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000-086 exam Dumps Source : System x high Performance Servers(R) Technical advocate V4

Test Code : 000-086
Test designation : System x high Performance Servers(R) Technical advocate V4
Vendor designation : IBM
: 43 existent Questions

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IBM System x high Performance

IBM energy gadget S922: Rack Server Overview and insight | killexams.com existent Questions and Pass4sure dumps

See the entire record of precise rack server providers

base line:

The IBM power methods S922 server is designed from the ground up for statistics intensive workloads fancy databases or analytics. it could actually steer a brace of key business information-intensive eventualities, together with mainstream applications, leading-facet HPC workloads and evolving synthetic intelligence (AI) tasks.

consumers in search of principal compute energy may silent comprehend this key fact: POWER9 options are the groundwork of the area’s first and third fastest supercomputers, the U.S. department of energy’s apex and Sierra installations.

IBM power servers tend to believe a better impregnate of entry than x86 machines. although, in keeping with a examine through Quark + Lepton, IBM energy systems running IBM I application believe 60% decrease total cost of ownership than home windows/SQL Server or X86 primarily based Oracle systems. IBM’s pitch is that there are limits to what commodity architectures can do.

however, if you are expecting surges favorite and don’t believe scope for downtime, licensing prices, or occasional crashes a far better commercial enterprise structure may well breathe required.

Product description:

The S922 is a 1 or 2 socket server that presents a big election of core configurations and up to four TB of memory. Chip core speeds on the four-core are 2.8 to 3.8GHz, on the eight core are three.4 to three.9 GHz and on the ten core are 2.9 to 3.eight GHz. the one socket edition gives up to six PCIe ( 2 x Gen4 and 4 x Gen3) slots and the two socket version provides as much as 9 slots (3 extra Gen4 slots). One slot is used by means of a mandatory Ethernet adapter. reckoning on what is connected, up to three of these slots could breathe reserved for other purposes. IBM i is just supported on the 6 cores and 8 core processors and is proscribed to 4 cores of IBM i with a utility tier of P10.

vigour techniques are widespread for their RAS (resiliency, availability, serviceability) points. IBM POWER9-based systems are said to deliver up to 10X sooner bandwidth acceleration and 50% superior recollection bandwidth than related x86 options. They additionally assist the latest in records transfer technologies, together with PCIe four.0 and novel NVLink and OpenCAPI interfaces. This recent server technology comes along with twice the reminiscence footprint than POWER8. alterations within the reminiscence subsystem and using the newest DIMMs enhance price/efficiency.

aspects:

number of processors:

up to 2

Processors supported:

IBM POWER9 Scale-Out SMT8 processor (12-core, 10-core, eight-core, four-core choices)

Cores per processor:

4, eight,10 cores per socket

maximum processor frequency/cache:

3.9 GHz/512k L2 and 10 MB L3

I/O enlargement slots:

the one socket version offers up to six PCIe ( 2 x Gen4 and 4 x Gen3) slots and the two socket edition offers up to 9 slots (three more Gen4 slots). One slot is used by using a mandatory Ethernet adapter. depending on what's connected, up to three of those slots may breathe reserved for different functions.

One front USB three.0 ports – Two rear USB three.0 ports – Two HMC 1 GbE RJ45 ports – One device port with RJ45 connector – 1x USB 3.0 front, 2x USB three.0 rear, 2x HMC 1 GB Eth RJ45 ports, one device port with RJ45 connector, 2x high pace 25 Gb/s ports

optimum reminiscence/# slots/speed:

as much as four TB/32 IS RDIMM slots/as much as 2666 Mhz

optimum Persistent memory:

NA 

Storage controller:

S922/S924 has two interior direct connected storage connectors, an NVMe card and a SAS card

aid:

The electronic capabilities internet portal is a single web entry point that replaces the diverse entry elements historically used to entry IBM internet functions and support. This web portal allows for you to gain simpler entry to IBM supplies for counsel in resolving technical complications. The newly better My programs and premium Search features build it even less complicated for digital service Agent-enabled shoppers to track tackle stock and find pertinent fixes.

My techniques provides useful studies of establish in hardware and utility using tips accrued from the techniques by using IBM electronic provider Agent. experiences are available for any device associated with the client's IBMid. top rate Search combines the office of search and the cost of digital carrier Agent advice, offering superior search of the technical aid knowledgebase.

“it's a transparent election in case you believe already got a longtime IBM AIX atmosphere and necessity to sustain compatibility and maintain performance. There are comparable options now which may breathe capable of net you to three nines for 1/2 the expenses,” observed a Senior supervisor of IT within the manufacturing industry. 

Key markets and spend circumstances:

IBM energy techniques S922 server conveniently integrates into an organization’s cloud & cognitive approach and promises advanced rate performance for mission primary workloads.

POWER9 is designed from the ground up for records intensive workloads fancy databases or analytics

expense:

20 core, 512 GB, $37,222. The utility is expensive.

“it's a product with extreme efficiency, efficiency and monetary indices in the IT market,” mentioned an applications Engineering within the schooling business. "Deployment is very handy, but took greater than three months. It proved low-priced in the long run.”

Server

IBM vigour S922

Max Processor Frequency

three.9 GHz/512k L2 and 10 MB L3

Max Persistent memory

N/A

form ingredient

2U

Max Processors

2 POWER9 Scale-Out SMT8

Max memory

4 TB

Max Storage

four TB

rate

$37,222

Key Differentiator

properly processing power


IBM Bets $2B in quest of 1000X AI Hardware performance boost | killexams.com existent Questions and Pass4sure dumps

For now, AI methods are primarily laptop researching-based and “slender” – powerful as they are by today’s specifications, they’re confined to performing a brace of, narrowly-described tasks. AI of the next decade will leverage the enhanced energy of abysmal discovering and develop into broader, fixing a improved array of more complicated problems. in addition, the popular-aim technologies used these days for AI deployments will net replaced by way of a technology stack that’s AI-selected and exponentially sooner – and it’s going to elect some huge cash.

IBM’s Mukesh Khare

in quest of to elect focus stage in AI’s unfolding, IBM – in combination with ny situation and a few know-how heavies – is investing $2 billion in the IBM research AI Hardware core, concentrated on constructing next era AI silicon, networking and manufacturing with a view to, IBM pointed out, bring 1,000x AI efficiency effectivity growth over the subsequent decade.

“nowadays, AI’s ever-increasing sophistication is pushing the boundaries of the trade’s present hardware techniques as users locate extra effortless methods to comprise a considerable number of sources of statistics from the side, internet of issues, and extra,” stated Mukesh Khare, VP, IBM research Semiconductor and AI Hardware neighborhood, in a weblog asserting the assignment. “…nowadays’s programs believe achieved more advantageous AI efficiency by means of infusing computing device-studying capabilities with high-bandwidth CPUs and GPUs, really estimable AI accelerators and excessive-performance networking equipment. To retain this trajectory, recent thinking is needed to accelerate AI efficiency scaling to suit to ever-expanding AI workload complexities.”

