IBM C9010-262 : IBM Power Systems with POWER8 Enterprise Technical Sales Skills V2 ExamExam Dumps Organized by Dingxiang
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Exam Title :
IBM Certified Technical Sales Specialist - Power Systems with POWER8 Enterprise V2
Exam ID : C9010-262
Exam Duration : 120 mins
Questions in test : 60
Passing Score : 38 / 60
Exam Center : Pearson VUE
Real Questions : IBM Power Systems with POWER8 Enterprise Technical Sales Skills Real Questions
VCE practice test : IBM C9010-262 Certification VCE Practice Test
- Identify the advantages of POWER8 processor technology vs x86.
- Compare and contrast the value proposition of Power Systems solutions (e.g., SAP HANA) with competitive solutions (e.g., x86, Dell, HP, Oracle, etc.).
- Position the advantages of PowerVM virtualization solutions relative to competition (e.g., Oracle, HP, Hyper-V, VMware). 10%
Design Solution to Customer Requirements
- Given customer requirements, design an appropriate HMC solution, including Enterprise Pools, remote restart, performance and capacity management, virtualization management/co-management, redundant FSPs, multiple HMCs, and secure networking.
- Incorporate appropriate existing hardware in a new configuration (e.g., disk drive migration, etc.).
- Discuss the options that are available for attaching SAS storage to Power Systems enterprise servers.
- Given a customer's requirements, describe the benefits of Integrated Facility for Linux.
- Recognize that enterprise servers can be designated for CBU.
- Describe the role of the Technical and Delivery Assessment (TDA) and how it is used to meet customer requirements.
- Identify terms and conditions when implementing CoD (Capacity on Demand) offerings (e.g., CUoD, Utility, Elastic, Mobile Activations, Trial).
- Identify key IBM cloud management offerings available for Power Systems (e.g. PowerVM NovaLink, PowerVC, IBM Cloud Orchestrator) and the benefits that are associated with having a cloud infrastructure based on Power enterprise servers (e.g. configuration flexibility, Dynamic Resource Optimization, Capacity on Demand).
- Utilize knowledge of key IBM cloud management offerings to address Power Systems customers' business imperatives for private and/or hybrid cloud.
- Position key IBM analytics solutions on enterprise Power Systems (e.g., DB2 BLU, Cognos, SPSS) relative to scalability over scale-out models.
- Identify IBM's heterogeneous computing solution offerings (e.g., solutions utilizing CAPI, GPUs, FPGAs).
- Identify technical advantages that POWER8 enterprise servers provide for Linux workloads in terms of performance, price/performance, and workload consolidation.
- Identify the processes that are possible to install and maintain hardware and software (e.g., firmware, FLRT, etc.).
- Identify the benefits of PowerCare for enterprise servers.
- Given a client's availability requirements (RTO/RPO), design an appropriate solution for business continuity and/or disaster recovery (e.g., PowerHA, backup/restore). 35%
Power Systems Architecture and Product Family
- Position why enterprise models may be preferred to Scale-out models in order to satisfy customer needs.
- Describe the Power Systems enterprise servers' features and functionality.
- Recognize POWER8 compatibility with prior generations of Power Systems when planning to upgrade or migrate a customer's installed hardware and/or software.
- Describe reliability, availability and serviceability (RAS) features of the Power Systems product family, especially those features that are exclusive to enterprise-class models.
- Identify Capacity on Demand features and benefits and describe when each is appropriate, including CUoD, Elastic, Utility and Trial.
- Describe Enterprise Pools prerequisites, capabilities and benefits.
- Design solutions with expansion drawers, adapter cards, traditional disk, Solid State Drives (SSDs), and attached SAN and tape into a POWER8 solution.
- Describe the benefits of POWER8 processor architecture, including SMT, L4 cache, balanced performance, clock speed, EnergyScale, memory bandwidth, I/O bandwidth (PCIe Gen3), CAPI, etc. relative to prior Power Systems and competition.
- Identify rack best practices for enterprise servers (e.g., I/O drawer placement, spacing, and cabling implications, "deracking", horizontal PDUs, IBM manufacturing options, etc.). 37%
Virtualization and Cloud
- Recognize when to configure physical I/O, virtual I/O or a combination of both.
- Match hardware connectivity (Fibre Channel, SAS, iSCSI) with the types of virtualization (NPIV, vSCSI, SR-IOV, SEA).
