most revolutionary changes to happen to data centers in the last 30 years. Joining me, in writing this blog are Daniel Costello, my director of Data Center Research and Engineering and Christian Belady, principal power and cooling architect. I feel their voices will add significant value to driving understanding around the many benefits included in this new design paradigm.
Сейчас мы хотим поделиться своим планом модульного дата-центра четвертого поколения. Это наше видение и оно будет основанием для инфраструктуры наших облачных дата-центров в ближайшие пять лет. Мы считаем, что это одно из самых революционных изменений в дата-центрах за последние 30 лет. Вместе со мной в написании этого блога участвовали Дэниел Костелло, директор по исследованиям и инжинирингу дата-центров, и Кристиан Белади, главный архитектор систем энергоснабжения и охлаждения. Мне кажется, что их авторитет придаст больше веса большому количеству преимуществ, включенных в эту новую парадигму проектирования.
Our “Gen 4” modular data centers will take the flexibility of containerized servers—like those in our Chicago data center—and apply it across the entire facility. So what do we mean by modular? Think of it like “building blocks”, where the data center will be composed of modular units of prefabricated mechanical, electrical, security components, etc., in addition to containerized servers.
Was there a key driver for the Generation 4 Data Center?Наши модульные дата-центры “Gen 4” будут гибкими с контейнерами серверов – как серверы в нашем чикагском дата-центре. И гибкость будет применяться ко всему ЦОД. Итак, что мы подразумеваем под модульностью? Мы думаем о ней как о “строительных блоках”, где дата-центр будет состоять из модульных блоков изготовленных в заводских условиях электрических систем и систем охлаждения, а также систем безопасности и т.п., в дополнение к контейнеризованным серверам.
Был ли ключевой стимул для разработки дата-центра четвертого поколения?
If we were to summarize the promise of our Gen 4 design into a single sentence it would be something like this: “A highly modular, scalable, efficient, just-in-time data center capacity program that can be delivered anywhere in the world very quickly and cheaply, while allowing for continued growth as required.” Sounds too good to be true, doesn’t it? Well, keep in mind that these concepts have been in initial development and prototyping for over a year and are based on cumulative knowledge of previous facility generations and the advances we have made since we began our investments in earnest on this new design.Если бы нам нужно было обобщить достоинства нашего проекта Gen 4 в одном предложении, это выглядело бы следующим образом: “Центр обработки данных с высоким уровнем модульности, расширяемости, и энергетической эффективности, а также возможностью постоянного расширения, в случае необходимости, который можно очень быстро и дешево развертывать в любом месте мира”. Звучит слишком хорошо для того чтобы быть правдой, не так ли? Ну, не забывайте, что эти концепции находились в процессе начальной разработки и создания опытного образца в течение более одного года и основываются на опыте, накопленном в ходе развития предыдущих поколений ЦОД, а также успехах, сделанных нами со времени, когда мы начали вкладывать серьезные средства в этот новый проект.
One of the biggest challenges we’ve had at Microsoft is something Mike likes to call the ‘Goldilock’s Problem’. In a nutshell, the problem can be stated as:
The worst thing we can do in delivering facilities for the business is not have enough capacity online, thus limiting the growth of our products and services.Одну из самых больших проблем, с которыми приходилось сталкиваться Майкрософт, Майк любит называть ‘Проблемой Лютика’. Вкратце, эту проблему можно выразить следующим образом:
Самое худшее, что может быть при строительстве ЦОД для бизнеса, это не располагать достаточными производственными мощностями, и тем самым ограничивать рост наших продуктов и сервисов.The second worst thing we can do in delivering facilities for the business is to have too much capacity online.
А вторым самым худшим моментом в этой сфере может слишком большое количество производственных мощностей.
This has led to a focus on smart, intelligent growth for the business — refining our overall demand picture. It can’t be too hot. It can’t be too cold. It has to be ‘Just Right!’ The capital dollars of investment are too large to make without long term planning. As we struggled to master these interesting challenges, we had to ensure that our technological plan also included solutions for the business and operational challenges we faced as well.
So let’s take a high level look at our Generation 4 designЭто заставило нас сосредоточиваться на интеллектуальном росте для бизнеса — refining our overall demand picture. Это не должно быть слишком горячим. И это не должно быть слишком холодным. Это должно быть ‘как раз, таким как надо!’ Нельзя делать такие большие капиталовложения без долгосрочного планирования. Пока мы старались решить эти интересные проблемы, мы должны были гарантировать, что наш технологический план будет также включать решения для коммерческих и эксплуатационных проблем, с которыми нам также приходилось сталкиваться.
Давайте рассмотрим наш проект дата-центра четвертого поколенияAre you ready for some great visuals? Check out this video at Soapbox. Click here for the Microsoft 4th Gen Video.
It’s a concept video that came out of my Data Center Research and Engineering team, under Daniel Costello, that will give you a view into what we think is the future.
From a configuration, construct-ability and time to market perspective, our primary goals and objectives are to modularize the whole data center. Not just the server side (like the Chicago facility), but the mechanical and electrical space as well. This means using the same kind of parts in pre-manufactured modules, the ability to use containers, skids, or rack-based deployments and the ability to tailor the Redundancy and Reliability requirements to the application at a very specific level.
Посмотрите это видео, перейдите по ссылке для просмотра видео о Microsoft 4th Gen:
Это концептуальное видео, созданное командой отдела Data Center Research and Engineering, возглавляемого Дэниелом Костелло, которое даст вам наше представление о будущем.
С точки зрения конфигурации, строительной технологичности и времени вывода на рынок, нашими главными целями и задачами агрегатирование всего дата-центра. Не только серверную часть, как дата-центр в Чикаго, но также системы охлаждения и электрические системы. Это означает применение деталей одного типа в сборных модулях, возможность использования контейнеров, салазок, или стоечных систем, а также возможность подстраивать требования избыточности и надежности для данного приложения на очень специфичном уровне.Our goals from a cost perspective were simple in concept but tough to deliver. First and foremost, we had to reduce the capital cost per critical Mega Watt by the class of use. Some applications can run with N-level redundancy in the infrastructure, others require a little more infrastructure for support. These different classes of infrastructure requirements meant that optimizing for all cost classes was paramount. At Microsoft, we are not a one trick pony and have many Online products and services (240+) that require different levels of operational support. We understand that and ensured that we addressed it in our design which will allow us to reduce capital costs by 20%-40% or greater depending upon class.
Нашими целями в области затрат были концептуально простыми, но трудно реализуемыми. В первую очередь мы должны были снизить капитальные затраты в пересчете на один мегаватт, в зависимости от класса резервирования. Некоторые приложения могут вполне работать на базе инфраструктуры с резервированием на уровне N, то есть без резервирования, а для работы других приложений требуется больше инфраструктуры. Эти разные классы требований инфраструктуры подразумевали, что оптимизация всех классов затрат имеет преобладающее значение. В Майкрософт мы не ограничиваемся одним решением и располагаем большим количеством интерактивных продуктов и сервисов (240+), которым требуются разные уровни эксплуатационной поддержки. Мы понимаем это, и учитываем это в своем проекте, который позволит нам сокращать капитальные затраты на 20%-40% или более в зависимости от класса.For example, non-critical or geo redundant applications have low hardware reliability requirements on a location basis. As a result, Gen 4 can be configured to provide stripped down, low-cost infrastructure with little or no redundancy and/or temperature control. Let’s say an Online service team decides that due to the dramatically lower cost, they will simply use uncontrolled outside air with temperatures ranging 10-35 C and 20-80% RH. The reality is we are already spec-ing this for all of our servers today and working with server vendors to broaden that range even further as Gen 4 becomes a reality. For this class of infrastructure, we eliminate generators, chillers, UPSs, and possibly lower costs relative to traditional infrastructure.
Например, некритичные или гео-избыточные системы имеют низкие требования к аппаратной надежности на основе местоположения. В результате этого, Gen 4 можно конфигурировать для упрощенной, недорогой инфраструктуры с низким уровнем (или вообще без резервирования) резервирования и / или температурного контроля. Скажем, команда интерактивного сервиса решает, что, в связи с намного меньшими затратами, они будут просто использовать некондиционированный наружный воздух с температурой 10-35°C и влажностью 20-80% RH. В реальности мы уже сегодня предъявляем эти требования к своим серверам и работаем с поставщиками серверов над еще большим расширением диапазона температур, так как наш модуль и подход Gen 4 становится реальностью. Для подобного класса инфраструктуры мы удаляем генераторы, чиллеры, ИБП, и, возможно, будем предлагать более низкие затраты, по сравнению с традиционной инфраструктурой.
Applications that demand higher level of redundancy or temperature control will use configurations of Gen 4 to meet those needs, however, they will also cost more (but still less than traditional data centers). We see this cost difference driving engineering behavioral change in that we predict more applications will drive towards Geo redundancy to lower costs.
