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000-084 System x lofty Performance Servers Technical support V3

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000-084 exam Dumps Source : System x lofty Performance Servers Technical support V3

Test Code : 000-084
Test cognomen : System x lofty Performance Servers Technical support V3
Vendor cognomen : IBM
: 41 true Questions

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IBM System x lofty Performance

IBM researchers foster a pair of low-energy, high-performance desktop imaginative and prescient techniques | killexams.com true Questions and Pass4sure dumps

laptop studying algorithms acquire greater by using leaps and bounds in simultaneous years. State-of-the-paintings programs like facebook’s, for example, can instruct photograph classification algorithms in an hour with out sacrificing accuracy. but a lot of them are informed on excessive-conclusion machines with potent GPUs, and because the information superhighway of things (IoT) industry strikes toward side computing, there’s growing claim for low-vigour synthetic intelligence (AI) fashions with low overhead.

Promising analysis out of IBM lays the foundation for tons extra productive algorithms. on the 2018 convention on laptop vision and sample awareness in Salt Lake city, Utah this week, analysis scientists from the industry are proposing two papers that snitch care of photograph classification.

BlockDrop

the first, titled “BlockDrop: Dynamic Interference Paths in Residual Networks,” builds on Microsoft’s toil on residual networks that was posted in 2015. Residual networks (ResNets for short) introduce id connections between the layers within the neural network, permitting them to study incremental, or residual, representations for the duration of working towards.

IBM BlockDrop

IBM takes this conception one step extra. Scientists brought a lightweight secondary neural community — observed within the paper as a “coverage community” — that dynamically dropped residual blocks in a pre-proficient ResNet. To acquire certain the efficiency positive aspects didn’t gain at the suffuse of precision, the policy network changed into knowledgeable to consume a minimal number of blocks and to retain recognition accuracy.

“frequently speaking, in case you add extra layers to a mannequin, which you can enrich its accuracy, but you raise the computational charge,” IBM research supervisor Rogerio Feris instructed VentureBeat in a phone interview. “One theme with most current models nowadays is that you've got one-dimension-suits-all networks where the identical computation is applied to every unique photos. [Our] outfit allocates supplies more efficaciously and [can] precisely identify a picture.”

BlockDrop accelerated image classification by using 20 p.c on average, and through as a total lot as 36 percent in certain cases, every unique whereas conserving 76.four p.c accuracy — the equal as the scan’s handle.

improving stereo vision

The 2nd paper, “A Low vigour, lofty Throughput, full event-primarily based Stereo gadget,” tackled an additional vicissitude in realistic processing: stereo imaginative and prescient.

IBM Stereo

As IBM researcher Alexander Andreopoulos defined, human eyes are centimeters other than each and every different and notice the world from a bit of distinctive views. The brain’s visible cortex seamlessly merges images from each eyes into one, permitting us to understand depth, but two-digital camera robotics programs acquire a more difficult time reconciling the disparity.

“within the case of computing device imaginative and prescient, digicam lenses acquire abnormalities, and this ends up in uproar and complicates the problem,” Andreopoulos observed.

The researcher’s solution: a system running on IBM’s TrueNorth neuromorphic chips, which acquire a incredibly parallelized architecture optimized for machine researching fashions. the usage of a cluster of nine processors, a pair of event-based mostly cameras (cameras that most effectual snap a picture once they become cognizant of motion), and a laptop that distributed computations to the aforementioned chips, the algorithms captured and processed four hundred (up to a maximum of two,000) disparity maps per 2d.

using adventure-primarily based cameras enormously carve down on bandwidth and power utilization, Andreopoulos defined. “Stereo algorithms had been round for over 30 years, however most of these techniques … consume an lively approach to sensing the area. Ours uses a passive method.”

IBM Research

Above: Depth assistance of scene mapped with the aid of IBM’s device.

picture credit score: IBM

general, the outfit demonstrated a 200 times progress in terms of vitality per pixel per disparity map compared to state-of-the-artwork programs with lofty framerate cameras.

The consequences hang engage for robotics programs that depend on low-energy, low-latency depth guidance to navigate the area, Andreopoulos noted. “[I imagine] it getting used in colleague robots for the elderly … [that] present some shape of mobility suggestions.”


IBM Bets $2B looking for 1000X AI Hardware performance enhance | killexams.com true Questions and Pass4sure dumps

For now, AI techniques are in generic machine learning-based and “slim” – potent as they are by means of these days’s requirements, they’re restrained to performing just a few, narrowly-described tasks. AI of the next decade will leverage the improved vitality of abysmal gaining knowledge of and become broader, solving a improved array of extra tangled issues. additionally, the typical-goal applied sciences used nowadays for AI deployments will live replaced by passage of a expertise stack that’s AI-certain and exponentially faster – and it’s going to snitch a lot of money.

IBM’s Mukesh Khare

in the hunt for to snitch center stage in AI’s unfolding, IBM – in aggregate with commodious apple status and a number of expertise heavies – is investing $2 billion in the IBM analysis AI Hardware center, focused on establishing next technology AI silicon, networking and manufacturing for you to, IBM noted, convey 1,000x AI performance efficiency growth over the next decade.

“nowadays, AI’s ever-expanding sophistication is pushing the boundaries of the trade’s current hardware programs as users find extra methods to comprise a variety of sources of data from the area, web of issues, and more,” brought up Mukesh Khare, VP, IBM analysis Semiconductor and AI Hardware group, in a weblog announcing the mission. “…these days’s programs acquire carried out superior AI efficiency via infusing laptop-gaining knowledge of capabilities with excessive-bandwidth CPUs and GPUs, really splendid AI accelerators and excessive-performance networking gadget. To retain this trajectory, unusual thinking is needed to accelerate AI performance scaling to wholesome to ever-increasing AI workload complexities.”

IBM roadmap for 1,000x growth in AI compute efficiency efficiency.