- Determine when shared storage pools are appropriate for an enterprise scenario.
- Given a scenario, apply the capabilities of Live Partition Mobility.
- Given a scenario, apply the resource sharing capabilities of Power Systems, including processors, memory, and I/O.
- Given a business need and workload, design an appropriate virtualization solution (including how to virtualize).
- Design an appropriate virtualization system management solution (consider: HMC, PowerVC, PowerVM NovaLink). 18%
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In October 2019, researchers at Google introduced to outstanding fanfare that their embryonic quantum computing device had solved an issue that would overwhelm the most excellent supercomputers. Some mentioned the milestone, referred to as quantum supremacy, marked the crack of dawn of the age of quantum computing. despite the fact, Greg Kuperberg, a mathematician at the college of California, Davis, who focuses on quantum computing, wasn’t so impressed. He had expected Google to purpose for a goal this is less flashy however, he says, far more essential.
whether it’s calculating your taxes or making Mario jump a canyon, your desktop works its magic by way of manipulating long strings of bits that can be set to 0 or 1. In contrast, a quantum desktop employs quantum bits, or qubits, that may also be each 0 and 1 at the equal time, the equivalent of you sitting at both ends of your sofa without delay. Embodied in ions, photons, or tiny superconducting circuits, such two-way states supply a quantum laptop its power. but they’re also fragile, and the slightest interaction with their surroundings can distort them. So scientists have to be taught to correct such errors, and Kuperberg had anticipated Google to take a key step toward that aim. “I agree with it a extra primary benchmark,” he says.
If some experts question the value of Google’s quantum supremacy test, all stress the significance of quantum error correction. “it's in reality the change between a $100 million, 10,000-qubit quantum computing device being a random noise generator or the most powerful computer on the planet,” says Chad Rigetti, a physicist and co-founding father of Rigetti Computing. And all agree with Kuperberg on step one: spreading the counsel mostly encoded in a single jittery qubit amongst many of them in a means that continues the advice even as noise rattles the underlying qubits. “You’re trying to construct a ship that is still the identical ship, while every plank in it rots and has to be replaced,” explains Scott Aaronson, a pc scientist on the university of Texas, Austin.
The early leaders in quantum computing—Google, Rigetti, and IBM—have all proficient their points of interest on that goal. “That’s very explicitly the subsequent massive milestone,” says Hartmut Neven, who leads Google’s Quantum synthetic Intelligence lab. Jay Gambetta, who leads IBM’s quantum computing efforts, says, “in the next couple of years, you’ll see a series of consequences for you to come out from us to take care of error correction.”
Physicists have begun to check their theoretical schemes in small experiments, but the problem is grand. To display quantum supremacy, Google scientists needed to wrangle fifty three qubits. To encode the information in a single qubit with ample fidelity, they may need to master 1000 of them.
the quest for quantum computer systems took off in 1994 when Peter Shor, a mathematician on the Massachusetts Institute of technology, showed that this type of computing device—then hypothetical—should be in a position to right now component large numbers. Shor’s algorithm represents the feasible factorizations of a bunch as quantum waves that may slosh simultaneously during the desktop’s qubits, due to the qubits’ two-manner states. The waves intervene so that the incorrect factorizations cancel one another and the correct one pops out. A laptop running Shor’s algorithm might, among different things, crack the encryption techniques that now cozy information superhighway communications, which depend on the undeniable fact that attempting to find the factors of an important quantity overwhelms any average desktop.
besides the fact that children, Shor assumed each and every qubit would maintain its state so the quantum waves might slosh round as long as essential. precise qubits are a long way much less sturdy. Google, IBM, and Rigetti use qubits product of tiny resonating circuits of superconducting metallic etched into microchips, which to this point have proved more convenient to control and combine into circuits than different styles of qubits. each and every circuit has two different energy states, that could denote 0 or 1. by way of plying a circuit with microwaves, researchers can ease it into either state or any aggregate of the two—say, 30% 0 and 70% 1. but these in-between states will fuzz out or “decohere” in a fraction of a 2d. Even earlier than that happens, noise can jostle the state and alter it, potentially derailing a calculation.Mapping a qubit
Whereas a normal bit ought to be either 0 or 1, a qubit will also be in any aggregate of 0 and 1 on the identical time. these two constituents of the state mesh in a method described by means of an summary angle, or phase. So the qubit’s state is like a degree on a globe whose latitude displays how a good deal the qubit is 0 and the way tons it is 1, and whose longitude shows the section. Noise can jostle the qubit in two primary ways in which knock the element around the globe.