Системы, которым требуется более высокий уровень резервирования или температурного контроля, будут использовать конфигурации Gen 4, отвечающие этим требованиям, однако, они будут также стоить больше. Но все равно они будут стоить меньше, чем традиционные дата-центры. Мы предвидим, что эти различия в затратах будут вызывать изменения в методах инжиниринга, и по нашим прогнозам, это будет выражаться в переходе все большего числа систем на гео-избыточность и меньшие затраты.
Another cool thing about Gen 4 is that it allows us to deploy capacity when our demand dictates it. Once finalized, we will no longer need to make large upfront investments. Imagine driving capital costs more closely in-line with actual demand, thus greatly reducing time-to-market and adding the capacity Online inherent in the design. Also reduced is the amount of construction labor required to put these “building blocks” together. Since the entire platform requires pre-manufacture of its core components, on-site construction costs are lowered. This allows us to maximize our return on invested capital.
Еще одно достоинство Gen 4 состоит в том, что он позволяет нам разворачивать дополнительные мощности, когда нам это необходимо. Как только мы закончим проект, нам больше не нужно будет делать большие начальные капиталовложения. Представьте себе возможность более точного согласования капитальных затрат с реальными требованиями, и тем самым значительного снижения времени вывода на рынок и интерактивного добавления мощностей, предусматриваемого проектом. Также снижен объем строительных работ, требуемых для сборки этих “строительных блоков”. Поскольку вся платформа требует предварительного изготовления ее базовых компонентов, затраты на сборку также снижены. Это позволит нам увеличить до максимума окупаемость своих капиталовложений.
Мы все подвергаем сомнениюIn our design process, we questioned everything. You may notice there is no roof and some might be uncomfortable with this. We explored the need of one and throughout our research we got some surprising (positive) results that showed one wasn’t needed.
В своем процессе проектирования мы все подвергаем сомнению. Вы, наверное, обратили внимание на отсутствие крыши, и некоторым специалистам это могло не понравиться. Мы изучили необходимость в крыше и в ходе своих исследований получили удивительные результаты, которые показали, что крыша не нужна.
Серийное производство дата центров
In short, we are striving to bring Henry Ford’s Model T factory to the data center. http://en.wikipedia.org/wiki/Henry_Ford#Model_T. Gen 4 will move data centers from a custom design and build model to a commoditized manufacturing approach. We intend to have our components built in factories and then assemble them in one location (the data center site) very quickly. Think about how a computer, car or plane is built today. Components are manufactured by different companies all over the world to a predefined spec and then integrated in one location based on demands and feature requirements. And just like Henry Ford’s assembly line drove the cost of building and the time-to-market down dramatically for the automobile industry, we expect Gen 4 to do the same for data centers. Everything will be pre-manufactured and assembled on the pad.Мы хотим применить модель автомобильной фабрики Генри Форда к дата-центру. Проект Gen 4 будет способствовать переходу от модели специализированного проектирования и строительства к товарно-производственному, серийному подходу. Мы намерены изготавливать свои компоненты на заводах, а затем очень быстро собирать их в одном месте, в месте строительства дата-центра. Подумайте о том, как сегодня изготавливается компьютер, автомобиль или самолет. Компоненты изготавливаются по заранее определенным спецификациям разными компаниями во всем мире, затем собираются в одном месте на основе спроса и требуемых характеристик. И точно так же как сборочный конвейер Генри Форда привел к значительному уменьшению затрат на производство и времени вывода на рынок в автомобильной промышленности, мы надеемся, что Gen 4 сделает то же самое для дата-центров. Все будет предварительно изготавливаться и собираться на месте.
Невероятно энергоэффективный ЦОД
And did we mention that this platform will be, overall, incredibly energy efficient? From a total energy perspective not only will we have remarkable PUE values, but the total cost of energy going into the facility will be greatly reduced as well. How much energy goes into making concrete? Will we need as much of it? How much energy goes into the fuel of the construction vehicles? This will also be greatly reduced! A key driver is our goal to achieve an average PUE at or below 1.125 by 2012 across our data centers. More than that, we are on a mission to reduce the overall amount of copper and water used in these facilities. We believe these will be the next areas of industry attention when and if the energy problem is solved. So we are asking today…“how can we build a data center with less building”?А мы упоминали, что эта платформа будет, в общем, невероятно энергоэффективной? С точки зрения общей энергии, мы получим не только поразительные значения PUE, но общая стоимость энергии, затраченной на объект будет также значительно снижена. Сколько энергии идет на производство бетона? Нам нужно будет столько энергии? Сколько энергии идет на питание инженерных строительных машин? Это тоже будет значительно снижено! Главным стимулом является достижение среднего PUE не больше 1.125 для всех наших дата-центров к 2012 году. Более того, у нас есть задача сокращения общего количества меди и воды в дата-центрах. Мы думаем, что эти задачи станут следующей заботой отрасли после того как будет решена энергетическая проблема. Итак, сегодня мы спрашиваем себя…“как можно построить дата-центр с меньшим объемом строительных работ”?
Строительство дата центров без чиллеровWe have talked openly and publicly about building chiller-less data centers and running our facilities using aggressive outside economization. Our sincerest hope is that Gen 4 will completely eliminate the use of water. Today’s data centers use massive amounts of water and we see water as the next scarce resource and have decided to take a proactive stance on making water conservation part of our plan.
Мы открыто и публично говорили о строительстве дата-центров без чиллеров и активном использовании в наших центрах обработки данных технологий свободного охлаждения или фрикулинга. Мы искренне надеемся, что Gen 4 позволит полностью отказаться от использования воды. Современные дата-центры расходуют большие объемы воды и так как мы считаем воду следующим редким ресурсом, мы решили принять упреждающие меры и включить экономию воды в свой план.
By sharing this with the industry, we believe everyone can benefit from our methodology. While this concept and approach may be intimidating (or downright frightening) to some in the industry, disclosure ultimately is better for all of us.
Делясь этим опытом с отраслью, мы считаем, что каждый сможет извлечь выгоду из нашей методологией. Хотя эта концепция и подход могут показаться пугающими (или откровенно страшными) для некоторых отраслевых специалистов, раскрывая свои планы мы, в конечном счете, делаем лучше для всех нас.
Gen 4 design (even more than just containers), could reduce the ‘religious’ debates in our industry. With the central spine infrastructure in place, containers or pre-manufactured server halls can be either AC or DC, air-side economized or water-side economized, or not economized at all (though the sanity of that might be questioned). Gen 4 will allow us to decommission, repair and upgrade quickly because everything is modular. No longer will we be governed by the initial decisions made when constructing the facility. We will have almost unlimited use and re-use of the facility and site. We will also be able to use power in an ultra-fluid fashion moving load from critical to non-critical as use and capacity requirements dictate.
Проект Gen 4 позволит уменьшить ‘религиозные’ споры в нашей отрасли. Располагая базовой инфраструктурой, контейнеры или сборные серверные могут оборудоваться системами переменного или постоянного тока, воздушными или водяными экономайзерами, или вообще не использовать экономайзеры. Хотя можно подвергать сомнению разумность такого решения. Gen 4 позволит нам быстро выполнять работы по выводу из эксплуатации, ремонту и модернизации, поскольку все будет модульным. Мы больше не будем руководствоваться начальными решениями, принятыми во время строительства дата-центра. Мы сможем использовать этот дата-центр и инфраструктуру в течение почти неограниченного периода времени. Мы также сможем применять сверхгибкие методы использования электрической энергии, переводя оборудование в режимы критической или некритической нагрузки в соответствии с требуемой мощностью.
Gen 4 – это стандартная платформаFinally, we believe this is a big game changer. Gen 4 will provide a standard platform that our industry can innovate around. For example, all modules in our Gen 4 will have common interfaces clearly defined by our specs and any vendor that meets these specifications will be able to plug into our infrastructure. Whether you are a computer vendor, UPS vendor, generator vendor, etc., you will be able to plug and play into our infrastructure. This means we can also source anyone, anywhere on the globe to minimize costs and maximize performance. We want to help motivate the industry to further innovate—with innovations from which everyone can reap the benefits.
Наконец, мы уверены, что это будет фактором, который значительно изменит ситуацию. Gen 4 будет представлять собой стандартную платформу, которую отрасль сможет обновлять. Например, все модули в нашем Gen 4 будут иметь общепринятые интерфейсы, четко определяемые нашими спецификациями, и оборудование любого поставщика, которое отвечает этим спецификациям можно будет включать в нашу инфраструктуру. Независимо от того производите вы компьютеры, ИБП, генераторы и т.п., вы сможете включать свое оборудование нашу инфраструктуру. Это означает, что мы также сможем обеспечивать всех, в любом месте земного шара, тем самым сводя до минимума затраты и максимальной увеличивая производительность. Мы хотим создать в отрасли мотивацию для дальнейших инноваций – инноваций, от которых каждый сможет получать выгоду.