IBM mentioned the core can live the nucleus of a brand unusual ecosystem of research and industrial partners participating with IBM researchers. partners introduced today consist of Samsung for manufacturing and analysis, Mellanox applied sciences for prime-efficiency interconnect machine, Synopsys for utility platforms, emulation and prototyping, and IP for developing high-performance silicon chips, and semiconductor outfit groups applied substances and Tokyo Electron.

Hosted at SUNY Polytechnic Institute, Albany, the commodious apple, in collaboration with neighboring Rensselaer Polytechnic Institute center for Computational innovations, IBM mentioned the industry and its companions will “improve various applied sciences from chip degree gadgets, materials, and architecture, to the utility supporting AI workloads.”

massive Blue observed analysis at the core will focal point on overcoming existing laptop-studying boundaries through methods that consist of approximate computing via Digital AI Cores and in-memory computing via Analog AI Cores. These technologies will give the thousand-fold increases in efficiency efficiency required for full cognizance of abysmal researching AI, based on IBM.

“Our analog AI cores are a portion of an in-memory computing manner in performance effectivity which improves via suppressing the so-called Von Neuman bottleneck by putting off records switch to and from reminiscence,” referred to IBM. “Deep neural networks are mapped to analog cross factor arrays and unusual non-risky material qualities are toggled to retain network parameters in the cross points.”

“A key district of research and construction will live systems that meet the demands of abysmal getting to know inference and practicing approaches,” Khare mentioned. “Such systems offer giant accuracy improvements over more typical computing device getting to know for unstructured records. those immoderate processing demands will develop exponentially as algorithms develop into extra tangled with a view to convey AI programs with elevated cognitive potential.”

Khare talked about the analysis center will host R&D, emulation, prototyping, trying out and simulation actions for brand unusual AI cores specially designed for training and deploying superior AI fashions, together with a check bed during which individuals can demonstrate innovations in true-world functions. specialized wafer processing for the core should live finished in Albany with some lead at IBM’s Thomas J. Watson research center in Yorktown Heights, unusual york.


IBM Db2 query Optimization the usage of AI | killexams.com true Questions and Pass4sure dumps

In September 2018, IBM introduced a brand unusual product, IBM Db2 AI for z/OS. This synthetic intelligence engine screens data access patterns from executing SQL statements, uses desktop getting to know algorithms to pick most suitable patterns and passes this advice to the Db2 question optimizer for consume by subsequent statements.

laptop discovering on the IBM z Platform

In can furthermore of 2018, IBM announced version 1.2 of its laptop gaining knowledge of for z/OS (MLz) product. here's a hybrid zServer and cloud utility suite that ingests efficiency information, analyzes and builds fashions that symbolize the fitness repute of a variety of indicators, screens them over time and gives true-time scoring capabilities.

several aspects of this product offering are aimed at supporting a community of mannequin developers and executives. as an instance:

  • It supports numerous programming languages corresponding to Python, Scala and R. This makes it viable for records modelers and scientists to consume a language with which they are frequent;
  • A graphical person interface called the visual mannequin Builder publications model builders with out requiring incredibly-technical programming abilities;
  • It contains varied dashboards for monitoring mannequin results and scoring capabilities, as well as controlling the system configuration.
  • This machine getting to know suite was firstly geared toward zServer-primarily based analytics functions. one of the most first glaring choices was zSystem performance monitoring and tuning. system management Facility (SMF) records which are automatically generated through the operating system provide the uncooked information for device resource consumption corresponding to principal processor utilization, I/O processing, reminiscence paging and so on. IBM MLz can assemble and rescue these data over time, and construct and school models of system conduct, rating those behaviors, establish patterns now not with ease foreseen by means of humans, foster key efficiency warning signs (KPIs) after which feed the mannequin results back into the device to feel outfit configuration adjustments that can enrich efficiency.

    The next step changed into to implement this suite to dissect Db2 efficiency statistics. One solution, known as the IBM Db2 IT Operational Analytics (Db2 ITOA) solution template, applies the desktop discovering expertise to Db2 operational records to gain an understanding of Db2 subsystem health. it will possibly dynamically build baselines for key efficiency warning signs, provide a dashboard of those KPIs and provides operational personnel true-time perception into Db2 operations.

    while prevalent Db2 subsystem efficiency is an necessary factor in middling software fitness and performance, IBM estimates that the DBA lead staff spends 25% or extra of its time, " ... fighting access route problems which occasions efficiency degradation and repair affect.". (See Reference 1).

    AI involves Db2

    accept as honest with the plight of modern DBAs in a Db2 environment. In present day IT world they acquire to wait on one or extra commodious information purposes, cloud application and database capabilities, application installation and configuration, Db2 subsystem and software efficiency tuning, database definition and management, cataclysm recuperation planning, and extra. query tuning has been in being in view that the origins of the database, and DBAs are continually tasked with this as well.

    The heart of question direction analysis in Db2 is the Optimizer. It accepts SQL statements from purposes, verifies authority to entry the information, reports the places of the objects to live accessed and develops a listing of candidate data entry paths. These access paths can consist of indexes, table scans, quite a lot of table live portion of strategies and others. within the statistics warehouse and great facts environments there are usually additional decisions purchasable. One of these is the being of summary tables (on occasion referred to as materialized question tables) that comprehend pre-summarized or aggregated facts, thus allowing Db2 to stay away from re-aggregation processing. a further preference is the starjoin access course, middling in the records warehouse, where the order of table joins is changed for efficiency reasons.

    The Optimizer then studies the candidate access paths and chooses the access path, "with the lowest cost." suffuse in this context potential a weighted summation of useful resource usage together with CPU, I/O, reminiscence and other elements. finally, the Optimizer takes the lowest cost access course, retailers it in reminiscence (and, optionally, within the Db2 listing) and starts access course execution.

    huge information and records warehouse operations now encompass application suites that allow the enterprise analyst to acquire consume of a graphical interface to build and manipulate a miniature statistics mannequin of the facts they are looking to analyze. The applications then generate SQL statements based on the users’ requests.