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

IBM pointed out the middle might breathe the nucleus of a recent ecosystem of research and industrial companions participating with IBM researchers. partners introduced today consist of Samsung for manufacturing and research, Mellanox technologies for high-efficiency interconnect equipment, Synopsys for application systems, emulation and prototyping, and IP for developing high-efficiency silicon chips, and semiconductor machine organizations utilized substances and Tokyo Electron.

Hosted at SUNY Polytechnic Institute, Albany, huge apple, in collaboration with neighboring Rensselaer Polytechnic Institute focus for Computational innovations, IBM said the enterprise and its companions will “enhance more than a few technologies from chip stage instruments, materials, and architecture, to the application supporting AI workloads.”

big Blue spoke of analysis at the core will focus of attention on overcoming current computing device-researching boundaries through approaches that consist of approximate computing via Digital AI Cores and in-memory computing via Analog AI Cores. These technologies will provide the thousand-fold raises in performance efficiency required for complete attention of abysmal learning AI, in response to IBM.

“Our analog AI cores are section of an in-memory computing approach in efficiency effectivity which improves via suppressing the so-known as Von Neuman bottleneck through eliminating information transfer to and from memory,” illustrious IBM. “Deep neural networks are mapped to analog pass point arrays and recent non-unstable material characteristics are toggled to shop network parameters within the trail aspects.”

“A key belt of research and evolution will breathe techniques that meet the calls for of abysmal studying inference and training processes,” Khare observed. “Such systems present colossal accuracy advancements over more benchmark computing device getting to know for unstructured facts. these stern processing demands will grow exponentially as algorithms develop into more advanced so as to deliver AI methods with improved cognitive abilities.”

Khare mentioned the analysis middle will host R&D, emulation, prototyping, trying out and simulation activities for brand recent AI cores peculiarly designed for practicing and deploying superior AI models, together with a verify bed in which contributors can demonstrate innovations in precise-world applications. really estimable wafer processing for the middle could breathe executed in Albany with some advocate at IBM’s Thomas J. Watson analysis focus in Yorktown Heights, recent york.


Settling In With IBM i For The long Haul | killexams.com existent Questions and Pass4sure dumps

February eleven, 2019 Timothy Prickett Morgan

If nothing else, the IBM i platform has exhibited superb durability. One may even utter legendary sturdiness, if you necessity to elect its historical past the entire manner returned to the equipment/three minicomputer from 1969. this is the precise starting factor in the AS/400 family unit tree and here's when huge Blue, for very sound felony and technical and advertising and marketing motives, determined to fork its products to maneuver the exciting needs of big companies (with the equipment/360 mainframe and its observe-ons) and miniature and medium companies (starting with the equipment/3 and poignant on through the system/34, system/32, system/38, and device/36 in the 1970s and early Nineteen Eighties and passing throughout the AS/400, AS/400e, iSeries, gadget i, after which IBM i on punch systems platforms.

It has been an extended elope certainly, and a lot of customers who've invested in the platform began means back then and there with the early types of RPG and moved their purposes ahead and adjusted them as their organizations developed and the depth and breadth of corporate computing modified, relocating on up through RPG II, RPG III, RPG IV, ILE RPG, and now RPG free form. Being on this platform for even three many years makes you a relative newcomer.

there is a longer elope ahead, since they accept as right with that the corporations that are silent operating IBM i techniques are the existent diehards, the ones who don't believe any purpose of leaving the platform and that, at the least according to the survey facts we've been privy too, are desiring to proceed investing in, or even expand their investments in, the IBM i platform.

to date, they don't look to breathe in a recession and heaven willing there usually are not one, so the priorities that IBM i retail outlets believe don't look to breathe those that they'd a decade in the past entire the way through the peak of the awesome Recession. back then, as changed into the case in just about entire IT organizations, IBM i shops were hunkering down and had been trying to crop costs in entire ways possible, including deferring tackle improvements and migrations as well as cutting lower back on other initiatives. best 29 percent of the 750 IBM i retail outlets that participated in the 2019 IBM i industry Survey, which HelpSystems did again in October 2018, were involved about cutting back IT spending. this is a remarkably low stage, and i feel is indicative of how quite strong the monetary system is – excepting one of the vital suits and begins they saw at the conclusion of 2018 and right here in early 2019 that build us frightened and will delivery placing power on issues. here are the commandeer concerns as culled from the survey:

dealing with the growth in facts and in deciding the analytics to chew on that records ranked a bit bit greater on the 2019 IBM i market Survey than did cutting back prices, and that i feel over the lengthy haul these concerns will spin into extra censorious than modernizing functions and dealing with the IBM i scholarship shortages which are a perennial breathe anxious. both of these issues are being solved as recent programmers and recent tackle to build recent interfaces to database functions are becoming extra general and as applied sciences similar to free benign RPG, which appears more fancy Java, Python, and Hypertext Preprocessor, are being extra broadly deployed and, importantly, can likewise breathe picked up extra straight away by using programmers skilled with these different languages.

Given the nature of the customer base, it appears unlikely to me that protection and extreme availability will now not proceed to breathe primary considerations, despite the fact that the IBM i platform is among the many most at ease systems on the earth (and not simply because it is vague, however because it is quite tricky to hack) and it has a number of high availability and catastrophe restoration tackle (from IBM, Syncsort, Maxava, and HelpSystems) obtainable for those that want to double up their programs and give protection to their purposes and records. The bar is commonly bigger than benchmark backup and restoration for many IBM i stores in the banking, coverage, manufacturing, and distribution industries that dominate the platform. These organizations can’t believe protection breaches, and they can’t believe downtime.

there is a astonishing amount of steadiness in the IBM i customer basis that they consider, at this element, is reflective within the stability of the IBM i platform and big Blue’s personal credit that it wants a vigorous IBM i platform to believe an mediocre match vigour methods enterprise. they entire comprehend that the vigour programs hardware enterprise has simply grew to become in five quarters of revenue boom – anything they mentioned recently in constructing their own earnings model for the energy methods enterprise – but what they did not breathe sensible of, and what breathe positive to recognize, is that in the 2nd and third quarters of 2018, the IBM i component of the business grew greatly sooner than the benchmark vigour programs business, and the simplest intent that this did not spin up in the closing quarter of 2018 is that revenue of IBM i machinery in q4 2017 became fairly mighty and represented a really tough examine. The point is, the IBM i enterprise has been raising the energy programs classification average. (These guidelines in regards to the IBM i company Come compliments of Steve Sibley, vice president and offering manager of Cognitive techniques at IBM.)

IBM’s personal economic steadiness of the vigour platform – which has been bolstered by way of a trail into Linux clusters for analytics and high performance computing simulation and modeling in addition to through the adoption of the HANA in-memory database with the aid of SAP consumers on big iron machines together with Power8 and now Power9 programs – helps IBM i shoppers assume extra assured in investing within the current IBM i platform. The fresh proof from a brace of different surveys, now not just the one completed by using HelpSystems each year, means that companies are through and massive either continuing to build investments within the platform and even in some instances are planning to enlarge their spending on the IBM i platform in 2019.