Главные характеристики дата-центров четвертого поколения Gen4To summarize, the key characteristics of our Generation 4 data centers are:
Scalable
Plug-and-play spine infrastructure
Factory pre-assembled: Pre-Assembled Containers (PACs) & Pre-Manufactured Buildings (PMBs)
Rapid deployment
De-mountable
Reduce TTM
Reduced construction
Sustainable measuresНиже приведены главные характеристики дата-центров четвертого поколения Gen 4:
Расширяемость;
Готовая к использованию базовая инфраструктура;
Изготовление в заводских условиях: сборные контейнеры (PAC) и сборные здания (PMB);
Быстрота развертывания;
Возможность демонтажа;
Снижение времени вывода на рынок (TTM);
Сокращение сроков строительства;
Экологичность;Map applications to DC Class
We hope you join us on this incredible journey of change and innovation!
Long hours of research and engineering time are invested into this process. There are still some long days and nights ahead, but the vision is clear. Rest assured however, that we as refine Generation 4, the team will soon be looking to Generation 5 (even if it is a bit farther out). There is always room to get better.
Использование систем электропитания постоянного тока.
Мы надеемся, что вы присоединитесь к нам в этом невероятном путешествии по миру изменений и инноваций!
На этот проект уже потрачены долгие часы исследований и проектирования. И еще предстоит потратить много дней и ночей, но мы имеем четкое представление о конечной цели. Однако будьте уверены, что как только мы доведем до конца проект модульного дата-центра четвертого поколения, мы вскоре начнем думать о проекте дата-центра пятого поколения. Всегда есть возможность для улучшений.So if you happen to come across Goldilocks in the forest, and you are curious as to why she is smiling you will know that she feels very good about getting very close to ‘JUST RIGHT’.
Generations of Evolution – some background on our data center designsТак что, если вы встретите в лесу девочку по имени Лютик, и вам станет любопытно, почему она улыбается, вы будете знать, что она очень довольна тем, что очень близко подошла к ‘ОПИМАЛЬНОМУ РЕШЕНИЮ’.
Поколения эволюции – история развития наших дата-центровWe thought you might be interested in understanding what happened in the first three generations of our data center designs. When Ray Ozzie wrote his Software plus Services memo it posed a very interesting challenge to us. The winds of change were at ‘tornado’ proportions. That “plus Services” tag had some significant (and unstated) challenges inherent to it. The first was that Microsoft was going to evolve even further into an operations company. While we had been running large scale Internet services since 1995, this development lead us to an entirely new level. Additionally, these “services” would span across both Internet and Enterprise businesses. To those of you who have to operate “stuff”, you know that these are two very different worlds in operational models and challenges. It also meant that, to achieve the same level of reliability and performance required our infrastructure was going to have to scale globally and in a significant way.
Мы подумали, что может быть вам будет интересно узнать историю первых трех поколений наших центров обработки данных. Когда Рэй Оззи написал свою памятную записку Software plus Services, он поставил перед нами очень интересную задачу. Ветра перемен двигались с ураганной скоростью. Это окончание “plus Services” скрывало в себе какие-то значительные и неопределенные задачи. Первая заключалась в том, что Майкрософт собиралась в еще большей степени стать операционной компанией. Несмотря на то, что мы управляли большими интернет-сервисами, начиная с 1995 г., эта разработка подняла нас на абсолютно новый уровень. Кроме того, эти “сервисы” охватывали интернет-компании и корпорации. Тем, кому приходится всем этим управлять, известно, что есть два очень разных мира в области операционных моделей и задач. Это также означало, что для достижения такого же уровня надежности и производительности требовалось, чтобы наша инфраструктура располагала значительными возможностями расширения в глобальных масштабах.
It was that intense atmosphere of change that we first started re-evaluating data center technology and processes in general and our ideas began to reach farther than what was accepted by the industry at large. This was the era of Generation 1. As we look at where most of the world’s data centers are today (and where our facilities were), it represented all the known learning and design requirements that had been in place since IBM built the first purpose-built computer room. These facilities focused more around uptime, reliability and redundancy. Big infrastructure was held accountable to solve all potential environmental shortfalls. This is where the majority of infrastructure in the industry still is today.
Именно в этой атмосфере серьезных изменений мы впервые начали переоценку ЦОД-технологий и технологий вообще, и наши идеи начали выходить за пределы общепринятых в отрасли представлений. Это была эпоха ЦОД первого поколения. Когда мы узнали, где сегодня располагается большинство мировых дата-центров и где находятся наши предприятия, это представляло весь опыт и навыки проектирования, накопленные со времени, когда IBM построила первую серверную. В этих ЦОД больше внимания уделялось бесперебойной работе, надежности и резервированию. Большая инфраструктура была призвана решать все потенциальные экологические проблемы. Сегодня большая часть инфраструктуры все еще находится на этом этапе своего развития.
We soon realized that traditional data centers were quickly becoming outdated. They were not keeping up with the demands of what was happening technologically and environmentally. That’s when we kicked off our Generation 2 design. Gen 2 facilities started taking into account sustainability, energy efficiency, and really looking at the total cost of energy and operations.
Очень быстро мы поняли, что стандартные дата-центры очень быстро становятся устаревшими. Они не поспевали за темпами изменений технологических и экологических требований. Именно тогда мы стали разрабатывать ЦОД второго поколения. В этих дата-центрах Gen 2 стали принимать во внимание такие факторы как устойчивое развитие, энергетическая эффективность, а также общие энергетические и эксплуатационные.
No longer did we view data centers just for the upfront capital costs, but we took a hard look at the facility over the course of its life. Our Quincy, Washington and San Antonio, Texas facilities are examples of our Gen 2 data centers where we explored and implemented new ways to lessen the impact on the environment. These facilities are considered two leading industry examples, based on their energy efficiency and ability to run and operate at new levels of scale and performance by leveraging clean hydro power (Quincy) and recycled waste water (San Antonio) to cool the facility during peak cooling months.
Мы больше не рассматривали дата-центры только с точки зрения начальных капитальных затрат, а внимательно следили за работой ЦОД на протяжении его срока службы. Наши объекты в Куинси, Вашингтоне, и Сан-Антонио, Техас, являются образцами наших ЦОД второго поколения, в которых мы изучали и применяли на практике новые способы снижения воздействия на окружающую среду. Эти объекты считаются двумя ведущими отраслевыми примерами, исходя из их энергетической эффективности и способности работать на новых уровнях производительности, основанных на использовании чистой энергии воды (Куинси) и рециклирования отработанной воды (Сан-Антонио) для охлаждения объекта в самых жарких месяцах.
As we were delivering our Gen 2 facilities into steel and concrete, our Generation 3 facilities were rapidly driving the evolution of the program. The key concepts for our Gen 3 design are increased modularity and greater concentration around energy efficiency and scale. The Gen 3 facility will be best represented by the Chicago, Illinois facility currently under construction. This facility will seem very foreign compared to the traditional data center concepts most of the industry is comfortable with. In fact, if you ever sit around in our container hanger in Chicago it will look incredibly different from a traditional raised-floor data center. We anticipate this modularization will drive huge efficiencies in terms of cost and operations for our business. We will also introduce significant changes in the environmental systems used to run our facilities. These concepts and processes (where applicable) will help us gain even greater efficiencies in our existing footprint, allowing us to further maximize infrastructure investments.
Так как наши ЦОД второго поколения строились из стали и бетона, наши центры обработки данных третьего поколения начали их быстро вытеснять. Главными концептуальными особенностями ЦОД третьего поколения Gen 3 являются повышенная модульность и большее внимание к энергетической эффективности и масштабированию. Дата-центры третьего поколения лучше всего представлены объектом, который в настоящее время строится в Чикаго, Иллинойс. Этот ЦОД будет выглядеть очень необычно, по сравнению с общепринятыми в отрасли представлениями о дата-центре. Действительно, если вам когда-либо удастся побывать в нашем контейнерном ангаре в Чикаго, он покажется вам совершенно непохожим на обычный дата-центр с фальшполом. Мы предполагаем, что этот модульный подход будет способствовать значительному повышению эффективности нашего бизнеса в отношении затрат и операций. Мы также внесем существенные изменения в климатические системы, используемые в наших ЦОД. Эти концепции и технологии, если применимо, позволят нам добиться еще большей эффективности наших существующих дата-центров, и тем самым еще больше увеличивать капиталовложения в инфраструктуру.
This is definitely a journey, not a destination industry. In fact, our Generation 4 design has been under heavy engineering for viability and cost for over a year. While the demand of our commercial growth required us to make investments as we grew, we treated each step in the learning as a process for further innovation in data centers. The design for our future Gen 4 facilities enabled us to make visionary advances that addressed the challenges of building, running, and operating facilities all in one concerted effort.
Это определенно путешествие, а не конечный пункт назначения. На самом деле, наш проект ЦОД четвертого поколения подвергался серьезным испытаниям на жизнеспособность и затраты на протяжении целого года. Хотя необходимость в коммерческом росте требовала от нас постоянных капиталовложений, мы рассматривали каждый этап своего развития как шаг к будущим инновациям в области дата-центров. Проект наших будущих ЦОД четвертого поколения Gen 4 позволил нам делать фантастические предположения, которые касались задач строительства, управления и эксплуатации объектов как единого упорядоченного процесса.