    The issue for the DBA

    with a purpose to accomplish splendid analytics to your diverse data stores you need a splendid understanding of the statistics requirements, an understanding of the analytical capabilities and algorithms obtainable and a high-efficiency information infrastructure. unfortunately, the quantity and location of statistics sources is increasing (each in dimension and in geography), information sizes are transforming into, and applications continue to proliferate in quantity and complexity. How should IT managers wait on this atmosphere, notably with essentially the most experienced and mature staff nearing retirement?

    take into account additionally that a great a portion of decreasing the total suffuse of ownership of these methods is to regain Db2 applications to flee faster and more correctly. This usually interprets into the usage of fewer CPU cycles, doing fewer I/Os and transporting less information across the network. because it is frequently problematic to even establish which applications may handicap from performance tuning, one approach is to automate the detection and correction of tuning considerations. here is where computer gaining knowledge of and synthetic intelligence can furthermore live used to splendid impact.

    Db2 12 for z/OS and synthetic Intelligence

    Db2 edition 12 on z/OS makes consume of the computer getting to know amenities mentioned above to congregate and store SQL question text and entry direction particulars, in addition to genuine performance-related historical assistance equivalent to CPU time used, elapsed instances and outcome set sizes. This providing, described as Db2 AI for z/OS, analyzes and shops the records in computing device discovering models, with the mannequin analysis consequences then being scored and made obtainable to the Db2 Optimizer. The subsequent time a scored SQL commentary is encountered, the Optimizer can then consume the model scoring records as enter to its entry course alternative algorithm.

    The influence may still live a reduction in CPU consumption as the Optimizer makes consume of mannequin scoring enter to pick more desirable access paths. This then lowers CPU fees and speeds application response times. a significant talents is that the consume of AI application doesn't require the DBA to acquire data science skills or abysmal insights into question tuning methodologies. The Optimizer now chooses the top-quality access paths based no longer best on SQL question syntax and statistics distribution records however on modelled and scored ancient performance.

    This can live chiefly essential if you shop records in dissimilar places. as an instance, many analytical queries towards massive data require concurrent entry to certain statistics warehouse tables. These tables are commonly known as dimension tables, and that they comprehend the records aspects always used to manipulate subsetting and aggregation. as an instance, in a retail ambiance consider a table called StoreLocation that enumerates each rescue and its district code. Queries in opposition t retain sales records may wish to aggregate or summarize sales by passage of area; hence, the StoreLocation desk can live used via some huge facts queries. in this ambiance it's middling to snitch the dimension tables and copy them constantly to the massive statistics utility. within the IBM world this region is the IBM Db2 Analytics Accelerator (IDAA).

    Now believe about SQL queries from each operational purposes, records warehouse clients and massive information company analysts. From Db2's perspective, every unique these queries are equal, and are forwarded to the Optimizer. besides the fact that children, in the case of operational queries and warehouse queries they may still surely live directed to access the StoreLocation desk within the warehouse. however, the query from the enterprise analyst in opposition t massive data tables should likely access the copy of the table there. This effects in a proliferations of skills entry paths, and extra toil for the Optimizer. fortunately, Db2 AI for z/OS can deliver the Optimizer the tips it must acquire smart access direction decisions.

    the passage it Works

    The sequence of activities in Db2 AI for z/OS (See Reference 2) is frequently privilege here:

  • all over a bind, rebind, Put together or define operation, an SQL commentary is handed to the Optimizer;
  • The Optimizer chooses the data entry direction; as the option is made, Db2 AI captures the SQL syntax, entry direction option and query efficiency records (CPU used, and so on.) and passes it to a "studying assignment";
  • The learning project, which will furthermore live completed on a zIIP processor (a non-commonplace-purpose CPU core that does not factor into utility licensing costs), interfaces with the computing device discovering utility (MLz mannequin features) to retain this information in a mannequin;
  • because the quantity of records in every mannequin grows, the MLz Scoring provider (which furthermore can live completed on a zIIP processor) analyzes the mannequin statistics and rankings the behavior;
  • right through the next bind, rebind, Put together or explain, the Optimizer now has entry to the scoring for SQL fashions, and makes acceptable adjustments to entry path decisions.
  • There are furthermore a number of consumer interfaces that supply the administrator visibility to the reputation of the accumulated SQL statement efficiency facts and model scoring.

    abstract

    IBM's computer learning for zOS (MLz) providing is being used to first rate outcome in Db2 version 12 to help the performance of analytical queries in addition to operational queries and their linked applications. This requires administration consideration, as you need to examine that your industry is prepared to consume these ML and AI conclusions. How will you measure the charges and merits of using desktop researching? Which IT assist group of workers acquire to live tasked to reviewing the influence of model scoring, and perhaps approving (or overriding) the effects? How will you evaluation and justify the assumptions that the software makes about access direction selections?

    In other phrases, how smartly accomplish you know your data, its distribution, its integrity and your present and proposed entry paths? this will check the region the DBAs expend their time in helping analytics and operational application performance.

    # # #

    Reference 1

    John Campbell, IBM Db2 extraordinary EngineerFrom "IBM Db2 AI for z/OS: boost IBM Db2 software performance with machine researching"https://www.worldofdb2.com/hobbies/ibm-db2-ai-for-z-os-raise-ibm-db2-utility-efficiency-with-ma

    Reference 2

    Db2 AI for z/OShttps://www.ibm.com/assist/knowledgecenter/en/SSGKMA_1.1.0/src/ai/ai_home.html

    See every unique articles through Lockwood Lyon


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    Why I replaced Google Wifi with Synology's mesh networking gear (and why you might, too) | killexams.com true questions and Pass4sure dumps

    Router reviews are normally about speeds and feeds. They generally retort whether or not routers being reviewed are faster for Wi-Fi than other routers, and what connections and protocols they offer. They are an almost never-ending string of price/performance comparisons. CNET has an excellent, in-depth review of the Synology RT2600ac which has had the capitalize of CNET Labs performance testing.

    This review is not enjoy that. This review is almost entirely subjective. In it, I compare the marriage of the Synology RT2600ac and MR2200ac against Google Wifi in my very challenging house.

