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L50-501 LSI SVM5 Implementation Engineer

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L50-501 exam Dumps Source : LSI SVM5 Implementation Engineer

Test Code : L50-501
Test cognomen : LSI SVM5 Implementation Engineer
Vendor cognomen : LSI
: 119 actual Questions

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LSI LSI SVM5 Implementation Engineer

SAP and LSI Consulting wait on minute and Midsize Healthcare suppliers offer greater services at lessen can saturate | killexams.com actual Questions and Pass4sure dumps

jointly Developed software solution for Healthcare is based on SAP(R) most suitable Practices programs to improvement Healthcare providers With confirmed Integration and Operations techniques

NEWTOWN square, Pa.-- The want for productive operations within the healthcare company trade isn't remoted to massive fitness programs and medical institution chains. Smaller and midsize healthcare issuer organizations are additionally under power to continuously spin into greater efficient whereas on the equal time providing high-quality care. SAP AG (NYSE: SAP) in conjunction with LSI Consulting nowadays announced the provision of a healthcare-based solution that leverages the energy of the commercial enterprise useful resource planning (ERP) software SAP® ERP and SAP® most usurp Practices packages for minute to midsize hospitals in the U.S. market.

The industries group at SAP worked carefully with LSI to check the strategies and tactics of outdated successful SAP integrations at bigger clinical facilities, together with those connected to greater-researching associations working SAP applied sciences. The group then aggregated the finest practices recognized to construct the solution, which might breathe offered by the spend of each the traditional on-premise and simple on-demand models. The software is designed for hospitals and scientific centers in the minute to midsize segment, described as providing 400 beds or fewer, with a view to spend it to achieve equivalent enterprise value in a shorter time duration and at a lower saturate aspect than their larger counterparts.

As a depended on healthcare consultancy and implementation enterprise, LSI recognized the want for sophisticated expertise in these smaller, customarily community-based mostly facilities. however with restricted budgets and materials, minute to midsize hospitals want guidance in securing an accelerated time to enterprise cost from their IT implementations, with bendy deployment alternatives, with out sacrificing satisfactory or a customer-focused method. the original solution turned into for this reason developed the spend of the training learned from diverse on-time, on-funds implementations carried out by LSI. The outcomes is a portfolio of pre-packaged templates and accelerators that allow repeatable success via confirmed solutions that engineer lots of the time-intensive choices out of the implementation procedure.

"because of their long background of presenting SAP solutions to colossal healthcare carrier organizations, we're in a special station to identify and accumulate the optimum practices for implementation throughout a firm's core commerce approaches," pointed out Steve Roach, director of Healthcare options at LSI Consulting. "The solution they suffer now packaged is designed to wield the bottom set of primary functionalities obligatory by using hospitals enabling them to sojourn practicable within the smaller community setting. That performance comprises economic accounting, deliver chain management, together with alternate cart processing, and analytics."

a variety of Deployment models offer Flexibility in start

on account of the growing to breathe recognition and relevance of quite a few internet hosting methods, the brand original answer, which can also breathe purchased through LSI, should breathe offered through each an on-premise and on-demand mannequin. A hosted model is already purchasable, enabling for the reply itself to breathe managed, monitored and maintained through SAP experts in world-category hosted facts centers. This option cuts down on the necessity for IT authorities to maintain the apparatus on site, cutting back the capital rate tribulation that can avoid smaller companies from making the most of business-leading know-how. Licensing for a subscription-based mostly mannequin will become obtainable in coming months.

"SAP has a longtime popularity globally as a company of healthcare options to massive scientific facilities, and has worked in concomitant years to help equally advisable solutions to minute and midsize hospitals every bit of over the world," spoke of John Papandrea, senior vice chairman, international health Sciences Sector, SAP. "The introduction of this jointly developed answer, principally configured to fulfill the wants of the U.S. market, suggests their dedication to this section as they observe top-quality practices, articulated inside a template, to present a comprehensive solution with bendy deployment alternatives that could mitigate chance and allow speedy time to price for smaller hospitals."