Bit-flip error Exchanges 0 and 1, flippingthe qubit in latitude Qubitstate phase-flip error Pushes the qubit’s state halfwayaround the sphere in longitude section Equal mixof 1 and nil Mixtureof 1 and zero 1 0
Such noise virtually drowned out the sign in Google’s quantum supremacy experiment. Researchers started by way of surroundings the fifty three qubits to encode all feasible outputs, which ranged from zero to 253. They implemented a set of randomly chosen interactions among the many qubits that in repeated trials made some outputs extra doubtless than others. Given the complexity of the interactions, a supercomputer would need hundreds of years to calculate the pattern of outputs, the researchers observed. So by way of measuring it, the quantum computing device did some thing that no standard laptop might suit. but the demo was barely distinguishable from the random flipping of qubits caused by way of noise. “Their demonstration is ninety nine% noise and most effective 1% sign,” Kuperberg says.
To understand their best goals, builders need qubits that are as authentic as the bits in an ordinary computer. “You are looking to have a qubit that stays coherent until you change off the computing device,” Neven says.
Scientists’ method of spreading the tips of 1 qubit—a “logical qubit”—amongst many genuine ones traces its roots to the early days of common computer systems in the Fifties. The bits of early computers consisted of vacuum tubes or mechanical relays, which were liable to flip all at once. to conquer the difficulty, famed mathematician John von Neumann pioneered the box of error correction.
Von Neumann’s method relied on redundancy. think a laptop makes three copies of every bit. Then, even though probably the most three flips, the vast majority of the bits will retain the appropriate environment. The laptop can discover and fix the flipped bit with the aid of evaluating the bits in pairs, in so-called parity checks. If the first and third bits healthy, however the first and 2nd and 2nd and third range, then undoubtedly, the 2d bit flipped, and the computer can flip it lower back. more suitable redundancy capability stronger capacity to suitable mistakes. sarcastically, the transistors, etched into microchips, that up to date computers use to encode their bits are so legit that error correction isn’t an awful lot used.
but a quantum computer will rely upon it, at least if it’s made from superconducting qubits. (Qubits product of individual ions suffer less from noise, however are more durable to integrate.) lamentably for developers, quantum mechanics itself makes their task plenty tougher with the aid of depriving them of their easiest error-correcting device, copying. In quantum mechanics, a no-cloning theorem says it’s not possible to reproduction the state of 1 qubit onto a further with out altering the state of the first one. “This capability that it’s now not possible to without delay translate their classical error correction codes to quantum error correction codes,” says Joschka Roffe, a theorist at the school of Sheffield.a straightforward fix
In a conventional laptop, a little is a switch that will also be set to either 0 or 1. To supply protection to just a little, a pc can copy it. If noise then flips a copy, the desktop can discover the error through making parity measurements: evaluating pairs of bits to look whether or not they’re the same or distinct.
1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 Parity measurements Errorcorrection Noise Flipped bit Copying
Even worse, quantum mechanics requires researchers to find blunders blindfolded. youngsters a qubit can have a state it is both 0 and 1 on the equal time, based on quantum theory, experimenters can’t measure that two-manner state with out collapsing it into either 0 or 1. Checking a state obliterates it. “The simplest [classical error] correction is that you simply look at all the bits to look what’s long gone wrong,” Kuperberg says. “but when it’s qubits then you definitely have to locate the error with out searching.”
those hurdles might also sound insurmountable, however quantum mechanics features to a possible solution. Researchers can't replica a qubit’s state, however they could prolong it to different qubits the use of a mysterious quantum connection called entanglement.
How the entangling is executed shows simply how refined quantum computing is. Prodded with microwaves, the usual qubit interacts with an extra that ought to start in the 0 state through a “managed no longer” (CNOT) operation. The CNOT will exchange the state of the 2nd qubit if the state of the first is 1 and leave it unchanged if the primary qubit is 0. although, the maneuver doesn’t really measure the primary qubit and cave in its state. as an alternative, it keeps the each-ways state of the primary qubit while both altering and not changing the second qubit at the same time. It leaves the two qubits in a state in which, simultaneously, they are each 0 and both 1.