    The Synology RT2600ac is an AC2600 4x4 quad stream router. It's portion of a router class that, privilege now, includes hasty -- but not the fastest -- Wi-Fi routers. When CNET initially reviewed the RT2600ac, it was at the top of its game in terms of speed. Even two years later, it consistently gets considerable marks for its performance. There's a lot more to the RT2600ac, but we'll gain back to that later.

    Also: Best Wi-Fi Systems for 2019 CNET

    The Synology MR2200ac is, to me, where the magic is. The MR2200ac is a mesh router. You could just buy an MR2200ac and consume that as your only Wi-Fi router, but if you combine a few MR2200ac devices with an RT2600ac, it can transform the Wi-Fi in your home or office by creating a seamless, always-available mesh of solid Wi-Fi coverage.

    This was furthermore the engage of Google Wifi. You could (and still can) buy a bunch of Google Wifi pucks or, as I did, a Google Wifi-compatible Asus OnHub and then some Google Wifi pucks, and create a mesh network as well.

    I know. It gets confusing fast. stay with me. This will acquire sense very soon -- and it's necessary because it could acquire your life easier.

    Problem statement

    Last year, my wife and I bought a fixer-upper home in Oregon. It's a wonderful place, but it's a bit uncanny structurally. It consists of one section built on top of crawl space, and another section built slab-on-grade. Connecting the two is a minuscule hallway and utility closet, which furthermore has the water cooler, HVAC system, washer/dryer, and circuit breaker box.

    In other words, there's a Faraday cage between both wings of the house. It's almost impossible for a Wi-Fi signal from one side to gain the other.

    I initially set up Google Wifi to try to acquire everything work. My wife's office is at the far cease of one wing, and my office (and the servers) is at the other end. They both toil from home and rely entirely on both their internal LAN and the Internet to acquire their living.

    Also: Top 5 things to know about airplane Wi-Fi TechRepublic 

    My first attempt involved just planting a few Google Wifi pucks around the house, allowing the Wifi signal to leapfrog from one puck to another. In their previous house, this worked well enough -- so well, in fact, that doing so essentially upgraded an venerable 2011-vintage Mac mini's Wi-Fi to much more modern performance.

    In the unusual house, though, things weren't as optimal. It quickly became clear that Wi-Fi performance through the utility margin hallway was a non-starter. I first tried putting a string of bridging pucks between the rooms, including one just outside the hallway, one in the utility room, and one on just the other side.

    When that didn't work, I attached a wired Ethernet switch to the OnHub router and ran a cable from there through the hallway and utility closet, to a Google Wifi puck on the other side.

    Google Wifi supports using Ethernet as a back-channel for long-run communication, but it's very poorly documented. Worse, Google Wifi tech support doesn't acquire much additional information, which forced me to rely mostly on the Reddit GoogleWiFi subreddit for technical information.

    featurevisualise.png

    As you slip around your location, NetSpot maps signal energy onto a map or floor plan. IMAGE: NetSpot.

    Signal energy was generally good. I even used the pro version of the NetSpot Wi-Fi scanner to dissect performance house-wide. By the time I had placed six Google Wifi pucks, I was able to blanket the house with what NetSpot said was a solid signal.

    Also: 5 out of 6 routers are inadequately updated for security flaws

    This proved to live both expensive and futile. Some folks in the subreddit pretension that too many Google Wifi pucks clog up the signal, and I mediate they might live right. Google Wifi tech support, unfortunately, had nothing informative to mutter on the matter.

    But something wasn't right. No matter how many different configurations I tried of the Google Wifi pucks, rearranging them, tying them together with Ethernet or not, increasing and decreasing the number installed, their internal network reliability was just consistently poor.

    The problem was not their connection to the Internet, because they acquire absolutely stellar broadband. They toil from home, so they expend a bit extra to bring 1GB fiber performance to the house. The problem was Wi-Fi connectivity inside the house itself.

    img-3961.jpg

    img-3961.jpg

    Ideally, you want a solid line, not a lot of drop-offs.

    I used another tool, an app called Wi-Fi Sweetspots. This appliance constantly tests Internet connection quicken and graphs it over time. Because that test has to depart through the router, it's furthermore testing the connection quicken to the router. What I create was interesting.

    In areas of the house near the main router, connection speeds remained consistently high, but when I went to rooms at the far cease of the house, connection speeds alternated between really hasty and absolutely nothing. This despite the fact that my Wi-Fi signal energy in those identical areas was showing in the NetSpot survey as quite strong.

    Also: mediate your Wi-Fi's faster than mobile internet? Not in these 33 countries 

    In other words, the signal was good, but they were losing packets. A lot of packets. Connection quicken would betray as 500Mbps for a few seconds, then drop to zero for about five to thirty seconds, then pick back up to 500Mbps or more. The Google Wifi mesh wasn't meshing, apparently.

    Our IoT devices suffered the most. The Nest thermostat had vicissitude retaining a reliable connection. The Alexa devices nearest the main hub worked fine, but as they moved farther away from the center of the house, they had consistent connection issues. The smart TVs kept glitching on Netflix and Hulu.

    I eventually ran six network cables through the attic to the various main rooms of the house. This solved the problem of connecting computers to the server, but did not decipher the IoT issues, which rely on Wi-Fi almost exclusively.

    Our smart home was losing its grip.

    Enter Synology

    I've known the folks at Synology for a couple of years now. My first leer was at their 4-bay DS916+ NAS appliance. Later, I evaluated their 8-bay DS1817+, which went on to win top scores in their NAS Wars shootout.

    Synology distinguished itself by hitting on a number of vectors: splendid price/performance, excellent RAID reliability scores, and absolutely top-of-the-game usability scores with their Diskstation Manager (DSM) UI.

    The company furthermore makes routers. Their router UI, called Synology Router Manager, shares the identical exceptional UI design from DSM. But they need to live impartial here. The Google Wifi UI is furthermore excellent. Both are clear and well-designed.