About LSI ConsultingDedicated to the U.S. Healthcare, larger schooling and analysis and Public Sector markets, LSI empowers organizations to maximise service, revenue, ROI and supply chain visibility for their valued clientele. With over a decade of experience as an SAP implementer, its mission is to uphold optimize their customers' company operations to coerce fulfillment of strategic organizational and public aims. LSI's complete offering of replete lifecycle features contains preconfigured solutions for accelerated SAP Healthcare, better education, analysis and autochthonous executive implementations. To study greater, search counsel from http://www.lsiconsulting.com/.

About SAPSAP is the realm's main issuer of commerce software(*), offering applications and capabilities that allow organizations of every bit of sizes and in additional than 25 industries to develop into premiere-run groups. With greater than ninety seven,000 shoppers in over a hundred and twenty international locations, the enterprise is listed on a couple of exchanges, together with the Frankfurt inventory alternate and NYSE, beneath the attribute "SAP." For extra information, search counsel from www.sap.com.

(*) SAP defines enterprise software as comprising commercial enterprise resource planning, enterprise intelligence, and linked purposes.

follow SAP on Twitter at @sapnews.

For consumers attracted to studying more about SAP items:world client middle: +49 one hundred eighty 534-34-24United States most effective: 1 (800) 872-1SAP (1-800-872-1727)

For extra counsel, press best:Dorit Shackleton, (604) 974-2444, dorit.shackleton@sap.com, PDTSAP Press office, +49 (6227) 7-46315, CET; +1 (610) 661-3200, EDT;press@sap.comBecca Hatton, Burson-Marsteller, (202) 530-4568, becca.hatton@bm.com, EDT

supply: SAP AG

web website: www.sap.com/

linked Thomas trade replace Thomas For Industry

LSI Industries Inc. F4Q09 (Qtr sojourn 30/06/09) earnings cognomen Transcript | killexams.com actual Questions and Pass4sure dumps

No outcomes found, are trying original key phrase!We had met with many consulting engineer ... for this market and LSI is the only company that they've considered that is able to conclude these things every bit of together. i would philosophize that commerce plan is in a position compl...

A Design Methodology for constructing technique-independent Hardmacro IP | killexams.com actual Questions and Pass4sure dumps

unexpectedly migrating highbrow property (IP) from one foundry to an additional and from one process node to the next will also breathe a challenging, however fundamental, a portion of the business, in particular if the IP is generated and delivered as hardmacro IP.  That’s because challenging IP or a GDSII netlist versus soft IP, RTL or gate-level netlist ought to breathe available for every bit of most necessary foundries and for a wide selection of system nodes at every foundry.

Designing original reminiscence IP is essentially a pilot assignment that comprises extra analog circuits —can saturate pumps, voltage regulators and experience amplifiers, for instance — than most suitable judgment designs.  At four megabytes (Mb), the design tribulation facing the layout supervisor and his implementation group is formidable. 

These concerns are commonplace of reminiscence design, and the Kilopass team ran into them when designing a concomitant 4-Mb reminiscence IP block.  Its adventure offers approaches in which different groups can overcome these challenges.

To ease the burden, the team identified points of the design that may well breathe computerized, liberating them to breathe conscious of crucial analog aspects that should breathe tailored for a person foundry and technique.  The outcomes is an electronic design automation (EDA) utensil perambulate developed for the newest anti-fuse non-risky reminiscence (NVM) product line. 

Exploiting the EDA utensil circulate

using commercially obtainable EDA options, the primary job to breathe automatic become lickety-split and accurate entry of design ideas, together with managing design intent in a means that flowed naturally in the schematic.  This allowed designers to visualize and reckon the numerous interdependencies of an analog or combined-sign design and its consequences on circuit performance.

In designing this four-Mb reminiscence, about 10 % of the design required the layout team to import a GDSII netlist developed by an extra internal team.  The project of merging the existing layout with the relaxation of the reminiscence design become an simple manner requiring a day of manual location and route or connecting I/Os and routing vigour and ground. 

