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Test Code : 000-602
Test Name : IBM System z Technical Support V4
Vendor Name : IBM
: 67 Real Questions

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IBM System z Technical Support V4 certification

vigor techniques Bucks The IBM vogue And Grows | 000-602 Real Questions and VCE Practice Test

April 24, 2019 Timothy Prickett Morgan

The energy systems company continues to grow, and that is respectable information for all IBM i retail outlets, in particular for these of us who actively desire for there to be boisterous competitors in server processors and programs architecture. It comes as no shock that they feel massive Blue still has a lot to present when it comes to engineering programs that supply real differentiation in the market. the continued boom of vigor programs – protecting the happiness of the significant IBM i and AIX client bases and increasing the Linux base – is what is required for IBM to continue to make the heavy investments in processor and device design that it has carried out considering the fact that launching the energy structure returned in February 1990.

IBM has done just a little of rejiggering in its monetary reporting segments as it prepares to take in open source application significant crimson Hat, which it provided to purchase for $34 billion remaining fall, into its firm sometime in the 2d half of this yr. This rejiggering was additionally done as IBM is getting ready to sell the Domino collaboration utility and various on premises advertising applications to HCL, sells off its closing advertising purposes to Centerbridge, and has simply completed promoting off its Seterus loan servicing enterprise to Cooper neighborhood. in the first quarter, these groups represented round $417 million in revenues, so this time next year, when those groups are long gone, the Q1 2019 numbers should be that lots reduce when checked out from a relentless operations point of view.

The decent information is that pink Hat is a $3 billion (annual) utility enterprise transforming into at 25 % or so, and its numbers will snap in and more than make up the difference. As a part of the reporting section rejiggering, IBM merged its cloud software and so-called cognitive utility into one neighborhood – cognitive capability database, analytics, and transaction processing structures – and also merged its protection functions with its safety utility. The latter makes respectable sense. I believe it is a stretch to call databases, transaction screens, a considerable number of middleware, and such “cognitive” but IBM has to are trying to form some kind of rejuvenation story that Wall highway will buy – as do all IT companies that have been around for so long as big Blue has been.

in the first quarter led to March, IBM’s complete revenues had been $18.18 billion, down four.7 percent, and the business posted web revenue of $1.fifty nine billion, down 5.2 %. IBM is generating loads of money, youngsters nothing like a hyperscaler does, and accomplished the quarter with $18.14 billion in money and securities, roughly similar to that first quarter of earnings. IBM is build up its warfare chest to pay for that crimson Hat deal, and is promoting these application units above to elevate money to pay off pink Hat shareholders, who've given the acquisition the green mild. (Regulators within the u.s., Europe, and China have yet to weigh in, but they are going to.)

IBM’s methods neighborhood, which peddles equipment z and energy methods servers as well as storage arrays and application and operating techniques for these contraptions, had revenue of $1.33 billion to reseller companions and conclusion clients, down 11.5 %, with a different $163 million offered to other IBM corporations and divisions, up 6.5 percent yr on 12 months. complete techniques earnings got here to $1.49 billion, down 9.eight p.c. They estimate that inside these figures, IBM bought about $907 million in systems hardware (adding up server and storage hardware) externally, down 16 %, and operating system earnings came in at $428 million, down 2 p.c. They reckon that gross earnings for all of methods group have been round $628 million, however due to ongoing investments, pricing force within the server market in regularly occurring, better element costs, an unfavorable mix of equipment z mainframe revenue, and funding in future device z15 and Power10 processors, IBM booked a pretax loss of $202 million in the average techniques business. That’s in fact the equal stage of pre-tax loss IBM had within the yr-in the past period. the first quarter is all the time a foul one for IBM’s profitability in methods, so this is nothing new, and over the path of a full year, huge Blue makes money.

Jim Kavanaugh, IBM’s chief economic officer, spoke of on a call with Wall street analysts final week that the potent U.S. dollar has once once more supplied a headwind that diminishes the impact of overseas sales as offers in euro, ponds, yen, renminbi, and other currencies convert into fewer U.S. greenbacks than they might have a year in the past. For IBM universal, if you measured its increase at constant currency, it is only down 0.9 p.c, in comparison to the four.7 percent decline as stated. For the mainframe, the as GAAP profits as reported became down 39 percent in the quarter, and just about the identical at down 38 % at consistent foreign money, while for energy methods the as-pronounced sales have been up 6 percent but were up 9 % at consistent foreign money. IBM’s storage income inside techniques community fell 11 % at regular foreign money but 13 % as mentioned. operating systems revenues, which contains perpetual licenses for IBM i, AIX, and Linux however a much higher chunk it is for month-to-month licenses for the system z software stack, rose via 2 % as pronounced however elevated with the aid of 5 % at steady forex.