As you could see, the pattern of investment plans for the IBM i platform, as proven in the chart above, has no longer modified very tons at entire in the past four years. it's a remarkably stable pattern with but a cramped wiggling here and there that can likewise now not even breathe statistically big. simply under 1 / 4 of IBM i stores believe reported in the past four years that they purpose to enlarge their investment in the platform in each year, and simply beneath half utter that they are maintaining regular. This doesn't value that the same corporations, 12 months after yr, are investing more and different organizations are staying pat, yr after 12 months. it is far more possible that each handful of years – more fancy 4 or 5 – clients ameliorate their programs and extend their capacity, and they then sit tight. The anticipate yourself is that the rupture up isn’t displaying a long way fewer groups investing and far greater sitting tight. That greater than a tenth of the retail outlets don’t understand what their purpose is as each and every prior 12 months comes to a nearby is a bit of disturbing, nevertheless it is unaffected and suggests that a estimable portion of outlets bear other priorities apart from hardware and operating system improvements. they believe talked about this before and they will utter it again: They believe that the individuals who respond to surveys and read weekly publications focused on the IBM i platform are essentially the most lively retail outlets – the ones greater prone to dwell exceptionally latest on hardware and utility. So the tempo of adoption for brand recent applied sciences, and the fee of funding, should breathe higher than within the specific base, much of which doesn't alternate much in any respect.

So if they needed to alter this statistics to elect on the whole base, there might breathe some distance fewer sites that are investing greater funds, much more agencies that are sitting tight, and perhaps fewer websites that are contemplating relocating off the IBM i platform. I suppose the distribution of data is likely anything fancy 10 % of outlets believe no thought what they're doing investment sapient with IBM this year, 5 percent are brooding about relocating some or entire of their applications to a further platform, probably 10 percent are investing more this yr, and the ultimate seventy five p.c are sitting tight. here is only a wager, of direction. so far as they will tell, the fee of attrition – what number of sites they definitely lose every 12 months – just a tad over 1 percent. So the expense of circulation of applications off the platform, or incidences of unplugging IBM i databases and purposes, may additionally no longer breathe any set nearby as high in the common basis because the records above suggests. what's alarming, possibly, is that the cost of poignant some or entire purposes off the platform is balanced in opposition t those who utter they'll enlarge investments. perhaps these are hopeful survey takers, and people who feel it is effortless to movement locate it is not and people who believe they're going to learn the funds to invest will no longer.

What they execute know is that if the expense of utility attrition changed into anywhere nearby as high as these surveys imply, then the IBM i company would no longer breathe turning out to be, but shrinking. And they realize it isn't shrinking, so they assume there is a disconnect between planning and reality, both on the upside and the downside.

if you drill down into the records for the 2019 IBM i industry Survey, there were 13 p.c of outlets that illustrious they would breathe poignant some functions to a brand recent platform, and yet another 9 p.c that said they had been going to stream entire of their purposes off IBM i. (This quantity is in line with the simultaneous ALL400s survey finished by way of John Rockwell.)

Anyway, respectable estimable fortune with that.

Porting functions from one platform to an extra, of purchasing a brand recent suite on that recent platform, is an quite elaborate task. It is not fancy attempting to trade a weary whereas driving down the highway, as is a common metaphor, however fairly fancy trying to elect the weary off one car relocating down the toll road and setting up it on one other automobile riding beside it within the adjoining lane with out crashing both vehicle or smashing into any one else on the highway. Optimism abounds, however when push involves shove, very few corporations are attempting this benign of maneuver, and after they do, it is usually because there's a company mandate, more instances than not caused by way of a merger or acquisition, that pits any other platform in opposition t IBM i working on vigour techniques. organizations that utter they are making such a stream off IBM i are sanguine for their personal personal factors, perhaps, but they aren't necessarily simple about how lengthy it may take, what disruption it'll can charge, and what most excellent advantage, if any, could breathe realized.

if you execute the maths on the chart above, eight-tenths of the bottom has no view how lengthy a movement will take, one other 1.7 percent thinks it's going to elect greater than five years, and three p.c utter it'll elect between two years and 5 years. only three.four p.c of the overall basis utter they can execute it in under two years. They suppose entire of these numbers are positive, and the organizations who could readily depart OS/400 and IBM i already did a very long time ago and people that are remain believe a harder time, now not an easier time, relocating. If this believe been not true, the IBM i basis could breathe a hell of a whole lot smaller than the 120,000 consumers they believe are obtainable, in accordance with what huge Blue has advised us in the past. here is the contrast between terror or pressure or culture and the reality of making an attempt to circulation a company off one platform and onto an extra. These strikes are entire the time an dreadful lot more durable than they look on the entrance conclusion, and they suspect many of the advantages additionally don’t materialize for those that execute jump structures.

at the ordinary attrition expense counseled by using this survey information – 9 percent circulate off the platform in someplace between three hundred and sixty five days and greater than 5 years, with most businesses no longer being able to discern greater than five years into the longer term this is a dapper trick – the installed basis would reduce dramatically. it is hard to pretense how far because of the huge selection of timeframes in the survey. If it turned into 9 percent of the basis within two years – designation it four.5 p.c of the bottom per year – then inside a decade the benchmark basis would reduce from one hundred twenty,000 IBM i sites worldwide down to about seventy two,000. this could dramatic indeed. but at a 1 % attrition fee per 12 months, the basis remains at 107,500 entertaining purchasers (not websites and not installed machines, both of that are greater) with the aid of 2029. They assume there's each possibility that the attrition cost will in fact gradual and drop under 1 percent as IBM demonstrates dedication to the vigour techniques platform and its IBM i working system. There are at entire times some recent shoppers being added in recent markets, to build certain, however the bleed cost (in spite of the fact that it is small) is silent probably an order of magnitude better than the feed price.

once they execute deem about making the movement, IBM i retail outlets know precisely the set they want to go, and this reply has been step by step altering through the years: Linux as an alternative election to IBM i is on the upward thrust and windows Server as an alternative is on the wane. in the latest survey, fifty two percent of the agencies that referred to they were poignant entire or some of their purposes to yet another platform said they believe been picking windows Server, whereas 34 % selected Linux. This displays the relative popularity of home windows Server and Linux in the datacenters of the belt at tremendous, and might breathe tipped just a bit greater heavily towards Linux in comparison to the relaxation of the area. curiously, 10 percent of those polled who spoke of they had been poignant had been AIX systems, and a further four percent had been going upscale to gadget z mainframes – as unlikely as this may additionally seem. platforms are likely to roll downhill; they execute not continually challenge gravity fancy that.

The factor about such surveys is that they exhibit intent, now not motion. They commonly intend to execute a lot more than they definitely can accomplish, and poignant platforms after spending a long time of build up competencies is not constantly a very sensible rush except the platform is in precise quandary – fancy the Itanium programs from Hewlett Packard business operating OpenVMS or HP-UX or the HP 3000s running MPE or the Sparc techniques from Oracle working Solaris. These had been once first rate systems with huge establish in bases and colossal profits streams, however now, IBM is the closing of these Unix and proprietary platforms with its power systems line. And it's with the aid of a ways the biggest and for positive the only 1 showing any increase.