Тематики
Синонимы
EN
Англо-русский словарь нормативно-технической терминологии > modular data center
-
9 flagged data
маркированные данные
Термин, применяемый для обозначения результатов измерений показателей КЭ и результатов объединения измеренных значений показателей на временных интервалах, в пределах которых имели место прерывания, провалы напряжения или перенапряжения.
В настоящем стандарте для обозначения результатов измерений показателей КЭ и результатов объединения измеренных значений в условиях воздействия прерываний, провалов напряжения и перенапряжений вместо термина "сигнализация флагами"
("flagging") в соответствии с [4] применен термин "маркирование".
Примечание. Маркирование данных позволяет принять меры, исключающие учет единственного события более чем один раз для различных показателей КЭ. Маркирование предоставляет дополнительную информацию об измерении или объединении измеренных значений показателей КЭ. Маркированные данные не подлежат удалению из состава хранимых данных. В ряде случаев маркированные данные могут не учитываться при дальнейшем анализе, в других случаях сведения о том, что данные маркированы, могут иметь большое значение. Если в стандартах, устанавливающих нормы КЭ, не изложены правила оценки маркированных данных, порядок их применения устанавливает пользователь СИ, заявитель испытаний или испытательная лаборатория.
[ ГОСТ Р 51317.4.30-2008 (МЭК 61000-4-30:2008)]EN
flagged data
data that has been marked to indicate that its measurement or its aggregation may have been affected by interruptions, dips, or swells
NOTE Flagging enables other methods that may prevent a single event from being counted as several different types of events. Flagging is supplemental information about a measurement or aggregation. Flagged data is not removed from the data set. In some applications, flagged data may be excluded from further analysis but in other applications, the fact that data was flagged may be unimportant. The user, application, regulation, or other standards determine the use of flagged data. See 4.7 for further explanation.
[IEC 61000-4-30, ed. 2.0 (2008-10)]FR
données marquées
données qui ont été marquées pour indiquer que leur mesure ou leur agrégation ont pu être affectées par des interruptions, des creux de tension ou des surtensions temporaires
NOTE Le marquage permet d’autres méthodes qui peuvent éviter qu’un événement simple ne soit compté comme différents types d’événements. Le marquage est une information supplémentaire concernant une mesure ou une agrégation. Une donnée marquée n’est pas enlevée du jeu de données. Dans certaines applications, les données marquées peuvent être exclues par une analyse plus approfondie, mais dans d’autres applications le fait que la donnée soit marquée peut être sans importance. L’utilisateur, l’application, l’autorité de régulation ou d’autres normes déterminent l’utilisation des données marquées. Voir 4.7 pour des explications complémentaires.
[IEC 61000-4-30, ed. 2.0 (2008-10)]Тематики
EN
FR
3.6 маркированные данные (flagged data): Термин, применяемый для обозначения результатов измерений показателей КЭ и результатов объединения измеренных значений показателей на временных интервалах, в пределах которых имели место прерывания, провалы напряжения или перенапряжения.
В настоящем стандарте для обозначения результатов измерений показателей КЭ и результатов объединения измеренных значений в условиях воздействия прерываний, провалов напряжения и перенапряжений вместо термина «сигнализация флагами» («flagging») в соответствии с [4] применен термин «маркирование».
Примечание - Маркирование данных позволяет принять меры, исключающие учет единственного события более чем один раз для различных показателей КЭ. Маркирование предоставляет дополнительную информацию об измерении или объединении измеренных значений показателей КЭ. Маркированные данные не подлежат удалению из состава хранимых данных. В ряде случаев маркированные данные могут не учитываться при дальнейшем анализе, в других случаях сведения о том, что данные маркированы, могут иметь большое значение. Если в стандартах, устанавливающих нормы КЭ, не изложены правила оценки маркированных данных, порядок их применения устанавливает пользователь СИ, заявитель испытаний или испытательная лаборатория.
Источник: ГОСТ Р 51317.4.30-2008: Электрическая энергия. Совместимость технических средств электромагнитная. Методы измерений показателей качества электрической энергии оригинал документа
Англо-русский словарь нормативно-технической терминологии > flagged data
-
10 authentication data
"A scheme-specific block of data that is exchanged between the server and client during authentication. To prove its identity, the client encrypts some or all of this data with a user name and password. The client sends the encrypted data to the server, which decrypts the data and compares it to the original. If the decrypted data matches the original data, the client is authenticated." -
11 in some detail
фраз. довольно подробноWe want the experimental data to be presented in some detail and discussed as thoroughly as possible. — Мы хотим, чтобы опытные данные были представлены довольно подробно и обсуждены как можно тщательнее.
Англо-русский универсальный дополнительный практический переводческий словарь И. Мостицкого > in some detail
-
12 accepting (in some contexts)
Общая лексика: лояльно (http://www.abnews.ru/type_news_full.html?t=62961&data=news)Универсальный англо-русский словарь > accepting (in some contexts)
-
13 personal data
фраз. личные данныеAnd if we could start with some personal background information …
Англо-русский универсальный дополнительный практический переводческий словарь И. Мостицкого > personal data
-
14 put\ together
1. IIIput together smth. /smth. together/ put together a dictionary (a short account of one's travels, a description of events, some data, etc.) составлять словарь и т.д.; put one's thoughts together собраться с мыслями2. IVput together smth. /smth. together/ in some manner it's easier to take a machine to pieces than to put it together again легче разобрать машину, чем снова собрать ее3. XIbe put together with smth. pieces of a broken plate (of a broken vase, etc.) were put together with glue разбитая тарелка и т.д. была склеена; some furniture is put together with glue некоторые предметы мебели ставят /сажают/ на клей4. XXI1put together smth. /smth. together/ in smth. put together a large amount of biological facts in a book собрать в книге воедино большее количество сведений /фактов/ из области биологии5. XXVIput together smth. /smth. together/ before (after..., when.., etc.) I must put my thoughts /ideas/ together before I go on to the platform я должен собраться с мыслями перед выходом на трибуну; I managed to get my facts together only after (when) he gave me additional data я смог разобраться в материале только после того, как (тогда, когда) он сообщил мне дополнительные данные -
15 effects of the electric arc inside switchgear and controlgear assemblу
- действие электрической дуги, возникающей внутри НКУ распределения и управления
действие электрической дуги, возникающей внутри НКУ распределения и управления
-
[Интент]Параллельные тексты EN-RU
Effects of the electric arc inside switchgear and controlgear assemblies
In the proximity of the main boards, i.e. in the proximity of big electrical machines, such as transformers or generators, the short-circuit power is high and consequently also the energy associated with the electrical arc due to a fault is high.
Without going into complex mathematical descriptions of this phenomenon, the first instants of arc formation inside a cubicle can be schematized in 4 phases:
1. compression phase: in this phase the volume of the air where the arc develops is overheated owing to the continuous release of energy; due to convection and radiation the remaining volume of air inside the cubicle warms up; initially there are temperature and pressure values different from one zone to another;
2. expansion phase: from the first instants of internal pressure increase a hole is formed through which the overheated air begins to go out. In this phase the pressure reaches its maximum value and starts to decrease owing to the release of hot air;
3. emission phase: in this phase, due to the continuous contribution of energy by the arc, nearly all the air is forced out under a soft and almost constant overpressure;
4. thermal phase: after the expulsion of the air, the temperature inside the switchgear reaches almost that of the electrical arc, thus beginning this final phase which lasts till the arc is quenched, when all the metals and the insulating materials coming into contact undergo erosion with production of gases, fumes and molten material particles.
Should the electrical arc occur in open configurations, some of the described phases could not be present or could have less effect; however, there shall be a pressure wave and a rise in the temperature of the zones surrounding the arc.
Being in the proximity of an electrical arc is quite dangerous; here are some data to understand how dangerous it is:
• pressure: at a distance of 60 cm from an electrical arc associated with a 20 kA arcing fault a person can be subject to a force of 225 kg; moreover, the sudden pressure wave may cause permanent injuries to the eardrum;
• arc temperatures: about 7000-8000 °C;
• sound: electrical arc sound levels can reach 160 db, a shotgun blast only 130 db.
[ABB]Действие электрической дуги, возникающей внутри НКУ распределения и управления
Короткое замыкание вблизи больших силовых устройств, таких как трансформаторы или генераторы имеет очень большую мощность. Поэтому энергия электрической дуги, возникшей в результате короткого замыкания, очень большая.
Не вдаваясь в сложное математическое описание данного явления, можно сказать, что первые мгновения формирования дуги внутри шкафа можно упрощенно разделить на четыре этапа:
1. Этап сжатия: на этом этапе объем воздуха, в котором происходит зарождение дуги перегревается вследствие непрерывного высвобождения энергии. За счет конвекции и излучения оставшийся объем воздуха внутри шкафа нагревается. На этом начальном этапе значения температуры и давления воздуха в разных зонах НКУ разные.