The team made spend of the potential to embed design constraints in the netlist passed between the front-conclusion design group and the implementation crew.  Up except that factor, these constraints had been communicated with the aid of cryptic notes on the schematic.  for instance:  Specify that two gates mandatory to breathe matched or a selected web is censorious and its optimum size suffer to now not breathe handed in the layout.  Communicated the historical method, when the schematic became given to the implementation engineer, the clothier could simplest hope that the implementation crew executed the preferred outcome. 

Managing Complexity

The implementation crew built a original reminiscence through making a separate reminiscence cell then replicated it to construct the extra advanced arrays — a backside-up approach versus the yardstick proper-down routine that gigantic digital SoC design teams result spend of.  The reminiscence consisted of a runt mobile comprising two transistors.  

once the bit cellphone became created and optimized, the cell turned into replicated along a horizontal line of length n (32, for instance), as specific within the schematic.  once the line of reminiscence cells became created, it become replicated vertically m variety of rows (32, as an instance), as distinctive in the schematic.  in this method, the implementation engineer created a 1-Mb reminiscence array.  The procedure turned into repeated three greater times to create the 4-Mb reminiscence, a two-with the aid of-two matrix of 1-Mb arrays.

In constructing the initial netlist, the front-conclusion fashion designer labeled each and every of the bit cells and its linked vigour, floor, bit line and note line.  He then specific the variety of bit cells to breathe powered by using a given punch net to ensure that each and every phone received the selfsame amount of latest.

The potential to set constraints in the netlist passed to the implementation engineer ensured the design intent was captured in remaining design. 

Automating Repetitive pilot projects

Automating repetitive initiatives significantly reduced the time to comprehensive the design as smartly.  as an instance, labeling the bit line, observe line, feel amplifier, and punch and floor for a four-Mb reminiscence can prefer considerable time if achieved manually.  Surrendering the assignment to the EDA utensil reduced the chore to a handful of keyboard operations.

In a pull-down menu, the implementation engineer achieved a kindhearted that requested for the symptom name, number of pins to breathe labeled, x and y coordinates of the primary signal, spacing between pins, and the size of the textual content.  From this advice, the design device created each and every particular person symptom identify.

as soon as the reminiscence IP become applied for the forty-nanometer (nm) manner at foundry A, the design crew changed into confronted with changing the reminiscence to 40 nm at another foundry.  With the automatic EDA circulation, this became reduced to a two-step procedure:  layer mapping followed by means of statistics manipulation.  within the first step, the mapping desk for foundry A’s forty-nm library was replaced with the mapping table for foundry B’s 40-nm library.  The device then automatically produced a design for foundry B.  The process turned into now not completely automatic, as each and every foundry has its own wonderful guidelines; for that reason exceptions that conclude not map one-to-one are highlighted.

The implementation engineer examined every bit of generated exceptions then made integral alterations.  as an example, in foundry A, the bit telephone might also spend layer C and D, whereas in foundry B, layer D and E are used.  once the conversion became accomplished, a design rule check (DRC) changed into carried out together with ultimate verification. 

This automation took half the time in comparison with starting from scratch, enabling quick migration of IP from one foundry to a further.  while designing original reminiscence IP, comparable to Kilopass’ Gusto anti-fuse NVM, remains on the all a pilot effort, features may also breathe automatic, enabling the layout and implementation team to concentrate on censorious analog aspects that suffer to breathe tailor-made for an individual foundry and procedure.  

author Bio:  Bernd Stamme is Director for advertising and marketing and functions at Kilopass expertise.  He has more than 15 years of adventure within the IP and semiconductor trade. just before Kilopass, he become the Director of IP know-how at SiRF technology managing the licensing and a success integration of third-celebration IP into SiRF’s GPS chip sets.  before SiRF, he held administration positions in LSI logic’s CoreWare company and worked on excessive-pace SerDes IP, conversation interfaces and processor core.  Stamme holds a Dipl.-Ing. diploma in Electrical Engineering from FH Bielefeld in Germany.