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The IBM i basis Is able to rush On Up

investment And Integration warning signs For IBM i

safety nonetheless Dominates IBM i dialogue, HelpSystems’ 2018 Survey reveals

The IBM i basis not As Jumpy because it Has Been

The Feeds And Speeds Of The IBM i Base

IBM i Priorities For 2017: Pivot To protection

IBM i developments, issues, And Observations

IBM i Survey gets improved As Numbers develop

where execute these IBM i Machines Work?

finding IBM i: A game Of forty Questions

it is time to declare Us What you're as much as

IBM i marketplace Survey: The consequence Of Being Earnest

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IBM i market Survey Fills in the Blanks


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System x high Performance Servers(R) Technical advocate V4

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When Databases Meet FPGA: Achieving 1 Million TPS With X-DB Heterogeneous Computing | killexams.com existent questions and Pass4sure dumps

X-Engine is a recent generation storage engine developed by Alibaba Database Department and is the basis of the distributed database X-DB. To achieve 10 times the performance of MySQL and 1/10 the storage cost, X-DB combines software with hardware to build complete spend of the most cutting-edge technical advantages in both software and hardware fields.

FPGA acceleration is their first attempt in the custom computing field. At present, the FPGA-accelerated X-DB has been topic to small-scale online grayscale release. FPGA will assist X-DB in the 6.18 and Double 11 shopping carnivals this year and will meet Alibaba's business departments' high database performance requirements.

Overview of Alibaba's X-Engine

Owning the world's largest online transaction website, Alibaba's OLTP (online transaction processing) database system needs to satisfy high-throughput service requirements. According to their statistics, several billion records net written into their OLTP database system on a daily basis. During the 2017 Double 11 (Singles' Day) shopping carnival, the system's peak throughput reached 10 million TPS (transactions per second). Alibaba's business database systems mainly believe the following characteristics:

  • High transaction throughput and low latency in write and read operations.
  • Write operations build up a relatively high balance in comparison to that of traditional databases; the read to write workload ratio usually is more than 10:1. However, the number for Alibaba's transaction system reached 3:1 on the day of the 2017 Double 11 shopping carnival.
  • Data access hotspots are relatively concentrated. A newly written data record will breathe accessed mainly (99%) within the first seven days, and the possibility it may breathe accessed later is extremely low.
  • To meet Alibaba's stringent requirements on performance and cost, they believe designed a recent storage engine; it is called X-Engine. They believe used many cutting edge database technologies in X-Engine; these comprise highly-efficient recollection index structures, asynchronous write assembly-line processing mechanism, and optimistic concurrency control for in-memory databases.

    To achieve the best write performance and facilitate the separation of artic and warm data for tiered storage, X-Engine has borrowed the design of LSM-Tree. X-Engine maintains multiple memtables in its memory. It appends entire newly written data to these memtables, rather than directly replacing existing records. As the data storage is relatively large, it is impossible to store entire data in memory.

    When data in recollection reaches a specified volume, they flush it to the persistent storage to figure an SSTable. To reduce latency in read operations, X-Engine regularly schedules compaction tasks to compact SSTables in the persistent storage. X-Engine merges key-value pairs in multiple SSTables by keeping only the latest version of key-value pairs if multiple versions exist (all key-value pair versions currently referenced by transactions will likewise breathe kept).

    Based on the characteristics of data access, X-Engine applies tiered storage to persistent data, where they store lively data in relatively high data layers, and merge less lively data (seldom accessed) with base-layer data and store it in the base-layer. It compresses base-layer data at a high compression rate and migrates it to storage media featuring big capacity but the relatively low cost (such as SATA HDDs) to achieve the goal of storing a big quantity of data at a relatively low cost.

    In this case, tiered storage creates a recent problem: the system must frequently compact data, and the larger number of data writes requires more frequent compaction processes. Compaction is a compare and merge process which requires high consumption of CPU and storage I/O. In high-throughput write cases, a big number of compaction operations will occupy a big number of system resources. This can surely antecedent the performance of the entire system to drop tremendously thus leading to a huge impact on the application system.

    The completely recent X-Engine has extraordinary multi-core expansion capability to achieve very high performance. Its front-end transaction lonesome can almost completely consume entire CPU resources, and it has a much higher resource using efficiency than InnoDB. They believe shown the comparison between the two in the following figure:

    Image title

    At such a performance level, the system does not believe any other resources for compaction operations; otherwise, performance levels will drop.

    Based on their testing results, in DbBench benchmark's write-only scenario, the system periodically suffers from performance jitter. When a compaction chore occurs, the system performance drops by more than 40%, and when the compaction chore ends, the system performance returns to normal. They believe shown this conduct in the following figure:

    Image title

    However, if they execute not conduct compaction promptly, the accumulation of multi-version data can seriously finger the read operations.

    To solve the performance jitter caused by compaction, academic experts believe establish forward many structures such as VT-tree, bLSM, PE, PCP, and dCompaction. Although these algorithms can optimize the compaction performance across multiple aspects, they cannot reduce consumption of CPU resources by compaction. Based on germane research statistics, when using SSD storage devices, the computing operations of compaction in the system consumes approximately 60% of computing resources. Therefore, no matter what optimizations they implement for compaction in the software layer, for entire LSM tree-based storage engines, performance jitter caused by compaction is always an Achilles' heel.

    Fortunately, special hardware opens a recent door for solving performance jitter caused by compaction. In fact, it has become a trend to spend special hardware in solving traditional databases' performance bottlenecks. They believe already offloaded database operations such as Select and Where to FPGA, and more complicated operations such as Group By are under research. However, the current FPGA acceleration solutions believe a brace of drawbacks:

  • The current acceleration solutions are designed for the SQL layer; FPGA is generally placed between storage and host and is used as a filter. Although, researchers believe made numerous attempts to spend FPGA to accelerate the OLAP system, the FPGA acceleration design for the OLAP system remains a challenge.
  • While FPGA's chip size is getting smaller and smaller, FPGA's internal errors such as single event upset (SEU) pose greater and greater threats to FPGA reliability. For a single chip, the probability of internal oversight is 3-5 years. Therefore, the fault tolerance mechanism design becomes vitally primary for systems in necessity of large-scale availability.
  • To ease the impact of compaction on X-Engine's system performance, they believe used an asynchronous hardware device FPGA, rather than the CPU to complete the compaction operation. This approach is crucial for a storage engine that satisfies stringent service requirements by maintaining the overall system performance at a high-level and avoiding performance jitters. Here are the major design features:

  • Highly efficient design and implementation of FPGA compaction: Using streamlined compaction operations, FPGA compaction achieves a processing performance 10 times the CPU single-thread processing performance
  • Hybrid storage engine's asynchronous scheduling logic design: As FPGA can complete compaction's link requests in milliseconds, using a traditional synchronous scheduling mode will cloak a big number of compaction threads and antecedent heavy thread-switching cost. Through asynchronous scheduling, they believe successfully reduced the thread-switching cost and improved the system's engineering availability.
  • Fault tolerance mechanism design: As limits of entered data and FPGA internal errors may antecedent a rollback of some compaction tasks, to ensure data integrity, entire tasks that believe been rolled back by FPGA will breathe re-executed by the equivalent CPU compaction threads. The fault tolerance mechanism design as described in this article meets Alibaba's actual business requirements and avoids FPGA's internal instability.
  • X-Engine Compaction

    X-Engine's storage structure contains one or multiple recollection buffer areas (memtable), and multilayer persistent storage L0, L1... Each layer contains multiple SSTables.