    Also: The best location for your router for actually splendid Wi-Fi CNET

    What makes the Synology version different though, is that it's clear, but abysmal and powerful. You can set up intrusion detection, VPN, every unique sorts of traffic sculpting, and it's every unique very clear. On the other hand, the Google Wifi interface is designed for consumers. You can't even change your local IP address range. For some reason, if you're on Google Wifi, you're on 192.168.86.x. That's just the passage it is. UPDATE: It's been pointed out by several readers that this is no longer a limitation on Google Wifi. 

    For a year or so, I was relatively cozy trading power for Google's solid software and excellent network protection. I missed the VPN capabilities, but I was able to flee that through my NAS. I missed some of the power of traffic sculpting, but when I really thought about it, in a two-person household, it wasn't mission critical.

    But when my network experienced constant glitches, that I couldn't accept.

    I actually had a Synology-provided RT2600ac router in house while I was trying every unique my Google Wifi mesh workarounds. The problem was the RT2600ac just didn't acquire enough gain to acquire the ends of the house. It, too, was stymied by my hallway utility closet Faraday cage.

    Then, the company came out with their MR2200ac devices. These fulfill as standalone lower-end routers and as mesh extensions to the RT2600ac. enjoy Google Wifi, they will allow you to extend your Wi-Fi coverage by either leapfrogging Wi-Fi signals across devices, or by using an Ethernet connection and then extending Wi-Fi from that extended node. Unlike Google Wifi, the Ethernet extension option is a fully documented and supported feature that their support folks actually know about.

    Also: VPN services: The ultimate lead to protecting your data on the internet 

    Reaching the cease of my patience, I shot an email off to the folks at Synology and requested a couple of MR2200ac nodes to test. I figured that if my house was able to murder Google Wifi, it'd live a splendid test for Synology's mesh.

    I yanked out every unique the Google Wifi devices and replaced the main router with the RT2600ac. Then I attached an MR2200ac node to an Ethernet cable in my wife's office at one cease of the house. Because the architecture of the house is so weird, there was no passage to flee an Ethernet cable to the other portion of the house. Instead, I just dropped the second MR2200ac node on the floor by the back door.

    That was privilege around Thanksgiving. I've been running on the RT2600ac/MR2200ac mesh for about two and a half months. It's been rock solid. every unique of the IoT devices work. No matter where they are in the house, they acquire solid Wi-Fi.

    While connection quicken does drop down to about 200Mbps at the far reaches of the house, there is no packet loss. That's more than enough performance to stream movies and music and, watching Netflix and Hulu -- and connecting to their internal video server -- there acquire been no glitches.

    Cost may live an issue, though. You can regain a three-pack of Google Wifi pucks on Amazon for $239 (although retain in intellect that even six wouldn't decipher my networking problem). By contrast, the RT2600ac is two hundred dollars alone. Each MR2200ac will set you back about $140.

    Also: 11 ways to acquire your Wi-Fi faster CNET

    All told, my configuration (had Synology not been genial enough to provide me with test units for ZDNet) would acquire cost $480, or just about double what three Google Wifi devices cost. On the other hand, my smart home has gotten its mojo back, their IoT devices every unique now work, and streaming is solid everywhere in the house.

    What should you buy?

    Based on the GoogleWiFi subreddit, a lot of folks savor their Google Wifi devices. I did in their previous house. But there are furthermore a lot of folks who are hitting a wall with the devices, and because they're intended as a consumer item, Google doesn't acquire support for edge cases who need more performance.

    Synology, on the other hand, thrives on the edge cases. They give their customers every unique the customization capability they need, along with a hefty amount of power and the responsibility that goes with it.

    In terms of which you should buy, I mediate the preference is relatively simple:

  • If you acquire a minuscule home or office with simple Wi-Fi and networking needs, depart with Google Wifi or the Synology MR2200ac without the commodious RT2600ac router.
  • If you're on a budget and acquire a relatively minuscule space, depart with either Google Wifi or a unique Synology RT2600ac, depending on whether you want more flexibility or more Google.
  • If you acquire a larger space that's relatively open and you don't want to worry about network tweaking, you're probably splendid to depart with Google Wifi.
  • If you acquire a great space, want to acquire better control of your networking and enterprise-level features, depart with the Synology RT2600ac and MR2200ac mesh.
  • If you acquire a great space that actively blocks radio signals, depart with a combination of the RT2600ac, Ethernet cables to extend to remote areas, and MR2200acs devices to create Wi-Fi signal sources at those extended locations.
  • Basically, the geekier you are or the tougher the problem you have, the more you'll enjoy the Synology solution.

    What are you doing for Wi-Fi networking in your home or office? acquire you tried mesh networking? What's working best for you? Let us know in the TalkBacks below.

    You can supervene my day-to-day project updates on gregarious media. live certain to supervene me on Twitter at @DavidGewirtz, on Facebook at Facebook.com/DavidGewirtz, on Instagram at Instagram.com/DavidGewirtz, and on YouTube at YouTube.com/DavidGewirtzTV.


    Gigabyte G190-H44 1U server supports 4x GPU accelerators | killexams.com true questions and Pass4sure dumps

    Gigabyte emailed HEXUS today to uncover us about its recently launched G190-H44 barebone server. The Taiwanese PC and components specialist is disdainful to publish that the G190-H44 as its first lofty performance computing 1U server supporting 4 x double slot GPU / computing cards.

    The unusual Gigabyte G190-H44 is an official colleague product supporting the recently unveiled Nvidia Tesla M60 cards, and an Nvidia GRID certified server solution. However it isn't restricted to using the latest Nvidia GPU computing card, nor to Nvidia branded cards, a full range of Nvidia, AMD and Intel Xeon Phi cards are supported by this server.

    Looking at the ease of the necessary hardware specifications, Gigabyte's G190-H44 1U barebone system can live fitted with up to 2x Intel Xeon E5-2600 V3 processors, uses the Intel C612 chipset and supports 16 x DDR4 DIMM slots. For storage there are 2 x 2.5" hot-swappable HDD/SSD bays, 2 x 1.8" fixed HDD/SSD bays and 4 x SATA III 6Gb/s ports. Intel SATA RAID 0/1/5/10 is supported.