L50-501 LSI SVM5 Implementation Engineer

Study pilot Prepared by Killexams.com LSI Dumps Experts


Killexams.com L50-501 Dumps and actual Questions

100% actual Questions - Exam Pass Guarantee with high Marks - Just Memorize the Answers



L50-501 exam Dumps Source : LSI SVM5 Implementation Engineer

Test Code : L50-501
Test cognomen : LSI SVM5 Implementation Engineer
Vendor cognomen : LSI
: 119 actual Questions

attempt out these actual L50-501 questions.
Passed the L50-501 exam with 99% marks. Excellent! considering only 15 days preparation time. every bit of credit goes to the Question & reply by killexams. Its astounding material made preparation so simple that I could even understand the hard topics at ease. Thanks a lot, killexams.com for providing us such an simple and efficient study guide. Hope your team sustain on creating more of such guides for other IT certification tests.


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I had bought your online mock test of L50-501 exam and feature passed it in the first try. im very lots grateful to you in your support. Its a delight to inform that ive passed the L50-501 examination with seventy nine% marks..thank you killexams.com for the all thing. You men are virtually wondeful. gladden maintain up the suitable paintings and hold updating the cutting-edge questions.


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LSI SVM5 Implementation Engineer

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Video Encoding: proceed for the Specialist or the Jack-of-All-Trades? | killexams.com actual questions and Pass4sure dumps

Video Encoding: proceed for the Specialist or the Jack-of-All-Trades?

When it comes to video encoding, the option between hardware and software comes down to flexibility, latency, and cost.

Page 1

Learn more about the companies mentioned in this article in the Sourcebook:

One of the hardest choices encoding technicians suffer to result is deciding between hardware and software. Hardware-based encoders and transcoders suffer had a performance advantage over software since computers were invented. That's because dedicated, limited-purpose processors are designed to flee a specific algorithm, while the general-purpose processor that runs encoding software is designed to wield several functions. It's the specialist versus the jack-of-all-trades.

In the past few years, processors and workflows suffer changed. The considerable disruptor has been time and the economics of Moore's Law, which famously says that the number of transistors incorporated in a chip will approximately double every 24 months. The ratiocinative outcome of Moore's law is that the CPUs derive more powerful by a factor of two every few years, but more recently processing power seems to double every few months. Lately, Intel -- whose co-founder Gordon Moore coined Moore's Law -- has been adding specialty functions along with its math co-processors to equalize the differences between general-use processors and specialty processors.

There are many layers and elements to both a general-purpose processor and a task-specific hardware processor. The general-purpose CPU is the most common -- there are literally billions of them in every bit of manner of computing devices -- while the more purpose-oriented processors include digital signal processors (DSPs), field-programmable gate arrays (FPGAs), and integrated circuits (ICs) that are available for various industrial appliances and widely used in cellphones. Many of the structures and elements are similar across every bit of types, but there are considerable differences. If you are not chummy with the elements of the various types, here are the basic structures of both.

The General-Purpose CPU

The general-purpose CPU is laid out with supple core elements as the arithmetic logic unit (ALU), control unit (CU), and accessory elements that offer extra features for performance. Basically these two cores talk to each other, bring in reminiscence as needed, and ship travail to the other elements. Other elements include I/O processors, logic gates, integrated circuits, and -- on most newer processors and especially on the Intel Xeon processors -- a beefy math co-processor. The math co-processor assists the ALU and can wield the more extreme and complex mathematical computations. Essentially, it gives the processor the extra horsepower it might require.

The Dedicated Processor

Specific-purpose hardware encoders suffer been around longer than general-purpose processors, and the latter suffer been slower at mathematical equations or algorithm problems. History is vitally necessary to understand the market and technology, not to mention derive a sense of what the future holds. The earliest sample of encoding was in 1965, when the Intelsat 1 (Early Bird) became the first commercial deployment of a satellite to downlink video and audio. Since then, the world has been using specific processors to process video, and the technology has made leaps and bounds to offer higher density and quality.

Video ARM DSP

This is a generic layout of a video ARM DSP. The ARM core runs the embedded operating system, working enjoy a traffic cop to control input and output. 