If the usual qubit is in, for instance, a 30% 0 and 70% 1 state, physicists can hyperlink it to other qubits to make a sequence of, say, three qubits that share an entangled state that’s 30% all three are 0 and 70% all three are 1. That state is distinctive from three copies of the original qubit. in reality, none of the three entangled qubits in the string possesses a well defined quantum state of its own. however now, the three qubits are completely correlated: if you measure the first one and it collapses to 1, then the different two must additionally instantly cave in to 1. If the first collapses to 0, the others need to additionally. That correlation is the essence of entanglement.
With that greater entangled state, scientists can now retain a watch out for mistakes. To try this, they entangle nevertheless different “ancillary” qubits with the chain of three, one with first and 2nd qubits within the string and an extra with the second and third. They then use measurements on the ancillas to make the quantum mechanical equivalent of parity tests. as an example, without breaking the entanglement, noise can flip any one of the three coding qubits in order that its 0 and 1 ingredients get switched, changing the latent correlations among all three. If researchers set issues up correct, they could make “stabilizer” measurements on the ancillary qubits to probe those correlations.
besides the fact that children measuring the ancillary qubits collapses their states, it leaves the coding qubits unperturbed. “These are exceptionally designed parity measurements that don’t fall down the information encoded in the logical state,” Roffe says. as an example, if the measurement suggests the primary ancilla is 0, it exhibits handiest that the primary and 2nd coding qubits ought to be in the equal state, however no longer which state that's. If the ancilla is 1, then the dimension reveals most effective that the coding qubits must be in contrary states. If researchers can discover a flipped qubit more without delay than the qubits tend to fuzz out, they could use microwaves to flip it again to its original state and restore its coherence.Quantum fixes are tougher
The rules of quantum mechanics make it unattainable to look ahead to mistakes with the aid of copying and measuring qubits (properly). as a substitute, physicists need to unfold the qubit’s state to other qubits through “entanglement” (core) and computer screen those to realize blunders; then nudge an errant bit again to the relevant state (bottom).
greater is betterInstead of making an attempt to copy the state of a qubit, physicists can amplify it via entangling the qubit with others, resulting in a single state that corresponds to the equal aspect on a sphere. misplaced identification in the entangledcondition, none of thethree qubits has awell-defined quantumstate of its own. 0 1 0 1 Entanglement Copying now not so quick! Quantum mechanicsdoes no longer allow the stateof one qubit to becopied onto others. Originalqubit 0 1 0 1 0 1 000 111 111 000 101 010 111 000 Noise Ancillary qubit entangled with the primary and second qubits Ancillary qubit entangled with the 2d and third qubits Correction mild correctivesNow, if noise flips some of the qubits, physicists can notice the exchange devoid of basically measuring the state. They entangle pairs of the main qubits with other ancillary qubits whose state will also be measured and should be 0 if the correlation between a pair continues to be the equal and 1 if the correlation is flipped. Microwaves can then unflip the qubit and fix the preliminary entangled state.
That’s simply the simple idea. The state of a qubit is greater advanced than simply a mixture of 0 and 1. It additionally depends on precisely how these two components mesh, which, in flip, depends on an abstract attitude called the section. The phase can latitude from 0° to 360° and is key to the wavelike interference consequences that supply a quantum computing device its power. Quantum routinely, any error in a qubit’s state can also be thought of as some aggregate of somewhat-flip error that swaps 0 and 1 and a part flip that alterations the section by means of one hundred eighty°.
To appropriate both forms, researchers can expand into another dimension—literally. Whereas a string of three entangled qubits, with two ancillas woven between them, is the smallest array that can realize and correct just a little-flip error, a three-via-three grid of qubits, with eight interspersed ancillas, is the easiest one that can realize and proper each bit-flip and phase-flip mistakes. The logical qubit now resides in an entangled state of the 9 qubits—be thankful you don’t have to write it out mathematically! Stabilizer measurements along one dimension of the grid determine for bit-flip mistakes, while a bit of distinct stabilizer measurements along the different dimension check for phase-flip blunders.