    Networking hardware includes 2 x GbE LAN ports (Intel I350-AM2) and 1 x 10/100/1000 management LAN. On board video comes from an integrated Aspeed AST2400 2D Video realistic Adapter with PCIe bus interface providing a maximum of 1920 x 1200 @60Hz 32bpp. Two 2000W redundant 80 PLUS Platinum PSUs are included in this barebones system.

    Of course this barebones has 4x full length, full height expansion slots – where you will fit the headlined (up to) 4x GPU accelerator cards. There are furthermore 2x full length low profile slots and you can order raiser cards depending upon what expansions you require.

    Gigabyte says its G190-H44 1U server offers an optimised airflow to retain every unique these cards frigid in a rackmount configuration. For durability and reliability Gigabyte consume industry-leading IR Digital PWM and IR PowIRstage IC controllers for CPU and reminiscence power delivery and OS-CON capacitors.

    A plethora of internal and external I/O is provided. Gigabyte facilitates many system management functions (inc Remote System Management) and supports Windows Server 2008 R2 (x64), Windows Server 2012 (x64), Windows Server 2012 R2 (x64) plus various Linux distributions and VMWare versions.

    Earlier this year they saw Gigabyte pioneer GPU intensive server products in the UK, with the launch of the G250-G52 lofty performance computing (HPC) 2U server chassis with support for 8x double slot GPU / computing cards.


    A rundown of server hardware vendors and the server options | killexams.com true questions and Pass4sure dumps

    Server hardware vendors offer servers of every unique shapes and sizes, providing a wide range of options for organizations. Most of the major players comprehend rack servers in their inventories, but many furthermore provide blade servers, and some even offer mainframe computers.

    Server hardware vendors usually offer other types of systems, as well, such as towers, converged infrastructures, hyper-converged infrastructures (HCIs), high-density systems or supercomputers.

    Acer

    Acer Inc. offers a handful of rack servers that target midsize and enterprise-level organizations. These rack servers comprehend the Altos and AR series, available in 1U and 2U shape factors. The Altos string includes four models, every unique dual-socket. The AR string includes two models, one unique socket and one quad socket.

    One of the most powerful Altos systems is the AR580, which supports up to four Intel Xeon E5-4600 Processors and up to 48 dual in-line reminiscence modules (DIMMs). The server furthermore provides redundant feverish swappable power supplies and a dual-port, 10-gigabit Ethernet controller.

    In addition to the rack servers, Acer offers the AW2000h F2 series, which includes two models of high-density servers. Although Acer does not bill these as blade servers, the systems are similar in many ways. For example, the Acer AW2000h w/AW370h F2 system comes in a 2U rack-mountable chassis that can flee up to four server nodes, each with up to two Xeon Processors and 16 DIMMs. In addition, Acer offers several tower models and one mini-tower.

    For information about pricing and how to purchase servers, buyers should directly contact Acer.

    Asus

    AsusTek Computer Inc. is one of the server hardware vendors that offer a variety of rack servers, as well as two tower and two high-density graphics processing unit (GPU) servers. The rack servers are portion of the RS string and the ESC4000 series.

    The RS string includes nine models available in 1U or 2U shape factors. The servers target a range of operations depending on industry size and workloads. For example, the RS720-E9-RS12-E rack server in the RS string supports up to two Intel Xeon Scalable Processors for a total of 56 cores and 112 threads. The server can furthermore support up to 3 TB of memory. Other servers in the RS string are not nearly as robust.

    The ESC4000 string includes three models, every unique 2U shape factors and two-socket systems, with support for up to eight DIMMs per CPU. The primary differences between the models are in the processor types and number of drive bays. For example, the ESC4000 G3 supports Intel Xeon E5-2600 Processors and up to eight feverish swappable 3.5-inch drives, but the ESC8000 G4 supports Xeon Scalable Processors and up to eight feverish swappable 2.5-inch drives.

    Buyers can purchase Asus servers online from retailers such as Newegg, Amazon or CDW, but they should retain in intellect that prices can vary significantly. For example, list prices for the ESC4000 G3 at these three retailers range from about $1,900 to $3,300, not including processors or memory.

    Cisco

    Cisco offers seven models of rack servers and six models of blade servers to accommodate organizations of every unique sizes, with prices starting anywhere between $3,000 and $26,000. The rack servers are included in the Unified Computing System (UCS) C-Series and are available in 1U, 2U and 4U shape factors. Most models support up to two Xeon Processors, but the C460 M4 and C480 M5 support up to four, with reminiscence varying between 1.5 TB and 6 TB. The maximum amount of supported internal storage can range between 30 TB and 246 TB.

    The blade servers are portion of the UCS B-Series, with each supporting two or four processors depending on the model. As with the rack servers, total available reminiscence ranges between 1.5 TB and 6 TB, with maximum storage between 6.4 TB and 39 TB.

    Cisco furthermore offers its UCS S-Series of storage servers, its UCS E-Series of arm office blade servers and the UCS C-Series of multimode servers.

    Buyers interested in purchasing servers can depart to the Cisco website to find a nearby retailer.

    Dell EMC

    Dell EMC is another one of the server hardware vendors that offer a wide range of rack and blade servers to accommodate different types of organizations. Most of the rack servers are portion of the PowerEdge R-Series, with starting prices ranging from $899 to $10,759.

    The R-Series includes four one-socket models, ten two-socket models and five four-socket models available in shape factors between 1U and 4U. One of the most powerful of these servers is the PowerEdge R940xa, a 4U system that supports up to four processors, 6 TB of reminiscence and 32 internal 2.5-inch disks.

    Dell EMC blade servers are available through the PowerEdge M-Series, which includes two models starting at $1,849. The models differ in terms of the number of sockets, types of processors, amount of memory, and in several other ways.

    For example, the PowerEdge M640 blade server supports up to two Xeon Scalable Processors and 16 DIMMs, whereas the PowerEdge M830 supports up to four Xeon E5-4600 Processors and 48 DIMMs.