Dedicated processors -- such as dedicated signal processors (DSPs), graphics processing units (GPUs), and vector processors -- every bit of suffer a very similar design structure. A basic and most common constituent is an I/O manager, which has a tiny onboard operating system along with memory. This is the traffic cop, controlling input and output. Then there are multiple specialized processing modules that execute the desired instructions very quickly and that DSPs and other dedicated processors support. Unlike a general-purpose processor, which has many workable generic instructions that may not breathe most efficient for the job at hand, dedicated processors rely on accelerated, per-function instructions that are more job-specific.

Dedicated processors and encoders suffer a variety of applications and workflows. If you survey at the major users of professional encoders, you will notice that in many cases they rely on specialized encoders. The following well-known companies result DSP chips: LSI Corp.; Texas Instruments, Inc.; Analog Devices, Inc.; Sony; and Magnum Semiconductor. These DSPs are used in devices such as media gateways, telepresence devices, cellphones, and military and radar processing.

FPGAs are now very favorite implementations of DSP functions because of their flexibility of setup and upgrade. Since they are field-upgradeable, their development costs for the user are significantly cheaper than DSPs and application-specific integrated circuits (ASICs; more on those in a moment) from the traditional DSP providers. You can notice FGPAs from Altera Corp. and Xilinx, Inc. that suffer DSP functions built in. If you want a board or system that is easier to upgrade in the field, then this is probably the best pass to go.

DSP Packets

While each manufacturer will tweak its design slightly, this is an overview of how communications and packets tide into the modules of DSPs and ASICs. 

Another implementation of the dedicated processor is the ASIC. These factory-programmed DSPs are used everywhere cost is a crucial consideration, because they offer special functionality at optimal price and performance. In general, they are more expensive to design but are cost-effective for any appliance or board manufacturer to implement into their systems. Many manufacturers of DSPs also manufacture ASICs; companies such as NXP Semiconductors, Broadcom Corp., and Freescale, Inc. also result custom ASIC DSPs.

If you ever open up a hardware encoding appliance -- from IP media gateways to broadcast encoder and decoders -- you will notice several of the chips previously listed. You can find appliances for every industry. Today you will find a dedicated hardware-based encoding device from Harmonic, Inc.; Harris; Tandberg Data; or NTT Communications in every TV station or cable TV headend, and you'll find appliances or cards from ViewCast Corp. or Digital Rapids in many hybrid encoding farms, since they accelerate some of the functions in the hardware. If you've watched a video on YouTube, then you suffer seen video encoded by RGB Networks with the RipCode equipment, which used massive numbers of Texas Instruments, Inc. DSPs.

Pros and Cons of Hardware Encoders

There are always some pros and cons when it comes to specific design hardware encoders and dedicated appliances. The dedicated hardware approach with DSPs or chips is the faultless solution for media gateways and in low latency military applications. They are designed to flee 24/7 with runt or no human interaction. There are some processors that can encode an entire frame in the 1ms-10ms (millisecond) purview and FPGAs that can encode in the 10ms-30ms range. These processes allow for the creation of appliances where the encoding latency is less than 100ms from encode to transmission to decode. prerogative now you can only derive low latency using the prerogative DSPs, ASICs, and FPGAs. The dispassionate lifespan of an appliance is 5-10 years depending on the configuration and manufacturer. Similar lifetimes are assumed for systems that rarely change, such as satellite uplink or cable system encoders.

The primary drawback of dedicated hardware-based encoding is that the codec on the processor is generally impossible to upgrade. Every DSP, ASIC, or FPGA is based on an algorithm that was finalized years ago. By the time the chip is ready to breathe sold, the codec is 6 months to a year old. Add more design cycles for the appliance development and manufacturing, and the sojourn result is a device based on a codec that's a year or more old. If improvement to the codec comes out, the chip or device might never breathe able to integrate the original codec or technology due to the manufacturer or the pass the chip was designed. The dedicated DSP approach can reclaim a lot of money, but at the expense of flexibility. Those chips conclude just what they were originally designed to conclude and nothing more.

Hardware Encoder

Video comes into a hardware encoder to a media gateway, which will result adjustments to the video stream to address network conditions and the sojourn user’s video decoding device. When done, it will ship these modifications to the video decoder. 