Schemes for pushing into two dimensions fluctuate, counting on the geometric association of the qubits and the particulars of the stabilizer measurements. then again, researchers’ road to error correction is now clear: Encode a single logical qubit in a grid of genuine qubits and show that the constancy of the logical qubit receives superior because the measurement of the grid raises.
Experimenters have already made a birth. for example, in a Nature Physics look at published on 8 June, Andreas Wallraff at ETH Zurich and colleagues proven that they could realize—however now not proper—errors in a logical qubit encoded in a rectangular of 4 qubits with three ancillary qubits.
but experimenters face a frightening challenge. Manipulating individual qubits can introduce errors, and except that error rate falls below a definite stage, then entangling extra qubits with the original one only adds extra noise to the equipment, says Maika Takita, a physicist at IBM. “To exhibit anything else you have to get beneath that threshold,” she says. The ancillary qubits and different error-correction machinery add even more noise, and as soon as those outcomes are blanketed, the integral error threshold plummets extra. To make the scheme work, physicists ought to lower their error cost to less than 1%. “once I heard they accomplished an three% error fee, i believed that changed into wonderful,” Takita says. “Now, it has to be tons lessen.”
Error correction additionally requires fiddling with qubits many times. That makes the system greater annoying than quantum supremacy, which involved measuring all of the qubits just once, says Marissa Giustina, a physicist with Google. Error correction “requires you to measure and measure and measure time and again once again in a cycle, and that needs to be completed directly and reliably,” she says.
besides the fact that children a handful of qubits would suffice to display the precept of quantum error correction, in follow physicists will must control massive numbers of them. To run Shor’s algorithm well adequate to element, say, a host a thousand bits lengthy—roughly the measurement utilized in some internet encryption schemes—they’ll deserve to maintain logical qubits with a part-in-1-billion error fee. That may also require entangling a grid of 1000 genuine qubits to protect a single logical qubit, researchers say, a prospect with a purpose to take generations of bigger and more suitable quantum computing chips.
sarcastically, overcoming that problem would put builders back where they were two decades in the past, when they have been simply surroundings out to make pairs of genuine qubits have interaction to function the quite a few logical operations, or “gates,” crucial for computation. once scientists have begun to grasp error correction, they’ll need to repeat basically each construction to this point in quantum computing with the greater effective however enormously complicated logical qubits. “people say that error correction is the next step in quantum computing; it’s the subsequent 25 steps,” Giustina quips.
Retracing these steps won’t be handy. It’s no longer simply that any logical gate presently involving two qubits will require thousands of them. Worse, another theorem from quantum mechanics states that, no count what scheme researchers use, not all the logical gates will also be without problems translated from particular person physical qubits to diffuse logical ones.
Researchers believe they can sidestep that difficulty if they can initialize all of the qubits in their laptop in selected “magic states” that, extra or much less, do half the work of the troublesome gates. sadly, nonetheless more qubits could be obligatory to produce these magic states. “in case you wish to function anything like Shor’s algorithm, doubtless ninety% of the qubits would need to be dedicated to preparing these magic states,” Roffe says. So a full-fledged quantum desktop, with 1000 logical qubits, might turn out to be containing many thousands and thousands of physical qubits.
Google has a plan to construct simply this sort of laptop within 10 years. initially blush, that sounds preposterous. Superconducting qubits need to be cooled to near absolute zero, in a tool referred to as a cryostat that fills a small room. 1,000,000-qubit laptop conjures visions of a thousand cryostats in an important factory. but Google researchers suppose they can preserve their device compact. “I don’t want to tip my hand, however they accept as true with they figured this out,” Neven says.
Others are taking different tacks. Google’s scheme would require one thousand genuine qubits to encode a single logical qubit as a result of its chip allows only neighboring qubits to engage. If more far away qubits can also be made to have interaction, too, the variety of physical qubits may be a lot smaller, Gambetta says. “If i can achieve that, then these ridiculously scary numbers for the overhead of error correction can come crashing down,” he says. So IBM researchers are exploring a scheme with more far away interconnections among the qubits.
no one is inclined to predict how lengthy it'll take researchers to grasp error correction. however it is time to show to the problem in earnest, Rigetti says. “so far, appreciably the entire researchers who would determine themselves as error correction researchers are theorists,” he says. “We should make this an empirical container with real remarks on precise statistics generated with genuine machines.” Quantum supremacy is so 2019. In quantum computing, error correction is the subsequent scorching factor.
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