As they remind you on occasion, the element to trust for IBM as an entire is barely how large its genuine systems business is, if you happen to add in the entire application, technical assist, consulting, outsourcing, and financing that the company does for its system z and energy programs lines. They take a stab at estimating this every quarter, and this time round, in Q1 2019, they reckon that this real techniques company had income of $5.95 billion, up 4.7 percent, and that its gross profits were around $three.42 billion, up 12.6 p.c. (None of this contains IBM’s public cloud revenues, which they could argue belong in right here, or its database or utility utility, which you might add on.)

this fashion of things makes IBM seem as mighty in techniques as it truly is, as adversarial to so-Nineteen Nineties-meets-the-2010s approach that IBM talks about itself. To be fair, IBM can best discuss itself in a way that it is measuring itself, and clarity has not continually been the actual intention of fiscal reporting. just ample readability to maintain buyers and regulators satisfied is the true intention because too lots suggestions may cause more complications for a publicly traded company than now not satisfactory. In any adventure, this real techniques enterprise groundwork represents about a third of the enterprise’s revenues and about 40 % of its gross earnings, depending on the quarter.

That brings us to vigour methods, the iron upon which IBM i runs. this is the sixth consecutive quarter that the vigor methods enterprise line grew, and the frenzy of Linux on vigour is paying off, specifically in the HPC space. SAP HANA in-memory processing, and quite a lot of styles of statistics analytics, in particular the type that uses machine studying with GPU acceleration to supply the training for neural networks. The Power9 upgrade cycle for customers working massive workloads on Oracle 11g and 12c in addition to IBM Db2 databases is additionally helping, chiefly on the high end of the energy line. “both the high end and entry level offerings posted mighty boom this quarter as clients continue to adopt this new expertise,” Kavanaugh noted in reference to revenue of vigor-based mostly iron.

however vigor-based mostly storage earnings, just like the excessive end DS8800 disk arrays, took it on the chin a little in Q1 2019, and that become as a result of the downdraft within the mainframe market, which is due by and large to the incontrovertible fact that the system z14 is in the seventh quarter of its life. it will seem that IBM needs a new technology of mainframes (presumably the system z15), however that doubtless received’t ensue until 2021 or so, when the Power10 chips are additionally expected to be put into as a minimum two exascale-category supercomputers and also be spread throughout the greater conventional vigor techniques line.

in accordance with their income model for energy server sales and storage income in line with energy iron (just like the DS collection), here is how they consider the quarter mapped out in comparison to those in view that the exquisite Recession all started in 2009:

the primary quarters for 2017, 2018, and 2019 have been trending upwards, besides the fact that children just a little, and would have appeared even more desirable had storage hardware revenue no longer taken a 13 percent dive. simply so you don’t ought to squint your eyes there, they suppose that IBM had $302 million in power systems revenue – again, including servers in response to power processors in addition to a portion of the storage array hardware revenue that come from things just like the DS collection – up 3.8 p.c. This does not have in mind sales of working systems for vigour iron or revenue of vigor machinery to IBM’s outsourcing valued clientele. That could have added significantly to the earnings circulation from vigor, however they have no way of guessing how lots that may be. They currently went out on a limb to try to reckon these numbers for all of 2018, and that is about as far as they feel relaxed doing.

connected reviews

vigor techniques: riding extra income Than initially idea

Taking At Stab At Modeling The vigour methods enterprise

power methods hold becoming To conclude Off 2018

programs A shiny Spot In combined results For IBM

The Frustration Of not knowing How they are Doing

vigor techniques Posts increase in the First Quarter

IBM’s techniques group On The monetary Rebound

big Blue gains, Poised For The Power9

The vigor Neine Conundrum

IBM Commits To Power9 enhancements For huge vigour systems retail outlets


What Drove The AI Renaissance? | 000-602 Real Questions and VCE Practice Test

Italian Renaissance: Vitruvian Man via Leonardo da Vinci

Wikipedia

it's the present-day darling of the tech world. The current renaissance of artificial Intelligence (AI) with its sister self-discipline desktop discovering (ML) has led each IT company price its salt to engineer some sort of AI onto its platform, into its toolsets and all through its utility applications.

IBM CEO Ginni Rometty has already proclaimed that AI will alternate one hundred percent of jobs over the subsequent decade.

And yes, she does imply each person's job from yours to mine and onward to the position of grain farmers in Egypt, pastry cooks in Paris and dog walkers in Oregon i.e. every job. they are able to now be capable of help direct all laborers’ movements and behavior with a new diploma of intelligence that comes from predictive analytics, all stemming from the AI engines they will now increasingly depend upon.

When did it all go so appropriate?

but AI was a fanciful notion more often than not restrained science fiction, so when did it all go right?