    Image title

    When memtable is full, it turns into an immutable memtable and then flushes to an SSTable to L0. Each SSTable contains multiple data blocks and one index cloak to index the data block. When it reaches the maximum number of L0 files, it triggers the merge of SSTables that believe the overlapped key ranges; this process is called compaction. Likewise, when they achieve the maximum number of SSTables at a layer, it merges with lower layer data. In this way, artic data constantly flows downward while warm data remains at a relatively higher layer.

    We can specify a scope of key-value pairs that merge during a compaction process and this scope may hold multiple data blocks. Generally, a compaction process involves merging data blocks between two adjacent layers. However, they necessity to pay special attention to compaction tasks between L0 and L1. This is because as SSTables in L0 directly flushes from the memory, keys of SSTables in this layer may net overlapped. Therefore, a compaction chore between L0 and L1 may involve merging multiple data blocks.

    Image title

    For read operations, X-Engine needs to search for the required data from entire memtables. If it fails to find the data in memtables, it searches in the persistence storage, from higher to lower layers. As a result, timely compaction operations not only truncate the read path but likewise save the storage space. However, this mode uses a lot of system computing resources and causes performance jitter. This is an imperative problem that X-Engine must solve.

    FPGA Accelerated Database

    From the perspective of the existing FPGA accelerated databases' status quo, they can divide FPGA accelerated database architectures into two types; the bump-in-the-wire design and the hybrid design. In the early stage, because of the FPGA card's insufficient recollection resources, the former type of architecture is relatively popular. In this architecture, they set FPGA on the storage data path and spend the host as a filter. The advantage is that it requires zero data replication, while the drawback is that the acceleration operation must breathe a section of the streamlined process, therefore making it not supple enough in terms of the design method.

    The latter architecture design uses FPGA as a coprocessor, where they believe connected FPGA to host via PCIe and spend the DMA mode for data transmission. As long as the offloading computation is intensive enough, data transmission costs are acceptable. The hybrid architecture design allows more supple offloading methods. For complicated operations such as compaction, data transmission between FPGA and host is necessary. Therefore, they believe used the hybrid architecture design for hardware acceleration in their X-Engine.

    Image title

    System Design

    In traditional LSM-tree-based storage engines, CPU is amenable for handling benchmark user requests, as well as the scheduling and execution of compaction tasks. In other words, CPU is both the producer and consumer of compaction tasks. However, in a CPU-FPGA hybrid storage engine, CPU is only amenable for producing and scheduling compaction tasks. In this method, they necessity to offload the execution of compaction tasks to the special hardware (FPGA).

    Image title

    For X-Engine, handling of benchmark user requests is similar to that of LSM-tree-based storage engines:

  • A user submits a request to operate on a specified KV pair (Get/Insert/Update/Delete). In the case of a write operation, a recent record appends to a memtable.
  • When a memtable reaches its maximum size, it turns into an immutable memtable.
  • The immutable memtable then turns into an SSTable and flushes to the persistent storage.
  • When L0 reaches the maximum number of SSTables, compaction gets triggered. They can divide offloading of a compaction chore into the following steps:

  • CPU splits Load SSTables (that necessity to breathe compacted from the persistent storage) into multiple compaction tasks at the granularity of data blocks following the metadata, and pre-allocates recollection space for computation result of each compaction task. Consequently, it pushes each successfully created compaction chore into the chore Queue for FPGA to execute.
  • CPU reads the status of Compaction Units on FPGA and allocates compaction tasks from the chore Queue to available Compaction Units.
  • It transmits Input data to FPGA's DDR via DMA.
  • A Compaction Unit executes the compaction chore and transmits the computation result via DMA back to the host; it attaches a recrudesce code to testify the status of this compaction chore (fail or success). Next, it pushes the compaction results of finished tasks to the Finished Queue.
  • The CPU checks the compaction result status in the Finished Queue. If a compaction chore fails, the CPU executes it again.
  • It flushes the compaction results to storage.
  • Detailed Design FPGA-Based Compaction

    Compaction Units (CU) are the basic unit for FPGA to execute compaction tasks. An FPGA card can set multiple CUs, and each CU is composed of the following modules:

    Image title

    1. Decoder: In X-Engine, they store a KV in the data cloak after compression and encoding. The primary office of the Decoder module is to decode KV pairs. Each CU contains 4 Decoders, and a CU advocate a compression chore of a maximum of 4 KV pairs. They necessity to split the compression tasks that require compression of more than 4 KV by the CPU. Based on their assessment, most compression tasks involve less than 4 KV pairs. They believe placed 4 Decoders based on their considerations of performance and hardware resources. Comparing the configuration with 2 Decoders, we've increased 100% hardware consumption but obtained 300% performance improvement.

  • KV Ring Buffer: KV pairs decoded by the Decoder module net temporarily stored in KV Ring Buffer. Each KV Ring Buffer maintains a read indicator (maintained by the Controller module) and a write indicator (maintained by the Decoder module). KV Ring Buffer maintains three signals to testify the current status: FLAG_EMPTY, FLAG_HALF_FULL, and FLAG_FULL. If FLAG_HALF_FULL is at a low level, the Decoder module will continue decoding KV pairs. Conversely, the Decoder module will halt decoding KV pairs until downstream consumers in the pipeline believe consumed the decoded KV pairs.
  • KV Transfer: This module is amenable for transmitting keys to Key Buffer. Because merging KV pairs only involve comparison of key values, the values execute not necessity to breathe transmitted. They can track the currently compared KV pairs by using the read indicator.
  • Key Buffer: This module stores keys of each KV pair that necessity to breathe compared. When entire keys that necessity to breathe compared believe been transmitted to the Key Buffer, the Controller notifies the Compaction PE to compare them.
  • Compaction PE: The Compaction Processing Engine (compaction PE) is amenable for comparing key values in Key Buffer. Comparison results are sent to the Controller, and then the Controller sends a notice to KV Transfer to transmit the corresponding KV pair to the Encoding KV Ring Buffer for the Encoder module to encode them.
  • Encoder: The Encoder module is amenable for encoding KV pairs from the Encoding KV Ring Buffer into a data block. If the data cloak reaches its maximum size, then the current data cloak gets flushed to DDR.
  • Controller: The Controller acts as a coordinator in CU. Although the Controller is not a section of the compaction pipeline, it plays a key role in each step of the compaction pipeline design.
  • A compaction process contains three key steps: decoding, merging, and encoding. The most significant challenge for designing a proper compaction pipeline is that the execution time for each step varies significantly. For example, because of parallel processing, the throughput of the decoder module is much higher than the encoder module. Therefore, they must suspend some quick modules to wait for downstream modules silent in the pipeline. To match the throughput differences in each of the pipeline's modules, they believe designed a Controller module to coordinate different steps in the pipeline. An additional capitalize of this design is that it decouples each module in the pipeline and enables more supple evolution and maintenance during engineering implementation.