2. Этап расширения: с первых мгновений внутреннее давление создает канал, через который начинается движение перегретого воздуха. На этом этапе давление достигает своего максимального значения, после чего начинает уменьшаться вследствие выхода горячего воздуха.
3. Этап эмиссии: на этом этапе вследствие непрерывного пополнения энергией дуги почти весь воздух выталкивается под действием мягкого и почти постоянного избыточного давления.
4. Термический этап: после выхлопа воздуха температура внутри НКУ почти достигает температуры электрической дуги. Так начинается заключительный этап, который длится до тех пор, пока дуга не погаснет. При этом все металлические и изоляционные материалы, вступившие в контакт с дугой, оказываются подвергнутыми эрозии с выделением газов, дыма и частиц расплавленного материала.
Если электрическая дуга возникнет в открытом НКУ, то некоторые из описанных этапов могут не присутствовать или могут иметь меньшее воздействие. Тем не менее будет иметь место воздушная волна и подъем температуры вблизи дуги.
Находиться вблизи электрической дуги довольно опасно. Ниже приведены некоторые сведения, помогающие осознать эту опасность:
• давление: На расстоянии 60 см от электрической дуги, вызванной током короткого замыкания 20 кА, человек может подвергнуться воздействию силы 225 кг. Более того, резкая волна давления может нанести тяжелую травму барабанным перепонкам;
• температура дуги: около 7000-8000 °C;
• шумовое воздействие: Уровень шумового воздействия электрической дуги может достигнуть 160 дБ (выстрел из дробовика – 130 дБ).
[Перевод Интент]Тематики
- НКУ (шкафы, пульты,...)
EN
Англо-русский словарь нормативно-технической терминологии > effects of the electric arc inside switchgear and controlgear assemblу
-
16 confirm
To acknowledge an action or the value of some data (e.g. password) by definite assurance.يؤكّد -
17 date
I [deɪt]1) (fruit) dattero m.II [deɪt]1) data f.to fix o set a date fissare una data; the date for the match is... la partita avrà luogo il...; at a later date, at some future date — in data futura, più avanti
2) (meeting) appuntamento m.4) to date (fino) a oggiIII 1. [deɪt]1) (mark with date) [ person] datare [ letter]; [ machine] mettere la data su [ document]2) (identify age of) datare [ object]4) (go out with) uscire con [ person]2.1) (originate)to date from to date back to — [building, friendship] risalire a
2) (become dated) [clothes, style] passare di moda* * *I 1. [deit] noun1) ((a statement on a letter etc giving) the day of the month, the month and year: I can't read the date on this letter.)2) (the day and month and/or the year in which something happened or is going to happen: What is your date of birth?)3) (an appointment or engagement, especially a social one with a member of the opposite sex: He asked her for a date.)2. verb1) (to have or put a date on: This letter isn't dated.)2) ((with from or back) to belong to; to have been made, written etc at (a certain time): Their quarrel dates back to last year.)3) (to become obviously old-fashioned: His books haven't dated much.)•- dated- dateline
- out of date
- to date
- up to date II [deit] noun(the brown, sticky fruit of the date palm, a kind of tree growing in the tropics.)* * *date (1) /deɪt/n. (bot.)1 dattero♦ date (2) /deɪt/n.1 data: date of birth, data di nascita; DIALOGO → - Signing on with an agency- «What's your date of birth?» DIALOGO → - Signing on with an agency- «My date of birth is the 6th of March 1985», «Qual è la sua data di nascita?» «La mia data di nascita è il 6 marzo 1985»; the date of the battle of Waterloo, la data della battaglia di Waterloo; at a later date, in data posteriore; What's today's date?, quanti ne abbiamo oggi?; They're getting married next year but they haven't set ( o fixed) a date, si sposano l'anno prossimo ma non hanno stabilito una data2 tempo; periodo: at that date, a quel tempo; at a later date, successivamente; at an earlier date, precedentemente; at some future date, in seguito4 (fam.) appuntamento (spec. amoroso): He'll never pluck up the courage to ask her for a date, non troverà mai il coraggio per chiederle di uscire con lui; to go ( out) on a date ( with sb.), avere un appuntamento romantico (con q.); to go on a date, avere un appuntamento (amoroso); to have a dinner date, avere un invito per un pranzo a due; We made a date to have lunch, abbiamo combinato per pranzare insieme; We didn't even kiss on our first date, non ci siamo nemmeno baciati al nostro primo appuntamento NOTA D'USO: - appuntamento e appointment-5 (fam.) persona con cui si ha un appuntamento (o con cui si esce): She arrived in time, but her date was late, è arrivata in orario, ma il tipo con cui doveva uscire era in ritardo● date as postmark, data del timbro postale □ (fin., leg.) date certain, data certa □ date coding, annotazione in codice della data di scadenza ( di un prodotto confezionato) □ date-line, (geogr.) linea del cambiamento di data; ( nei giornali) riga che porta la data di un articolo □ (comm.) date of maturity, data di scadenza ( di una cambiale) □ date rape, «stupro su appuntamento» ( commesso nel corso di un appuntamento) □ date schedule, calendario delle scadenze □ date stamp, datario ( timbro della data) □ to go out of date, cadere in disuso; diventare obsoleto □ to be out of date, essere in disuso; essere antiquato □ to date, fino a oggi; sinora.(to) date /deɪt/A v. t.1 datare ( una lettera, un documento, ecc.): The letter was dated 19th August, la lettera era datata 19 agosto; Don't forget to date the cheque, non dimenticarti di datare l'assegno2 datare ( una scoperta archeologica, ecc.) fissare la data di ( un evento): Archaeologists have not yet been able to date the statue, gli archeologi non sono ancora riusciti a datare la statua3 (fam.) stare insieme a, uscire con (q.): All the girls he dates are older than him, tutte le ragazze con cui esce sono più vecchie di lui4 essere indicativo dell'età (di q.): I can remember the Beatles, I suppose that dates me, mi ricordo dei Beatles, presumo che questo sia indicativo della mia etàB v. i.1 – to date from (o back to) risalire a: This church dates from the 14th century, questa chiesa risale al Trecento; The furniture dates back to the 1700s, il mobilio risale al Settecento2 apparire superato: Some fashions date really fast, alcune mode appaiono superate molto in fretta; Many 60s buildings have dated badly, molti edifici degli anni '60 hanno un aspetto completamente superato3 (fam., anche to date each other) uscire (o stare) insieme ( di coppia): They've been dating for six months, stanno insieme da sei mesi; She didn't feel ready to date again, non si sentiva pronta a uscire di nuovo con un uomo● dating from, a datare (o partire) da.* * *I [deɪt]1) (fruit) dattero m.II [deɪt]1) data f.to fix o set a date fissare una data; the date for the match is... la partita avrà luogo il...; at a later date, at some future date — in data futura, più avanti
2) (meeting) appuntamento m.4) to date (fino) a oggiIII 1. [deɪt]1) (mark with date) [ person] datare [ letter]; [ machine] mettere la data su [ document]2) (identify age of) datare [ object]4) (go out with) uscire con [ person]2.1) (originate)to date from to date back to — [building, friendship] risalire a
2) (become dated) [clothes, style] passare di moda -
18 BIOS
['baios] n. shkurtesë nga b asic i nput o utput s ystem ( BIOS) sistemi themelor për hyrje-dalje ( informatikë)What is BIOS?BIOS is an acronym for Basic Input/Output System. It is the boot firmware program on a PC, and controls the computer from the time you start it up until the operating system takes over. When you turn on a PC, the BIOS first conducts a basic hardware check, called a Power-On Self Test (POST), to determine whether all of the attachments are present and working. Then it loads the operating system into your computer's random access memory, or RAM.The BIOS also manages data flow between the computer's operating system and attached devices such as the hard disk, video card, keyboard, mouse, and printer.The BIOS stores the date, the time, and your system configuration information in a battery-powered, non-volatile memory chip, called a CMOS (Complementary Metal Oxide Semiconductor) after its manufacturing process.Although the BIOS is standardized and should rarely require updating, some older BIOS chips may not accommodate new hardware devices. Before the early 1990s, you couldn't update the BIOS without removing and replacing its ROM chip. Contemporary BIOS resides on memory chips such as flash chips or EEPROM (Electrically Erasable Programmable Read-Only Memory), so that you can update the BIOS yourself if necessary.For detailed information about BIOS updates, visit:What is firmware?Firmware consists of programs installed semi-permanently into memory, using various types of programmable ROM chips, such as PROMS, EPROMs, EEPROMs, and flash chips.Firmware is non-volatile, and will remain in memory after you turn the system off.Often, the term firmware is used to refer specifically to boot firmware, which controls a computer from the time that it is turned on until the primary operating system has taken over. Boot firmware's main function is to initialize the hardware and then to boot (load and execute) the primary operating system. On PCs, the boot firmware is usually referred to as the BIOS.What is the difference between memory and disk storage?Memory and disk storage both refer to internal storage space in a computer.The term memory usually means RAM (Random Access Memory). To refer to hard drive storage, the terms disk space or storage are usually used.Typically, computers have much less memory than disk space, because RAM is much more expensive per megabyte than a hard disk. Today, a typical desktop computer might come with 512MB of RAM, and a 40 gigabyte hard disk.Virtual memory is disk space that has been designated to act like RAM.Computers also contain a small amount of ROM, or read-only memory, containing permanent or semi-permanent (firmware) instructions for checking hardware and starting up the computer. On a PC, this is called the BIOS.What is RAM?RAM stands for Random Access Memory. RAM provides space for your computer to read and write data to be accessed by the CPU (central processing unit). When people refer to a computer's memory, they usually mean its RAM.New computers typically come with at least 256 megabytes (MB) of RAM installed, and can be upgraded to 512MB or even a gigabyte or more.If you add more RAM to your computer, you reduce the number of times your CPU must read data from your hard disk. This usually allows your computer to work considerably faster, as RAM is many times faster than a hard disk.RAM is volatile, so data stored in RAM stays there only as long as your computer is running. As soon as you turn the computer off, the data stored in RAM disappears.When you turn your computer on again, your computer's boot firmware (called BIOS on a PC) uses instructions stored semi-permanently in ROM chips to read your operating system and related files