    Dell furthermore offers seven models of tower servers, every unique portion of the PowerEdge family, as well as the PowerEdge MX string and PowerEdge FX series, both billed as modular infrastructures for high-density computing, similar to the PowerEdge M-Series.

    Buyers can purchase servers directly on the Dell EMC website.

    Fujitsu

    Fujitsu Ltd. sells an assortment of racks, blades, towers, mainframes and other types of computers to organizations of any size, but buyers must live cognizant that the available models can vary between countries.

    In the U.S., Fujitsu offers eight rack servers that are portion of the Primergy RX series. The servers are available with one, two or four sockets and in 1U, 2U and 4U shape factors. Fujitsu furthermore offers four rack models in the Primequest series, which watch to live more robust than those in the Primergy RX series. For example, the Primequest 3800E server is an eight-socket system with a 7U shape factor, and it supports up to 12 TB of memory.

    What sets Fujitsu apart from most other server hardware vendors is its BS2000 string of mainframe computers. The string includes three models. The most performant is the SE700B, which can flee several operating systems based on an ESA/390 architecture and Intel x86 technologies. However, buyers should note that this product is only available for purchase in Japan.

    In addition to the mainframe computers, Fujitsu offers the Primergy BX400 blade series, which supports two compute blade models, the BX2560 M2 and the BX2580 M2, along with other chassis components. Plus, Fujitsu offers its Primequest mission-critical series, Primergy tower servers, Sparc M-Series and PrimeHPC supercomputers.

    For prices and purchasing options, buyers should contact Fujitsu directly or contact a regional Fujitsu sales office.

    Hewlett Packard Enterprise

    Hewlett Packard Enterprise (HPE) offers a wide range of rack and blade servers for every unique types of organizations. HPE's rack servers are available in four series: ProLiant DL, ProLiant XL, Apollo and Integrity.

    The ProLiant DL string is the most extensive and includes six Gen10 models and four Gen9 models. The models are available in 1U, 2U and 3U shape factors and gain with one, two or four sockets.

    Starting prices can range anywhere from $600 to $25,000. For example, the ProLiant DL560 Gen10 entry server lists for $11,855 and supports up to two Xeon Scalable Processors and 6 TB of memory.

    HPE furthermore offers a range of blade servers, with three models in the ProLiant string and two models in the Integrity series. Prices here can furthermore vary, although not to the extreme of rack servers. For instance, ProLiant configurations can range between $3,300 and $14,470.

    HPE's products furthermore comprehend towers; converged and hyper-converged infrastructures; and systems such as the HPE Superdome, ProLiant simple Connect, ProLiant MicroServer, ProLiant Moonshot and ProLiant XL Server.

    Buyers can buy servers directly from the HPE website.

    Huawei

    Huawei Technologies Co. Ltd.'s FusionServer line includes 13 rack server models and 15 blade server models to accommodate both great and minuscule IT operations. The rack servers gain in two-socket, four-socket and eight-socket configurations and are available in shape factors from 1U to 8U.

    For example, the FusionServer RH8100 V3 server has an 8U shape factor and supports up to eight Xeon E7-8800 Processors, 12 TB of reminiscence and 24 internal 2.5-inch drives. Its blade servers are equally varied, providing both half-width and full-width compute nodes, as well as liquid-cooled nodes, with support for one or two processors.

    In addition to the rack and blade servers, Huawei offers its FusionServer X high-density servers, FusionServer heterogeneous servers, FusionCube HCI systems and KunLun mission-critical servers.

    For information about prices and how to purchase Huawei servers, buyers should contact Huawei or a sales colleague directly. Organizations that signed an eDeal agreement with Huawei can consume the online eDeal ordering system.

    IBM

    IBM offers a variety of server products, but the company is best known for its Z mainframe computers, available in three configurable models. The most current is the z14, which includes a 10-core z14 processor chip that uses 14 nanometer silicon-on-insulator technology. In addition, the server can support up to 8 TB of reminiscence and flee both z/OS and Linux on IBM Z.

    IBM furthermore offers a variety of rack servers. The rack servers are portion of the Power Systems string and comprehend 13 models, available in 1U, 2U and 4U shape factors, with one or two sockets.

    IBM no longer offers blade servers. The company sold its division that offered blade systems to Lenovo. The systems that IBM currently sells are generally geared toward enterprise deployments, as well as local, status and federal governments.

    In addition to mainframe and rack computers, IBM offers the LinuxOne Emperor II system, Power Systems scale-out servers, Power System S822LC for commodious Data, Power System S822LC for Commercial Computing, HCIs and towers.

    For information about prices and how to purchase servers, buyers should directly contact an IBM sales rep.

    Inspur Group

    Inspur offers 10 rack server models that can accommodate a variety of workloads. Most of these are portion of the NF series, which includes seven two-socket servers and two four-socket servers. The two-socket systems are available in both 1U and 2U shape factors and the four-socket systems in the 4U shape factor.

    Inspur furthermore offers the TS860G3 rack server as portion of the TS series. The server comes in an 8U shape factor and supports up to eight processors, 12 TB of reminiscence and 16 feverish swappable 2.5-inch drives, making it the most robust of the rack servers.

    Then there is the NX string of blade servers, which includes four compute node models, along with other types of components typical of a blade system, such as storage expansion nodes, PCIe expansion nodes, switch modules, network mezzanine cards and the chassis. In addition, Inspur offers the i24 high-density rack-mounted server and several rack-scale systems based on SmartRack, a elastic rack structure that contains centralized power, cooling and management at the rack level.

    For information about prices and how to purchase servers, buyers should directly contact Inspur.

    Intel

    Intel currently offers two categories of rack servers, grouped in the S1200SP and S2600WF server board series.

    The S1200SP string includes three models with unique processors and 1U shape factors, making them best suited for minuscule businesses. The S2600WF string includes 11 models and is geared more toward larger organizations. These servers are available in 1U and 2U shape factors and support dual processors. Buyers might furthermore gain across the S2600WT string of rack servers, but these models acquire been discontinued.