    Image title

    When integrating FPGA compaction into X-Engine they hope to believe independent CU throughput performance; the baseline of the experiment is the CPU.

    Single-core compaction thread (Intel(R) Xeon(R) E5-2682 v4 CPU with 2.5 GHz)

    Image title

    We can draw the following three conclusions from the experiment:

  • n entire KV lengths, FPGA compaction has a higher throughput than that of a single-thread CPU; this proves the feasibility of compaction offload;
  • With the enlarge of KV lengths, FPGA compaction throughput reduces. This is because the lengths of bytes that necessity to breathe compared believe increased, resulting in the enlarge of cost for comparison.
  • The acceleration rate (FPGA throughput / CPU throughput) increases with the value length. This is because when the KV length is short, it requires frequent communication and status checking among different modules; this means a relatively high cost in comparison with benchmark pipeline operations.
  • Asynchronous Scheduling Logic Design

    Because a link request in FPGA is completed in milliseconds, using the traditional synchronous scheduling mode will antecedent high thread switching costs. Based on FPGA's characteristics, they believe redesigned an asynchronous scheduling compaction method, where:

  • The CPU is amenable for structure compaction tasks and pushing them into the chore Queue.
  • A thread pool is maintained to dispense compaction tasks to specified CUs.
  • When a compaction chore is finished, it will breathe pushed to the Finished Queue.
  • The CPU will then check the chore execution status, and schedule CPU compaction threads to re-execute the failed compaction tasks.
  • Asynchronous scheduling significantly reduces the thread-switching cost of CPU.

    Image title

    Fault Tolerance Mechanism Design

    For FPGA compaction, the following three reasons can lead to the failure of compaction task:

  • Data gets damaged during the transmission process: cipher the CRC values of data before and after transmission, and compare the values. If these two CRC values are inconsistent, it means that the data is damaged.
  • FPGA internal errors (bit upset): To solve this problem, they believe attached an additional CU to each CU. They can compare the computation results of both CUs and any inconsistency in the results will testify that a bit upset oversight has occurred.
  • Input data of a compaction chore is invalid: To facilitate FPGA compaction design, they believe set a restriction on the length of KVs. The compaction tasks for KVs that exceed the maximum allowable length are identified as invalid tasks.
  • To ensure the data is correct, the CPU will conduct computation again on entire failed tasks. As they mentioned earlier in the fault tolerance mechanism, they believe addressed a miniature section of compaction tasks that exceed the limits and believe avoided the risk of FPGA internal errors.

    Image title

    Experiment Results Lab environment
  • CPU: 64-core Intel (E5-2682 v4, 2.50 GHz) processor
  • Memory: 128 GB
  • FPGA card: Xilinix VU9P
  • memtable: 40 GB
  • block cache 40 GB
  • We compared the performance of two storage engines:

  • X-Engine-CPU: compaction operation executed by CPU
  • X-Engine-FPGA: compaction offloaded to FPGA for execution
  • DbBench

    Image title

    Result analysis:

  • n a write-only scenario, X-Engine-FPGA sees a 40% throughput increase. From the performance curve they can declare that when compaction begins, the performance of X-Engine-CPU drops by 1/3.
  • FPGA compaction has a higher throughput and is faster, so the read path is shortened faster. Therefore, in the read/write hybrid scenario, X-Engine-FPGA throughput increases by 50%.
  • The throughput in the read/write hybrid scenario is smaller than that of the write-only scenario. Read operations require access to data stored in persistent layers which brings in I/O cost and affects the overall throughput performance.
  • These two performance curves delineate two different compaction statuses. In the left figure, the system performance jitters periodically signification that the compaction operation is competing with benchmark transaction handling threads for CPU resources; while in the right figure, X-Engine-CPU's performance maintains at a low-level signification that the compaction quicken is smaller than the write speed, causing accumulation of SSTables. Compaction tasks are topic to constant scheduling at the backend.
  • CPU schedules the Compaction tasks. That's why X-Engine-FPGA's performance likewise jitters and the curve is not smooth.
  • YCSB

    Image title

    Result analysis:

  • On YCSB benchmark, due to the influence of compaction, X-Engine-CPU's performance decreases by approximately 80%. However, for X-Engine-FPGA, its performance only sees a fluctuation of 20% due to the influence of the compaction scheduling logic.
  • The check-unique logic introduces read operations. With the enlarge in pressure testing time, the read path becomes longer, and the performance of both storage engines decreases with time.
  • In the write-only scenario, X-Engine-FPGA's throughput increases by 40%. However, with the enlarge in the read/write ratio, the acceleration effect of FPGA Compaction decreases gradually. When the read/write ratio becomes higher, the write pressure becomes smaller, and the SSTable accumulation becomes slower thus reducing the number of threads that maneuver compaction tasks. Therefore, X-Engine-FPGA sees a more obvious performance enlarge in write-intensive workloads.
  • With the enlarge in the read/write ratio, the throughput increases. When write throughput is smaller than that of the KV interface, the cache miss ratio is relatively low, thus avoiding frequent I/O operations. With the enlarge in the balance of write operations, the number of threads that maneuver compaction tasks likewise increases, thus reducing the system's throughput capability.
  • Image title

    Result analysis:

  • With FPGA acceleration, X-Engine-FPGA's performance improves by 10%–15% when the number of connections is increased from 128 to 1024. When the number of connections increases, the throughput of both systems gradually decreases because of the lock competition of hotspot rows increases.
  • TPC-C's read/write ratio is 1.8 : 1. In the experiment, under the TPC-C benchmark, more than 80% of CPU resources were consumed on SQL resolution and lock competition of hotspot rows. The actual write pressure was not very heavy. Based on their observation in the experiment, the number of threads that execute compaction tasks in the X-Engine-CPU is no more than three (a total of 64 cores). Therefore, FPGA's acceleration effect is not as obvious as the previous instances.
  • SysBench

    We believe included testing for InnoDB in this experiment (buffer size = 80 GB)

    Image title

    Result analysis:

  • X-Engine-FPGA improves more than 40% of throughput performance. Because SQL resolution consumes a big number of CPU resources, the throughput of DBMS is smaller than that of the KV interface.
  • X-Engine-CPU reaches a equilibrium at a low level. Because the compaction quicken is slower than the writing speed, SST files are accumulated, and compaction is constantly scheduled.
  • X-Engine-CPU's performance is twice that of InnoDB, which shows the advantage of LSM tree-based storage engines in a write-intensive scenario;
  • In comparison with the TPC-C benchmark, Sysbench is more similar to Alibaba's existent transaction scenario. For a transaction system, most queries are data insertion queries and simple point queries and seldom involve scope queries. A decrease in hotspot row conflicts causes the number of resources consumed in the SQL layer to decrease. During the experiment, they believe observed that for X-Engine-CPU, when more than 15 threads are used to execute compaction tasks, the performance improvement brought by FPGA acceleration is very obvious.
  • Conclusion

    In this article, the X-Engine storage engine accelerated by FPGA brings 50% performance improvement for the KV interface, and 40% performance improvement for the SQL interface. With the decrease in the read/write ratio, FPGA's acceleration effect becomes more obvious, thus signification that FPGA compaction acceleration is suitable for write-intensive workloads. This is consistent with the purpose of the LSM-tree design. Also, they believe avoided FPGA's internal defects by designing a fault tolerance mechanism, and we've finally created a high-availability CPU-FPGA hybrid storage engine that meets Alibaba's existent service requirements.