from the disk and load them back into RAM.Note: On a PC, different parts of RAM may be more or less easily accessible to programs. For example, cache RAM is made up of very high-speed RAM chips which sit between the CPU and main RAM, storing (i.e., caching) memory accesses by the CPU. Cache RAM helps to alleviate the gap between the speed of a CPU's megahertz rating and the ability of RAM to respond and deliver data. It reduces how often the CPU must wait for data from main memory.What is ROM?ROM is an acronym for Read-Only Memory. It refers to computer memory chips containing permanent or semi-permanent data. Unlike RAM, ROM is non-volatile; even after you turn off your computer, the contents of ROM will remain.Almost every computer comes with a small amount of ROM containing the boot firmware. This consists of a few kilobytes of code that tell the computer what to do when it starts up, e.g., running hardware diagnostics and loading the operating system into RAM. On a PC, the boot firmware is called the BIOS.Originally, ROM was actually read-only. To update the programs in ROM, you had to remove and physically replace your ROM chips. Contemporary versions of ROM allow some limited rewriting, so you can usually upgrade firmware such as the BIOS by using installation software. Rewritable ROM chips include PROMs (programmable read-only memory), EPROMs (erasable read-only memory), EEPROMs (electrically erasable programmable read-only memory), and a common variation of EEPROMs called flash memory.What is an ACPI BIOS?ACPI is an acronym that stands for Advanced Configuration and Power Interface, a power management specification developed by Intel, Microsoft, and Toshiba. ACPI support is built into Windows 98 and later operating systems. ACPI is designed to allow the operating system to control the amount of power provided to each device or peripheral attached to the computer system. This provides much more stable and efficient power management and makes it possible for the operating system to turn off selected devices, such as a monitor or CD-ROM drive, when they are not in use.ACPI should help eliminate computer lockup on entering power saving or sleep mode. This will allow for improved power management, especially in portable computer systems where reducing power consumption is critical for extending battery life. ACPI also allows for the computer to be turned on and off by external devices, so that the touch of a mouse or the press of a key will "wake up" the computer. This new feature of ACPI, called OnNow, allows a computer to enter a sleep mode that uses very little power.In addition to providing power management, ACPI also evolves the existing Plug and Play BIOS (PnP BIOS) to make adding and configuring new hardware devices easier. This includes support for legacy non-PnP devices and improved support for combining older devices with ACPI hardware, allowing both to work in a more efficient manner in the same computer system. The end result of this is to make the BIOS more PnP compatible.What is CMOS?CMOS, short for Complementary Metal Oxide Semiconductor, is a low-power, low-heat semiconductor technology used in contemporary microchips, especially useful for battery-powered devices. The specific technology is explained in detail at:http://searchsmb.techtarget.com/sDefinition/0,,sid44_gci213860,00.htmlMost commonly, though, the term CMOS is used to refer to small battery-powered configuration chips on system boards of personal computers, where the BIOS stores the date, the time, and system configuration details.How do I enter the Setup program in my BIOS?Warning: Your BIOS Setup program is very powerful. An incorrect setting could cause your computer not to boot properly. You should make sure you understand what a setting does before you change it.You can usually run Setup by pressing a special function key or key combination soon after turning on the computer, during its power-on self test (POST), before the operating system loads (or before the operating system's splash screen shows). During POST, the BIOS usually displays a prompt such as:Press F2 to enter SetupMany newer computers display a brief screen, usually black and white, with the computer manufacturer's logo during POST.Entering the designated keystroke will take you into the BIOS Setup. Common keystrokes to enter the BIOS Setup are F1, F2, F10, and Del.On some computers, such as some Gateway or Compaq computers, graphics appear during the POST, and the BIOS information is hidden. You must press Esc to make these graphics disappear. Your monitor will then display the correct keystroke to enter.Note: If you press the key too early or too often, the BIOS may display an error message. To avoid this, wait about five seconds after turning the power on, and then press the key once or twice.What's the difference between BIOS and CMOS?Many people use the terms BIOS (basic input/output system) and CMOS (complementary metal oxide semiconductor) to refer to the same thing. Though they are related, they are distinct and separate components of a computer. The BIOS is the program that starts a computer up, and the CMOS is where the BIOS stores the date, time, and system configuration details it needs to start the computer.The BIOS is a small program that controls the computer from the time it powers on until the time the operating system takes over. The BIOS is firmware, which means it cannot store variable data.CMOS is a type of memory technology, but most people use the term to refer to the chip that stores variable data for startup. A computer's BIOS will initialize and control components like the floppy and hard drive controllers and the computer's hardware clock, but the specific parameters for startup and initializing components are stored in the CMOS. -
19 Artificial Intelligence
In my opinion, none of [these programs] does even remote justice to the complexity of human mental processes. Unlike men, "artificially intelligent" programs tend to be single minded, undistractable, and unemotional. (Neisser, 1967, p. 9)Future progress in [artificial intelligence] will depend on the development of both practical and theoretical knowledge.... As regards theoretical knowledge, some have sought a unified theory of artificial intelligence. My view is that artificial intelligence is (or soon will be) an engineering discipline since its primary goal is to build things. (Nilsson, 1971, pp. vii-viii)Most workers in AI [artificial intelligence] research and in related fields confess to a pronounced feeling of disappointment in what has been achieved in the last 25 years. Workers entered the field around 1950, and even around 1960, with high hopes that are very far from being realized in 1972. In no part of the field have the discoveries made so far produced the major impact that was then promised.... In the meantime, claims and predictions regarding the potential results of AI research had been publicized which went even farther than the expectations of the majority of workers in the field, whose embarrassments have been added to by the lamentable failure of such inflated predictions....When able and respected scientists write in letters to the present author that AI, the major goal of computing science, represents "another step in the general process of evolution"; that possibilities in the 1980s include an all-purpose intelligence on a human-scale knowledge base; that awe-inspiring possibilities suggest themselves based on machine intelligence exceeding human intelligence by the year 2000 [one has the right to be skeptical]. (Lighthill, 1972, p. 17)4) Just as Astronomy Succeeded Astrology, the Discovery of Intellectual Processes in Machines Should Lead to a Science, EventuallyJust as astronomy succeeded astrology, following Kepler's discovery of planetary regularities, the discoveries of these many principles in empirical explorations on intellectual processes in machines should lead to a science, eventually. (Minsky & Papert, 1973, p. 11)5) Problems in Machine Intelligence Arise Because Things Obvious to Any Person Are Not Represented in the ProgramMany problems arise in experiments on machine intelligence because things obvious to any person are not represented in any program. One can pull with a string, but one cannot push with one.... Simple facts like these caused serious problems when Charniak attempted to extend Bobrow's "Student" program to more realistic applications, and they have not been faced up to until now. (Minsky & Papert, 1973, p. 77)What do we mean by [a symbolic] "description"? We do not mean to suggest that our descriptions must be made of strings of ordinary language words (although they might be). The simplest kind of description is a structure in which some features of a situation are represented by single ("primitive") symbols, and relations between those features are represented by other symbols-or by other features of the way the description is put together. (Minsky & Papert, 1973, p. 11)[AI is] the use of computer programs and programming techniques to cast light on the principles of intelligence in general and human thought in particular. (Boden, 1977, p. 5)The word you look for and hardly ever see in the early AI literature is the word knowledge. They didn't believe you have to know anything, you could always rework it all.... In fact 1967 is the turning point in my mind when there was enough feeling that the old ideas of general principles had to go.... I came up with an argument for what I called the primacy of expertise, and at the time I called the other guys the generalists. (Moses, quoted in McCorduck, 1979, pp. 228-229)9) Artificial Intelligence Is Psychology in a Particularly Pure and Abstract FormThe basic idea of cognitive science is that intelligent beings are semantic engines-in other words, automatic formal systems with interpretations under which they consistently make sense. We can now see why this includes psychology and artificial intelligence on a more or less equal footing: people and intelligent computers (if and when there are any) turn out to be merely different manifestations of the same underlying phenomenon. Moreover, with universal hardware, any semantic engine can in principle be formally imitated by a computer if only the right program can be found. And that will guarantee semantic imitation as well, since (given the appropriate formal behavior) the semantics is "taking care of itself" anyway. Thus we also see why, from this perspective, artificial intelligence can be regarded as psychology in a particularly pure and abstract form. The same fundamental structures are under investigation, but in AI, all the relevant parameters are under direct experimental control (in the programming), without any messy physiology or ethics to get in the way. (Haugeland, 1981b, p. 31)There are many different kinds of reasoning one might imagine:Formal reasoning involves the syntactic manipulation of data structures to deduce new ones following prespecified rules of inference. Mathematical