    Intel does not sell blade servers, but it does provide other systems. Notable among these is its Data center Blocks systems, which are purpose-built, fully validated server systems. Intel furthermore offers its Storage System JBOD2000 servers, which support up to 48 TB of storage.

    For information about pricing and how to purchase servers, buyers should contact Intel authorized distributors, which are listed on the Intel website. Customers can furthermore consume Intel's online Configure to Order system to request quotes and region orders as portion of the configuration process.

    Lenovo

    Most of Lenovo Group Ltd.'s rack servers are portion of the ThinkSystem line, which includes seven rack servers available in 1U or 2U shape factors. A couple of these servers support only one processor, but most support two, with reminiscence varying between 64 GB and 3 TB.

    For example, the ThinkServer RS160 is an entry-level 1U server that supports only one processor and 64 GB of memory, whereas the ThinkSystem SR630 is designed for data center workloads, supporting up to two processors and 3 TB of memory. In addition, Lenovo offers the System x series, which includes three rack models that can manipulate various types of workloads.

    As portion of its ThinkSystem line, Lenovo furthermore offers two blade compute node models: SN550 and SN850. The first is a two-socket blade that supports up to 3 TB of reminiscence and the second is a four-socket blade that supports up to 6 TB of memory. Both systems consume the Xeon Platinum Processor, which can flee up to 28 cores. In addition to the rack and blade servers, Lenovo offers tower servers, mission-critical servers and high-density servers.

    Buyers can purchase servers directly through the Lenovo website. Rack servers start at $1,499 and blade servers start at $4,099, but prices can flee much higher depending on the model and configuration.

    NEC

    NEC Corp. offers nine rack servers that are every unique portion of the Express5800 line. The servers are categorized as basic rack servers -- five models -- fault-tolerant servers -- two models -- and scalable enterprise servers -- two models.

    The basic rack servers are available in 1U and 2U shape factors. They support one or two processors, between 64 GB and 3 TB of memory, and between 40 TB and 194 TB of internal storage, making them suitable for a wide range of workloads.

    The fault-tolerant rack servers are 4U systems that support up to two processors, 512 GB reminiscence and 9.6 TB of storage.

    The scalable enterprise servers are furthermore 4U systems, but they support up to four processors, 6 TB of reminiscence and 9.6 TB of storage.

    NEC furthermore offers tower servers and modular servers, which are high-density, dual-socket systems that consume Xeon Scalable Processors. The servers comprehend over 35 MB of cache and support up to 2 TB of reminiscence and 24 TB of storage. The modular servers are similar to blade servers and are available as either 1U or 2U server modules.

    For information about pricing and how to purchase servers, buyers should contact NEC directly. Although NEC servers might live suitable for organizations of any size, the vendor has a more limited selection compared to other vendors.

    Oracle

    Although Oracle does not offer a great number of servers, its inventory includes a surprising amount of variety, most of which target midrange and larger organizations. The systems comprehend x86 servers, Sparc servers, high-end servers, midrange servers and scale-out servers. Oracle even offers servers that conform to the Network outfit building System standard. Despite this variety, Oracle does not offer blade servers.

    Oracle's rack servers Fall primarily in the x86 category and are portion of the X7 series. The string includes three models, which every unique consume Xeon Scalable Processors.

    The X7-2 model, billed as a compute-optimized system, is a 1U server that supports up to two processors, 1.5 TB of reminiscence and eight 2.5-inch storage drives. The X7-2L model is a storage-optimized 2U system that furthermore supports up to two processors and 1.5 TB of memory, but it can manipulate up to 12 3.5 inch drives. The final model, X7-8, is a scale-up 5U server that supports up to eight processors, 6 TB of reminiscence and eight 2.5 inch drives.

    For information about pricing and how to purchase servers, buyers should directly contact Oracle.

    Supermicro

    Of every unique these featured server hardware vendors, Supermicro Computer Inc. offers the largest server selection, but its categorization can acquire it difficult to navigate the options.

    In addition to towers, mid-towers and mini-towers, Supermicro offers SuperServer computers, SuperBlade systems, Ultra 1U and 2U platforms, BigTwin 2U four-node systems, FatTwin 4U multi-node systems, SuperStorage servers, GPU platforms with up to eight GPUs, and multiprocessor servers that support up to eight CPUs.

    For the most part, however, the rack servers are included in the SuperServer series, with some of the other categories integrated into that category. The blade servers are portion of the SuperBlade series.

    The SuperServer string includes hundreds of models, with a range that can accommodate just about any workload. The servers gain in 1U, 2U, 3U and 4U shape factors, and with one, two or four sockets. The SuperBlade string includes about 50 models.

    As with rack servers, there is something for everyone. Supermicro recommends that customers purchase servers from authorized local resellers or distributors in order to receive guaranteed local support and services.

    Because Supermicro sells so many products, prices can vary greatly depending on the server model and configuration. Buyers must accomplish their homework or toil with resellers to pick the best option.



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    References :


    Dropmark : http://killexams.dropmark.com/367904/11587041
    Wordpress : http://wp.me/p7SJ6L-R6
    Issu : https://issuu.com/trutrainers/docs/000-084
    Dropmark-Text : http://killexams.dropmark.com/367904/12124617
    Blogspot : http://killexams-braindumps.blogspot.com/2017/11/pass4sure-000-084-practice-tests-with.html
    weSRCH : https://www.wesrch.com/business/prpdfBU1HWO000QXLJ
    Calameo : http://en.calameo.com/books/004923526302b2bff0b1e
    publitas.com : https://view.publitas.com/trutrainers-inc/pass4sure-000-084-system-x-high-performance-servers-technical-support-v3-exam-braindumps-with-real-questions-and-practice-software
    Box.net : https://app.box.com/s/5riwe6cgdkevj9h4m7b83dav5d86rcg6
    zoho.com : https://docs.zoho.com/file/5psib8357cc24d3c340a983c170dbdc3458e5






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