    It is the first existent project that uses a heterogeneous computing device introduced by X-DB to accelerate core database functions. Based on their experiences, FPGA can completely meet the computing demands raised by X-Engine's compaction tasks. At the same time, they believe been researching to schedule more suitable computing tasks to FPGA for execution, such as compression, BloomFilter generation, and SQL relate operators. At present, the R&D for the compression office is completed, and it will breathe built into a set of IP together with Compaction to effect data compaction and compression operations simultaneously.

    X-DB FPGA-Compaction hardware acceleration is an R&D project completed by three parties; these parties are respectively the Alibaba Database Department database kernel team, the Alibaba Server R&D Department custom computing team, and Zhejiang University. Xilinx's technical team has likewise made mighty contributions to the success of this project. They hereby extend their gratitude to them. They will post X-DB online for public beta this year. You will then breathe able to undergo the significant performance improvement with FPGA acceleration to X-DB.


    Buy server hardware with these key functions in judgement | killexams.com existent questions and Pass4sure dumps

    When the time comes to buy server hardware, there are a lot of factors to consider, such as the number of processors, the available recollection and the total storage capacity. Buyers should closely evaluate eight primary features when comparing the servers available from the leading vendors.

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    Companies should view these eight features as the starting point to identify their requirements and evaluate the available products and should expand their research as necessary to ensure they're addressing every concern.

    Server recollection might likewise comprise fault-tolerant capabilities or other features that enhance reliability. One of the most common capabilities is error-correcting code (ECC), a mode to detect and amend common single-bit errors. When evaluating server hardware memory, you should glimpse at the entire offering, keeping in judgement the types of workloads and applications you run.

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    Servers vary greatly in the amount and types of internal storage that they support, in section because workflows and applications likewise vary. For example, a server hosting a relational database management system will believe different requirements than one hosting a web application. In addition, the spend of external storage, such as storage belt networks (SANs), can likewise impact internal storage requirements.

    When you buy server hardware, breathe positive to evaluate each prospective server to ensure it can meet your storage needs. Today, most servers advocate both solid-state drives (SSDs) and hard disk drives (HDDs). But buyers should certainly verify this support, as well as the server's supported drive technologies, such as Serial-Attached SCSI (SAS), Serial Advanced Technology Attachment (SATA) or non-volatile recollection express (NVMe). Other considerations should comprise drive speeds, capacities, endurance and advocate for redundant array of independent disks (RAID).

    For example, Oracle's X7-2 rack server can advocate up to eight 2.5-inch HDDs or SSDs, either SAS or NVMe, and multiple RAID configurations. Compare that to the Inspur TS860G3 rack server, which can maneuver up to 16 drives, either SSDs or HDDs, and advocate both SAS and SATA. However, the Inspur server does not advocate NVMe, which means the SSDs might not effect as well.

    Connectivity

    A server's competence to connect to networks, peripherals, storage and other components is essential to its effectiveness within the data center. The server needs the necessary connectors and drivers to ensure that it can properly communicate with other entities and process various workloads. Buyers necessity to determine exactly what type of connectivity is necessary and, from there, examine the server's specs to verify whether it will meet those requirements.

    Servers disagree widely in this regard, so buyers should glimpse for specifics such as the number and quicken of the Ethernet connectors, the number and type of USB ports, the availability of management interfaces, the types of protocols available, advocate for SANs and other storage systems, as well as whatever other components are necessary to facilitate connectivity.

    Acer's rack server Altos R380 F3 is a estimable illustration of what connectivity features to glimpse for when you buy server hardware. It includes two Ethernet ports, either 1 GB or 10 GB, an RJ-45 management port, three USB 3.0 ports, one USB 2.0 port, and a video port. In addition, the server offers up to seven Peripheral Component Interconnect Express (PCIe) 3.0 slots and one PCIe 1.0 slot.

    Hot swapping

    Servers tender warm swapping capabilities to varying degrees. warm swapping refers to the competence to supplant or add a component without needing to shut down the system.

    The term warm plugging sometimes refers to warm swapping, although, in theory, warm plugging capabilities are limited to being able to add components but not supplant them without shutting down the system. Because of the confusion around these terms, it is best to verify how each vendor uses them.

    One of the most common warm swappable components is the disk drive. For example, the Cisco UCS B480 M5 blade server supports warm swappable drives, as does the Huawei FusionServer CH242 V5 blade server and the Intel R2224WFQZS rack server.

    With blade systems, the warm swapping capabilities are often within the chassis itself. One illustration is the chassis used for the Lenovo ThinkSystem SN850 blade server, which provides warm swapping capabilities for the fans and power supplies, in addition to the server's disk drives. However, these types of capabilities are not limited to blade servers. The Acer Altos R380 F3 system likewise supports warm swappable fans and power supplies even though it is a rack server.

    Redundancy

    Redundancy is primary to ensure a server's continued operation in the event of a component failure. Most servers provide some flush of redundancy, often for the hard drives, power supplies and fans. The Asus RS720-E9-RS12-E rack server, for example, offers redundant power supplies and the HPE ProLiant DL380 Gen10 rack server offers redundant fans.

    As with its warm swapping capabilities, the redundancy available to blade servers is often located within the chassis. For instance, the chassis that advocate the Dell PowerEdge M830 blade server and Supermicro SBI-6129P-T3N blade server both provide redundant power supplies.

    However, the Dell chassis likewise offers redundant cooling components, and the server itself provides redundant embedded hypervisors.

    Manageability

    Admins must manage a server effectively to ensure its continued operation while delivering optimal performance. Most servers provide at least some management capabilities.

    For example, many servers advocate the knowing Platform Management Interface (IPMI), a specification developed by Dell, Hewlett Packard, Intel and NEC to monitor and manage server systems. Not surprisingly, the servers offered by these companies, such as the Dell PowerEdge M830, HPE ProLiant DL380 Gen10, Intel Server System R2224WFQZS and NEC Express5800/B120g-h, are IPMI-compliant.

    But servers are certainly not limited to IPMI capabilities. For example, the Acer Altos R380 F3 rack server comes with the Acer Smart Server Manager; the Asus RS720-E9-RS12-E rack server comes with the ASUS Control Center; and the Cisco Unified Computing System (UCS) B480 M5 blade server comes with Cisco Intersight, Cisco UCS Manager, Cisco UCS Central Software, Cisco UCS Director and Cisco UCS Performance Manager.