There's another issue with dedicated chip-based encoders: Who determines the trait of the codes and streams? Is it a DSP engineer, a compressionist, or the producer and director? In a TV station, it's usually a combination of chief engineer and executive producer who resolve what station image goes over the air. If they spend a hardware encoder, in many cases decisions about encoding parameters suffer been taken out of their hands. The broadcast engineer has to travail within the parameters the chip manufacturer has allowed sojourn users to change, signification that while there is usually some control, there may not breathe as much as a producer or engineer would like. There are only so many operations and cycles you can result on a chip, so some functionality is uneconomical to implement.

The Pros and Cons of Software Encoders

General-purpose CPUs share some similarities and architecture with dedicated processors. They are designed to wield the everyday functions of your PC or server, and they are optimized to conclude mundane tasks such as word processing. This is why your motherboard has a powerful graphics card in your machine; it's a specialty office that is best offloaded to a specific-designed processor. If you conclude any nonlinear video editing, you likely suffer a capture card with some specialty processors to give you real-time output or transitions.

In the encoding and streaming industry, they mostly spend a capture board and one or more of many available software encoding packages. There are algorithms and formulas for every application, from live encoding to file-based transcoding to software-based decoding. These days most software-based encoders suffer hooks in the code to offload certain elements to accelerate or allow multiple CPUs to flee parallel functions to derive the best performance and quality. More recently, Intel is offering some onboard GPUs that feature decoding with MPEG, analysis of a video stream's motion vectors, and other functions.

GPU

This overview shows how a GPU or video accelerator is laid out. Again, one device works as a traffic cop to ship travail to the usurp processors, then takes the video streams back and reassembles them together, allowing video to breathe encoded at a faster rate. 

Software encoders suffer allowed users to breathe much more supple in responding to the needs of specific customers or events, and they every bit of spend the selfsame general-purpose processors and capture boards to uphold more video formats and standards. This has been an advantage for software encoders for a long time. They are simple to reconfigure and use.

The software encoding industry has recently seen battles between open source and closed source. There are some notable pioneering closed source companies that helped drive the development of software encoding and streaming: Microsoft; actual Networks, Inc.; Sorenson Communications; and Adobe Systems, Inc. laid out the framework for modern streaming and web-based video. They suffer been around since the beginning, and in many cases they financed the codecs that became standards.

In addition to these pioneering companies, there has been a recent movement to open source. Some of the earlier versions such as x264 and the open source library in the University of California-Berkeley provide the foundation for most software encoders. Code is added every so often and allows others to program their custom apps. The better-known ones such as VideoLan (VLC), FFmpeg, and WebM are creating original versions and are catching on in generic use. Some are even getting funding from some of the larger public companies. The most notable sample is WebM, which is being funded mostly by Google, which made the VP8 codec open source after it acquired On2 Technologies. every bit of this competition and activity is creating better products for consumers. The titanic companies realize open source development and innovation is faster-moving than their own, allowing the market to grow more quickly than it otherwise might.

But software-based encoding has some drawbacks. The most necessary parameters of encoding are quality, flexibility, price, latency, and support.

Software encoding's greatest advantages over absolute hardware encoders are its flexibility and quality. Software has always been able to adopt and update incredibly fast. When original codec optimizations near out, encoding package updates result very soon after.

Software encoding can enable the producer, engineer, or other user to derive precisely the trait and image that they want, unlike the automated hardware solution, where the user has no philosophize in what the overall image is and outcome will be. Some larger encoding firms hire color consultants and compressionists, along with programmers and delivery experts, every bit of of whom wait on the executive producers and directors determine what the overall outcome should survey like. It's a broadcast approach for streaming.

Xeon Phi

Later this year or in early 2013, Intel will release its Xeon Phi string of massive parallel coprocessors, which will travail with existing Xeon processors and workflows. 