logic is the archetypical formal representation. Procedural reasoning uses simulation to answer questions and solve problems. When we use a program to answer What is the sum of 3 and 4? it uses, or "runs," a procedural model of arithmetic. Reasoning by analogy seems to be a very natural mode of thought for humans but, so far, difficult to accomplish in AI programs. The idea is that when you ask the question Can robins fly? the system might reason that "robins are like sparrows, and I know that sparrows can fly, so robins probably can fly."Generalization and abstraction are also natural reasoning process for humans that are difficult to pin down well enough to implement in a program. If one knows that Robins have wings, that Sparrows have wings, and that Blue jays have wings, eventually one will believe that All birds have wings. This capability may be at the core of most human learning, but it has not yet become a useful technique in AI.... Meta- level reasoning is demonstrated by the way one answers the question What is Paul Newman's telephone number? You might reason that "if I knew Paul Newman's number, I would know that I knew it, because it is a notable fact." This involves using "knowledge about what you know," in particular, about the extent of your knowledge and about the importance of certain facts. Recent research in psychology and AI indicates that meta-level reasoning may play a central role in human cognitive processing. (Barr & Feigenbaum, 1981, pp. 146-147)Suffice it to say that programs already exist that can do things-or, at the very least, appear to be beginning to do things-which ill-informed critics have asserted a priori to be impossible. Examples include: perceiving in a holistic as opposed to an atomistic way; using language creatively; translating sensibly from one language to another by way of a language-neutral semantic representation; planning acts in a broad and sketchy fashion, the details being decided only in execution; distinguishing between different species of emotional reaction according to the psychological context of the subject. (Boden, 1981, p. 33)Can the synthesis of Man and Machine ever be stable, or will the purely organic component become such a hindrance that it has to be discarded? If this eventually happens-and I have... good reasons for thinking that it must-we have nothing to regret and certainly nothing to fear. (Clarke, 1984, p. 243)The thesis of GOFAI... is not that the processes underlying intelligence can be described symbolically... but that they are symbolic. (Haugeland, 1985, p. 113)14) Artificial Intelligence Provides a Useful Approach to Psychological and Psychiatric Theory FormationIt is all very well formulating psychological and psychiatric theories verbally but, when using natural language (even technical jargon), it is difficult to recognise when a theory is complete; oversights are all too easily made, gaps too readily left. This is a point which is generally recognised to be true and it is for precisely this reason that the behavioural sciences attempt to follow the natural sciences in using "classical" mathematics as a more rigorous descriptive language. However, it is an unfortunate fact that, with a few notable exceptions, there has been a marked lack of success in this application. It is my belief that a different approach-a different mathematics-is needed, and that AI provides just this approach. (Hand, quoted in Hand, 1985, pp. 6-7)We might distinguish among four kinds of AI.Research of this kind involves building and programming computers to perform tasks which, to paraphrase Marvin Minsky, would require intelligence if they were done by us. Researchers in nonpsychological AI make no claims whatsoever about the psychological realism of their programs or the devices they build, that is, about whether or not computers perform tasks as humans do.Research here is guided by the view that the computer is a useful tool in the study of mind. In particular, we can write computer programs or build devices that simulate alleged psychological processes in humans and then test our predictions about how the alleged processes work. We can weave these programs and devices together with other programs and devices that simulate different alleged mental processes and thereby test the degree to which the AI system as a whole simulates human mentality. According to weak psychological AI, working with computer models is a way of refining and testing hypotheses about processes that are allegedly realized in human minds.... According to this view, our minds are computers and therefore can be duplicated by other computers. Sherry Turkle writes that the "real ambition is of mythic proportions, making a general purpose intelligence, a mind." (Turkle, 1984, p. 240) The authors of a major text announce that "the ultimate goal of AI research is to build a person or, more humbly, an animal." (Charniak & McDermott, 1985, p. 7)Research in this field, like strong psychological AI, takes seriously the functionalist view that mentality can be realized in many different types of physical devices. Suprapsychological AI, however, accuses strong psychological AI of being chauvinisticof being only interested in human intelligence! Suprapsychological AI claims to be interested in all the conceivable ways intelligence can be realized. (Flanagan, 1991, pp. 241-242)16) Determination of Relevance of Rules in Particular ContextsEven if the [rules] were stored in a context-free form the computer still couldn't use them. To do that the computer requires rules enabling it to draw on just those [ rules] which are relevant in each particular context. Determination of relevance will have to be based on further facts and rules, but the question will again arise as to which facts and rules are relevant for making each particular determination. One could always invoke further facts and rules to answer this question, but of course these must be only the relevant ones. And so it goes. It seems that AI workers will never be able to get started here unless they can settle the problem of relevance beforehand by cataloguing types of context and listing just those facts which are relevant in each. (Dreyfus & Dreyfus, 1986, p. 80)Perhaps the single most important idea to artificial intelligence is that there is no fundamental difference between form and content, that meaning can be captured in a set of symbols such as a semantic net. (G. Johnson, 1986, p. 250)Artificial intelligence is based on the assumption that the mind can be described as some kind of formal system manipulating symbols that stand for things in the world. Thus it doesn't matter what the brain is made of, or what it uses for tokens in the great game of thinking. Using an equivalent set of tokens and rules, we can do thinking with a digital computer, just as we can play chess using cups, salt and pepper shakers, knives, forks, and spoons. Using the right software, one system (the mind) can be mapped into the other (the computer). (G. Johnson, 1986, p. 250)19) A Statement of the Primary and Secondary Purposes of Artificial IntelligenceThe primary goal of Artificial Intelligence is to make machines smarter.The secondary goals of Artificial Intelligence are to understand what intelligence is (the Nobel laureate purpose) and to make machines more useful (the entrepreneurial purpose). (Winston, 1987, p. 1)The theoretical ideas of older branches of engineering are captured in the language of mathematics. We contend that mathematical logic provides the basis for theory in AI. Although many computer scientists already count logic as fundamental to computer science in general, we put forward an even stronger form of the logic-is-important argument....AI deals mainly with the problem of representing and using declarative (as opposed to procedural) knowledge. Declarative knowledge is the kind that is expressed as sentences, and AI needs a language in which to state these sentences. Because the languages in which this knowledge usually is originally captured (natural languages such as English) are not suitable for computer representations, some other language with the appropriate properties must be used. It turns out, we think, that the appropriate properties include at least those that have been uppermost in the minds of logicians in their development of logical languages such as the predicate calculus. Thus, we think that any language for expressing knowledge in AI systems must be at least as expressive as the first-order predicate calculus. (Genesereth & Nilsson, 1987, p. viii)21) Perceptual Structures Can Be Represented as Lists of Elementary PropositionsIn artificial intelligence studies, perceptual structures are represented as assemblages of description lists, the elementary components of which are propositions asserting that certain relations hold among elements. (Chase & Simon, 1988, p. 490)Artificial intelligence (AI) is sometimes defined as the study of how to build and/or program computers to enable them to do the sorts of things that minds can do. Some of these things are commonly regarded as requiring intelligence: offering a medical diagnosis and/or prescription, giving legal or scientific advice, proving theorems in logic or mathematics. Others are not, because they can be done by all normal adults irrespective of educational background (and sometimes by non-human animals too), and typically involve no conscious control: seeing things in sunlight and shadows, finding a path through cluttered terrain, fitting pegs into holes, speaking one's own native tongue, and using one's common sense. Because it covers AI research dealing with both these classes of mental capacity, this definition is preferable to one describing AI as making computers do "things that would require intelligence if done by people." However, it presupposes that computers could do what minds can do, that they might really diagnose, advise, infer, and understand. One could avoid this problematic assumption (and also side-step questions about whether computers do things in the same way as we do) by defining AI instead as "the development of computers whose observable performance has features which in humans we would attribute to mental processes." This bland characterization would be acceptable to some AI workers, especially amongst those focusing on the production of technological tools for commercial purposes. But many others would favour a more controversial definition, seeing AI as the science of intelligence in general-or, more accurately, as the intellectual core of cognitive science. As such, its goal is to provide a systematic theory that can explain (and perhaps enable us to replicate) both the general categories of intentionality and the diverse psychological capacities grounded in them. (Boden, 1990b, pp. 1-2)Because the ability to store data somewhat corresponds to what we call memory in human beings, and because the ability to follow logical procedures somewhat corresponds to what we call reasoning in human beings, many