    Blade systems usually provide some type of module to manage the individual blades. For instance, Huawei's FusionServer CH242 V5 blade system includes the knowing Baseboard Management System module to monitor the compute node's operating status and advocate remote management.

    Not surprisingly, systems such as Fujitsu's BS2000 mainframes provide a variety of management capabilities. For example, each BS2000 system includes a management unit that works in conjunction with the SE Manager to tender a centralized interface from which to administer the entire server environment. And IBM's ZR1 mainframe includes the IBM Hardware Management Console (HMC) 2.14, the IBM Dynamic Partition Manager and an optimized z/OS platform for IBM Open Data Analytics.

    Security

    Another primary factor to deem is the server's security features. As with other features, servers can vary significantly in what they offer, with each vendor taking a different approach to securing their systems.

    For example, the Lenovo ThinkSystem SN850 blade server provides an integrated Trusted Platform Module 2.0 chip to store the RSA encryption keys used for hardware authentication. The server likewise supports Secure Boot, Intel Execute Disable Bit (EDB) functionality and Intel Trusted Execution Technology.

    Another illustration is the Oracle Server X7-2 rack server, which comes with the Oracle Integrated Lights Out Manager 4.x, a cloud-ready service processor for monitoring and managing system and chassis functions. On the other hand, the Huawei FusionServer CH242 V5 blade server supports the Advanced Encryption benchmark -- recent Instructions, as well as Intel's EDB feature and Trusted Execution Technology.

    IBM's ZR1 mainframe is likewise strong when it comes to security. The server includes on-chip cryptographic coprocessors and the Central Processor Assist for Cryptographic office (CPACF), which includes the recent Crypto Express6S feature to enable pervasive encryption and advocate a secure cloud strategy. The CPACF is benchmark on every core. The platform likewise includes IBM Secure Service Containers to securely deploy container-based applications.


    Plextor Introduces the PlexWriter 52/24/52A CD-R/RW Drive; Its Second 52X Optical Disk Drive; exemplar for Systems Integrators and Resellers Who Want High-Performance, Low-Cost ... | killexams.com existent questions and Pass4sure dumps

    FREMONT, Calif.--(BUSINESS WIRE)--May 27, 2003--Plextor(R) Corp., a leading developer and manufacturer of DVD and CD equipment, today announced the availability of the PlexWriter(TM) 52/24/52A CD-R/RW drive. The high-speed 3-in-1 drive features 52X CD-Writing, 24X CD-Rewriting, and 52X-max CD-Reading, and is available as a 5.25-inch half-height internal drive with an ATA/ATAPI-5 interface. The recent PlexWriter was specifically engineered to appeal to high-volume resellers and systems integrators seeking value, performance, and reliability in a CD burner.

    Although the PlexWriter(TM) 52/24/52A breaks a recent cost barrier for Plextor, it silent includes a complete suite of Roxio digital media software, as well as a unique combination of Plextor features and technologies that deliver unparalleled recording reliability. Buffer Under elope Proof technology prevents buffer underrun errors, so users can multi-task during a recording session. PoweRec(TM) (Plextor Optimized Writing oversight Reduction Control) technology is a sophisticated write strategy for stable recording at maximum speeds. Superior 52X-max digital audio extraction (DAE) eliminates pops, clicks, and hisses for superior sound quality.

    "Drive cost is a factor considered by many of their VARs and Systems Integrators," said Howard Wing, vice president of sales and marketing for Plextor. "We set out to design a 52X drive that would breathe affordable, yet silent uphold Plextor's reputation for dependability and consistency in recording CDs. Now they believe two 52X drive solutions--the PlexWriter(TM) Premium for professionals and other end-users who want the ultimate in user-controlled features, and the low-cost PlexWriter(TM) 52/24/52A for high-volume systems integrators."

    PlexWriter 52/24/52A CD-R/RW Drive

    The PlexWriter 52/24/52A drive makes installation faster and easier than ever before. The drive is designed for supple PC installation, with ATA/ATAPI-5 interface, advocate for horizontal or perpendicular drive bay orientation, and Plug & Play compatibility with Microsoft Windows(R) 98/ME/2000/XP(TM) operating systems.

    The unit features a 2 MB data buffer and burst data transfer rates of 33.3 MB/sec (UltraDMA Mode 2) or 16.6 MB/sec (PIO Mode 4/DMA Mode 2). PlexWriter drives advocate a wide variety of CD writing modes, including Track-at-Once, Disc-at-Once, Session-at-Once, Multisession, and variable/fixed packet writing.

    Software Bundle - Roxio(R) effortless CD Creator(TM), Roxio PhotoSuite(R) and PlexTools(R)

    Plextor's bundled software package offers ease-of-use and extensive functionality. The PlexWriter 52/24/52A ships with the effortless CD Creator/DirectCD software package from Roxio, Inc. Roxio's number one selling CD-recording software allows users to drag and drop files to CD-R and CD-RW media. effortless CD Creator includes DirectCD(TM) (packet writing), CD pre-mastering, one-button CD copier, and the competence to create enhanced and mixed-mode CDs. effortless CD Creator likewise provides the competence to create music CDs, photo slither shows synchronized with music, data CDs, and backup copies of personal discs.

    Roxio PhotoSuite allows consumers to capture, organize, edit and share digital photos. It includes simple electronic albums and a combination of automated and advanced photo-editing tools. Consumers can likewise print and share online or quickly E-mail them without leaving the program.

    PlexTools allows you to control the primary functions of the PlexWriter 52/24/52A with an easy-to-use interface. It permits drive identification and control, pomp of Compact Disc information, Digital Audio Extraction, CD copying and more.

    The PlexWriter 52/24/52A drive likewise includes a 30-day visitation version of Dantz Retrospect(R). Built on patented technologies, the Dantz Retrospect family of backup products has earned numerous awards for protecting vital information on file servers, business-critical application servers, desktops, and notebooks.

    Pricing and Availability

    The Plextor PlexWriter 52/24/52A drive is available for shipment to distributors and resellers in North and South America in late June 2003. The PlexWriter 52/24/52A has a Manufacturer's Suggested Retail cost (MSRP) of $86.00 USD. entire retail packages comprise unlimited toll-free technical advocate and one-year complete warranty.

    About Plextor

    Plextor Corp. is a leading developer and manufacturer of high-performance CD-related tackle for professional spend in consumer and business environments. Since opening its headquarters in Silicon Valley in 1990, Plextor has introduced numerous generations of award-winning optical storage products, including CD-ROM, CD-Recordable, CD-ReWritable, and DVD+R/RW drives. Plextor is privately owned by Shinano Kenshi Co., Ltd., a developer and manufacturer of advanced technology hardware and precision electronic tackle headquartered in Japan. Shinano Kenshi is best known for its expertise in manufacturing motors.

    Note to Editors: Plextor is a registered trademark and PlexWriter is a trademark of Plextor Corp. Roxio, PhotoSuite, and effortless CD Creator are registered trademarks of Roxio, Inc. entire other trademarks, trade names, registered trademarks, or registered trade names are the property of their respective holders.


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