In recent years we’ve had some massive changes in know-how. other than the proliferation of mobile instruments that has impacted us all, memory has turn into lots more affordable, information storage has turn into a lot less complicated (in cloud, and in different places) and laptop processing speeds have persevered to outstrip outdated information. With the energy of quantum computing across the corner, is the AI renaissance without difficulty as a result of the the arrival together of those ‘tech ingredient’ forces?

“It is never simply huge compute energy. There are essential algorithmic alterations which have been developed. Plus, it is much simpler to profit entry to extra facts in an online-linked world,” talked about Ted Dunning, CTO at records platform, AI and analytics enterprise MapR. “All three features (compute, algorithms, statistics) combine to make todays computer researching feasible. also and reasonably frankly, lots of functions best need facts availability... they may have applied them 25 years ago relatively without difficulty if the information had been purchasable and the output of the model could have been integrated lower back into the company move.”

So, in many ways, Dunning in fact heralds the up to date era of the net because the key facilitator for the new age of AI. counsel has turn into now not just ubiquitous; it has also turn into less difficult to entry and greater precisely categorized into structured, semi-structured and unstructured facts in its rawest form.

Tuning AI against existence

Dunning and MapR factor out that the brand new era of AI & ML is now rediscovering ideas, some of which were first concept of some 50 years in the past. The change today is, each and every time keep including a bit of something new. a little of computing vigour right here, improved records there, new concepts for organizing and optimizing a community and after a long time they get to construct new AI techniques that truly do advantageous work. So how may still they continue to engineer these new methods?

"A key to success [in the new era of AI] is to focus on the design of the human-AI interactions as much as within the AI itself," stated Jesus Mantas, accepted supervisor and managing associate in IBM world company functions. “Many AI classes focal point essentially on laptop studying algorithms and training datasets, but fail to tackle the most crucial success factors: the design of human-laptop relationships, new AI-powered workflows… and perfecting the choreography of methods, technology and humans. those classes hardly ever scale or obtain merits. The organizations succeeding to scale AI and its advantages show that knowledgeable, purposeful design of workflows and consumer interactions result in quicker adoption and enterprise advantages."

CEO of AI code analytics platform enterprise Gamma is Vishal Rai. In standard terms, Rai consents that the AI renaissance has been pushed by using tectonic shifts in three areas within the computing world: computing power, swathes of information (and its accessibility)… however additionally with the aid of human ingenuity.

He features to new traits popping out of both Silicon Valley however extra afield additionally (China being a main illustration, Huawei builds its smartphone chipsets around its Kirin AI-enriched microprocessor) and says that here's all assisting to create future industries akin to self sustaining using and health care diagnostics.

actual world utility of AI functions

So in what ways are the brand new real world applications of AI manifesting themselves and beginning to influence the features they use under the floor?

Cloud computing application intelligence and software efficiency administration (APM) professional Dynatrace has now extended its AI-powered platform to encompass IBM Z mainframe assist for CICS (a mainframe programming language), IMS (a mainframe database) and middleware. to position that in much less technical terms, Dynatrace can be used to video display application that sits on mainframes to make sure it stays in shape.

Why bother? since the mainframe was not ever constructed to be hammered via devices with hugely busy statistics streams like mobile banking apps, video games and other on-line niceties. This potential they want AI to be mindful what have an impact on the mainframe is having on the newer systems they build.

“whereas businesses are moving functions to modern cloud stacks for agility and competitive abilities, these purposes commonly nonetheless rely upon important transactions and ‘crown jewels’ consumer statistics dwelling on IBM Z mainframes. This places power on these substances to function initiatives that had been no longer expected when the mainframes had been launched,” talked about Steve Tack, SVP of items at Dynatrace. “as a result of Dynatrace gives conclusion-to-conclusion hybrid visibility [through their Davis AI engine], shoppers can optimize new services, seize efficiency degradations earlier than person affect, and have in mind exactly who has been impacted via an incident. This allows for purchasers to confidently innovate functions that leverage data from mainframes to raise profits, construct manufacturer loyalty, and create competitive capabilities.”

AI as a piece of art

Many would argue that the route to modern AI has been a protracted slog, however the programs they build now preserve finding artful shortcuts… so the momentum for the AI renaissance is truly constructing cumulatively.

Some argue that AI certainly not went away and that the existing popularization of AI and its ensuing discussion is barely a natural progression of a expertise that simply necessary to come back through a length of early life. both approach, AI is on your smartphone and for your cloud computing functions, so renaissance or now not, let’s hope it continues to become a piece of paintings.