members of the cult have concluded that what computers do somewhat corresponds to what we call thinking. It is no great difficulty to persuade the general public of that conclusion since computers process data very fast in small spaces well below the level of visibility; they do not look like other machines when they are at work. They seem to be running along as smoothly and silently as the brain does when it remembers and reasons and thinks. On the other hand, those who design and build computers know exactly how the machines are working down in the hidden depths of their semiconductors. Computers can be taken apart, scrutinized, and put back together. Their activities can be tracked, analyzed, measured, and thus clearly understood-which is far from possible with the brain. This gives rise to the tempting assumption on the part of the builders and designers that computers can tell us something about brains, indeed, that the computer can serve as a model of the mind, which then comes to be seen as some manner of information processing machine, and possibly not as good at the job as the machine. (Roszak, 1994, pp. xiv-xv)The inner workings of the human mind are far more intricate than the most complicated systems of modern technology. Researchers in the field of artificial intelligence have been attempting to develop programs that will enable computers to display intelligent behavior. Although this field has been an active one for more than thirty-five years and has had many notable successes, AI researchers still do not know how to create a program that matches human intelligence. No existing program can recall facts, solve problems, reason, learn, and process language with human facility. This lack of success has occurred not because computers are inferior to human brains but rather because we do not yet know in sufficient detail how intelligence is organized in the brain. (Anderson, 1995, p. 2)Historical dictionary of quotations in cognitive science > Artificial Intelligence
-
20 Psychoanalysis
[Psychoanalysis] seeks to prove to the ego that it is not even master in its own house, but must content itself with scanty information of what is going on unconsciously in the mind. (Freud, 1953-1974, Vol. 16, pp. 284-285)Although in the interview the analyst is supposedly a "passive" auditor of the "free association" narration by the subject, in point of fact the analyst does direct the course of the narrative. This by itself does not necessarily impair the evidential worth of the outcome, for even in the most meticulously conducted laboratory experiment the experimenter intervenes to obtain the data he is after. There is nevertheless the difficulty that in the nature of the case the full extent of the analyst's intervention is not a matter that is open to public scrutiny, so that by and large one has only his own testimony as to what transpires in the consulting room. It is perhaps unnecessary to say that this is not a question about the personal integrity of psychoanalytic practitioners. The point is the fundamental one that no matter how firmly we may resolve to make explicit our biases, no human being is aware of all of them, and that objectivity in science is achieved through the criticism of publicly accessible material by a community of independent inquirers.... Moreover, unless data are obtained under carefully standardized circumstances, or under different circumstances whose dependence on known variables is nevertheless established, even an extensive collection of data is an unreliable basis for inference. To be sure, analysts apparently do attempt to institute standard conditions for the conduct of interviews. But there is not much information available on the extent to which the standardization is actually enforced, or whether it relates to more than what may be superficial matters. (E. Nagel, 1959, pp. 49-50)3) No Necessary Incompatibility between Psychoanalysis and Certain Religious Formulationshere would seem to be no necessary incompatibility between psychoanalysis and those religious formulations which locate God within the self. One could, indeed, argue that Freud's Id (and even more Groddeck's It), the impersonal force within which is both the core of oneself and yet not oneself, and from which in illness one become[s] alienated, is a secular formation of the insight which makes religious people believe in an immanent God. (Ryecroft, 1966, p. 22)Freudian analysts emphasized that their theories were constantly verified by their "clinical observations."... It was precisely this fact-that they always fitted, that they were always confirmed-which in the eyes of their admirers constituted the strongest argument in favour of these theories. It began to dawn on me that this apparent strength was in fact their weakness.... It is easy to obtain confirmations or verifications, for nearly every theory-if we look for confirmation. (Popper, 1968, pp. 3435)5) Psychoanalysis Is Not a Science But Rather the Interpretation of a Narrated HistoryPsychoanalysis does not satisfy the standards of the sciences of observation, and the "facts" it deals with are not verifiable by multiple, independent observers.... There are no "facts" nor any observation of "facts" in psychoanalysis but rather the interpretation of a narrated history. (Ricoeur, 1974, p. 186)6) Some of the Qualities of a Scientific Approach Are Possessed by PsychoanalysisIn sum: psychoanalysis is not a science, but it shares some of the qualities associated with a scientific approach-the search for truth, understanding, honesty, openness to the import of the observation and evidence, and a skeptical stance toward authority. (Breger, 1981, p. 50)[Attributes of Psychoanalysis:]1. Psychic Determinism. No item in mental life and in conduct and behavior is "accidental"; it is the outcome of antecedent conditions.2. Much mental activity and behavior is purposive or goal-directed in character.3. Much of mental activity and behavior, and its determinants, is unconscious in character. 4. The early experience of the individual, as a child, is very potent, and tends to be pre-potent over later experience. (Farrell, 1981, p. 25)Our sceptic may be unwise enough... to maintain that, because analytic theory is unscientific on his criterion, it is not worth discussing. This step is unwise, because it presupposes that, if a study is not scientific on his criterion, it is not a rational enterprise... an elementary and egregious mistake. The scientific and the rational are not co-extensive. Scientific work is only one form that rational inquiry can take: there are many others. (Farrell, 1981, p. 46)Psychoanalysts have tended to write as though the term analysis spoke for itself, as if the statement "analysis revealed" or "it was analyzed as" preceding a clinical assertion was sufficient to establish the validity of what was being reported. An outsider might easily get the impression from reading the psychoanalytic literature that some standardized, generally accepted procedure existed for both inference and evidence. Instead, exactly the opposite has been true. Clinical material in the hands of one analyst can lead to totally different "findings" in the hands of another. (Peterfreund, 1986, p. 128)The analytic process-the means by which we arrive at psychoanalytic understanding-has been largely neglected and is poorly understood, and there has been comparatively little interest in the issues of inference and evidence. Indeed, psychoanalysts as a group have not recognized the importance of being bound by scientific constraints. They do not seem to understand that a possibility is only that-a possibility-and that innumerable ways may exist to explain the same data. Psychoanalysts all too often do not seem to distinguish hypotheses from facts, nor do they seem to understand that hypotheses must be tested in some way, that criteria for evidence must exist, and that any given test for any hypothesis must allow for the full range of substantiation/refutation. (Peterfreund, 1986, p. 129)Historical dictionary of quotations in cognitive science > Psychoanalysis
См. также в других словарях:
Data logger — Cube storing technical and sensor data A data logger (also datalogger or data recorder) is an electronic device that records data over time or in relation to location either with a built in instrument or sensor or via external instruments and… … Wikipedia
Data recovery — is the process of salvaging data from damaged, failed, corrupted, or inaccessible secondary storage media when it cannot be accessed normally. Often the data are being salvaged from storage media such as internal or external hard disk drives,… … Wikipedia
Data erasure — (also called data clearing or data wiping) is a software based method of overwriting data that completely destroys all electronic data residing on a hard disk drive or other digital media. Permanent data erasure goes beyond basic file deletion… … Wikipedia
Data parallelism — (also known as loop level parallelism) is a form of parallelization of computing across multiple processors in parallel computing environments. Data parallelism focuses on distributing the data across different parallel computing nodes. It… … Wikipedia
Data-flow analysis — is a technique for gathering information about the possible set of values calculated at various points in a computer program. A program s control flow graph (CFG) is used to determine those parts of a program to which a particular value assigned… … Wikipedia
Data independence — is the type of data transparency that matters for a centralized DBMS. It refers to the immunity of user applications to make changes in the definition and organization of data. Physical data independence deals with hiding the details of the… … Wikipedia
Data link layer — The OSI model 7 Application layer 6 Presentation layer 5 Session layer 4 Transport layer 3 Network layer 2 … Wikipedia
Data Link Layer — The Data Link Layer is Layer 2 of the seven layer OSI model. It responds to service requests from the Network Layer and issues service requests to the Physical Layer.The Data Link Layer is the protocol layer which transfers data between adjacent… … Wikipedia
Data monitoring switch — A data monitoring switch is a networking hardware appliance that provides a pool of monitoring tools with access to traffic from a large number of network links. It provides a combination of functionality that may include aggregating monitoring… … Wikipedia
Data-structured language — In computing a data structured language is a programming language in which the data structure is a main organizing principle, representation, model, for data and logic (code) alike, in which both are stored and operated upon, i.e., program data… … Wikipedia
Data mining in meteorology — Meteorology is the interdisciplinary scientific study of the atmosphere. It observes the changes in temperature, air pressure, moisture and wind direction. Usually, temperature, pressure, wind measurements and humidity are the variables that are… … Wikipedia