Renaissance artwork

Wikipedia

IBM Cloud Floats Power9 ‘Volta’ Servers | 000-602 Real Questions and VCE Practice Test

At IBM’s inaugural believe 2018 convention and third US-primarily based OpenPower summit, the tech tremendous is trumpeting swelling momentum for its OpenPower ecosystem and traction for Power9, together with Google’s disclosure that its customized-constructed (by using Rackspace) Power9 “Zaius” servers are “Google amazing,” i.e., market equipped. IBM is additionally welcoming the power servers, backed by Nvidia V100 GPUs, into its cloud.

IBM energy gadget AC922

In a weblog submit on “bringing safety and AI to the IBM cloud” Ross Mauri, accepted manager, IBM Z, and John Considine, familiar supervisor, IBM Cloud Infrastructure, revealed the availability of the Power9-based mostly AC922 (“Witherspoon”) systems in the enterprise’s cloud. the new servers with two 16-core Power9 chips and four Nvidia Tesla V100 GPUs are noted to provide a 4x speedup for deep studying practising in comparison to competitive Intel hardware, in response to internal testing by using IBM*.

while hailing the benefits of its vigor servers’ unique help for the CPU-to-GPU NVLink interface (which presents a 5-10x speedup in communications over PCIe gen3), IBM has been gradual to deliver HPC-classification vigor architectures into its personal cloud, even ceding first-mover bragging rights to associate and HPC cloud seller Nimbix, which deployed the Power8 Minsky expertise in 2016 (and turned into the first public cloud company to accomplish that). [Nimbix is also announcing Power9 on its cloud, which they cover in-depth here.]

IBM became an early adopter of Nvidia’s high-end Pascal and Volta GPU gear, however used the PCIe versions within x86 Intel servers. Why IBM held out on putting power in its cloud is a little of a head-scratcher due to the fact the business believes it has the sophisticated know-how (with vigour) and approach (with OpenPower) to position a dent in Intel’s online game. If IBM’s cloud shoppers weren’t ready, that’s comprehensible, however for the sake of optics on my own, it’s extraordinary IBM didn’t make the circulate earlier.

At any fee, now there is some vital mass occurring for vigour/OpenPower (coated right here) and IBM Cloud is relocating to embrace it. PowerAI will also be brought into the IBM Cloud, with planned availability for next quarter. The suite of artificial intelligence equipment supporting frequent frameworks like TensorFlow, Torch and Caffe become developed and optimized for IBM’s accelerated vigour servers, so it’s simplest herbal that it will be protected.

moreover, IBM introduced it is integrating SAP HANA on energy into the IBM Cloud as an SAP-licensed managed application provider. “through this integrated approach of hardware and application, IBM is the primary to present this level of cloud help for huge workloads of as much as 24 TB by using IBM vigour techniques and IBM Storage,” pointed out Mauir and Considine.

In a press briefing at IBM suppose, Senior vice chairman IBM Cognitive techniques Bob Picciano noted the usual approach to excessive-performance computing is present process disruption from the quick turning out to be GPU-accelerated approach. “We’re democratizing hardware-application integration,” Picciano instructed HPCwire. He cited Snap ML on Power9 for example, referring to the new library developed through the IBM Zurich analysis that “trains models quicker than that you can snap your fingers.”

using an online advertising (click on circulation) dataset launched with the aid of Criteo Labs with over four billion practising examples, the Zurich group knowledgeable a logistic regression classifier across 4 IBM energy equipment AC922 servers, every with four Nvidia Tesla V100 GPUs. working towards become accomplished in barely 91.5 seconds, a 46x speedup over the old greatest effect suggested by means of Google, which used TensorFlow on Google Cloud Platform to educate the same model in 70 minutes (more information here). “We’re considering pattern again and again with computer learning and deep discovering once you flow into Power9 on the GPU stack,” mentioned Picciano.

while IBM rolls out Power9/OpenPower in the commercial enterprise, it has already made a splash in management supercomputing with the DOE Power9-based mostly CORAL machines Summit and Sierra. on course for acceptance this summer time, the techniques, which can charge $325 million to increase and manufacture, could be the largest in the u.s.; and Summit, with an expected 200-petaflops of top efficiency, is within the running to be the world’s fastest supercomputer, as measured by the long-running Linpack benchmark.

* consequences are in response to IBM internal Measurements operating the CUDA H2D Bandwidth test Hardware: vigour AC922; 32 cores (2 x 16c chips), POWER9 with NVLink 2.0; 2.25 GHz, 1024 GB memory, 4xTesla V100 GPU; Ubuntu 16.04. S822LC for HPC; 20 cores (2 x 10c chips), POWER8 with NVLink; 2.86 GHz, 512 GB memory, Tesla P100 GPU  aggressive HW: 2x Xeon E5-2640 v4; 20 cores (2 x 10c chips) / forty threads; Intel Xeon E5-2640 v4; 2.4 GHz; 1024 GB memory, 4xTesla V100 GPU, Ubuntu 16.04


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