So if software encoding wins in flexibility and quality, what about precipitate or latency? While some highly tuned hardware encoders offer a latency down in the 30ms range, most software solutions flee in the 300ms-500ms range, if not higher. Most people who spend software encoding realize they are sacrificing some precipitate for quality. every bit of that matters is whether or not they can derive the resolution and framerate they want; if it's delayed some, the workflow can breathe designed to accommodate it. On the other hand, if you require the lowest latency and fastest delivery, you will suffer to give up some quality.

Cost of uphold is of course an necessary issue. Will the proprietary company sustain making the version you're using, or is there a chance it will breathe withdrawn from the market? How much will the updates and upgrades cost? It turns out that upgrades in the open source community are relatively frequent, whereas upgrades in propriety software are less so.

While some people assume that open source products offer lower trait or reliability than proprietary software, that's not necessarily the case. FFmpeg, VLC, and WebM are every bit of significantly upping their quality. On the other hand, proprietary software packages such as Sorenson and MainConcept suffer also stood the test of time and continue to find widespread use. Interestingly, MainConcept and Sorenson are two of the few companies whose solutions are used in both software and hardware encoding; both provide codecs for the PC environment as well as specifically designed chips.

Changes in Media Consumption, Changes in Media Encoding

General-purpose hardware-based decoders are now playing an necessary role in the overall media viewer world, especially as more and more viewers are quitting cable and going the IP route for every bit of of their video consumption. Roku, Boxee, and other IP set-top boxes are DSP-based decoders. At the selfsame time, more and more consumers are adopting Android or iOS devices and using them as personal media players, and each device brings with it its own set of example encoding profiles and parameters. You'll find you necessity to conclude custom scaling and probably want to offer the highest workable complexity. Then again, you necessity to spend more CPU cycles per frame, which will require more encoding time but create a better outcome.

Conclusion

There will always breathe a battle between hardware encoding and software encoding. Who will win in various market segments? Why a hardware encoder versus the software encoder? Even now they are starting to notice more specialty functionality appended on the general-purpose CPUs, due to the miniaturization and density of transistors and processors. For instance, Intel recently agreed to buy 190 patents and 170 patent applications from RealNetworks, and for years the company has been adding graphics processing and other accelerators or processing engines.

Dedicated hardware encoding wins in unique parallel processing situations when massive amounts of data necessity to breathe processed, as well as in low latency communications such as real-time monetary and some military applications. It also leads in situations where you want to just install the encoding utensil and let it conclude its thing, such as in situations with YouTube that can rely on automated, predefined resolutions and bitrates for a massive amount of viewers. But software encoders will breathe the utensil of option in most applications. It's faster and cheaper to encode with software than in hardware, and once you notice how the market responds to your output, it's faster and cheaper to result modifications.

So, conclude you most value flexibility and lower costs? Then software is probably your best bet. conclude you necessity low latency and stream density or automated auto-transcoding for the mobile market? Then a hardware solution probably is best for you.

This article appears in the October/November, 2012, issue of Streaming Media magazine under the title "The Specialist Vs. the Jack-of-All-Trades."

Page 1

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A Design Methodology for pile Process-Independent Hardmacro IP | killexams.com actual questions and Pass4sure dumps

Rapidly migrating intellectual property (IP) from one foundry to another and from one process node to the next can breathe a challenging, but necessary, portion of the business, especially if the IP is generated and delivered as hardmacro IP.  That’s because hard IP or a GDSII netlist versus soft IP, RTL or gate-level netlist must breathe available for every bit of major foundries and for a wide selection of process nodes at each foundry.

Designing original reminiscence IP is largely a manual job that involves more analog circuits —charge pumps, voltage regulators and sense amplifiers, for sample — than most logic designs.  At four megabytes (Mb), the design tribulation facing the layout manager and his implementation team is formidable. 

These issues are typical of reminiscence design, and the Kilopass team ran into them when designing a recent 4-Mb reminiscence IP block.  Its experience offers ways in which other teams can overcome these challenges.

To ease the burden, the team identified elements of the design that could breathe automated, freeing them to concentrate on censorious analog elements that must breathe tailored for an individual foundry and process.  The result is an electronic design automation (EDA) utensil tide developed for the latest anti-fuse non-volatile reminiscence (NVM) product line. 

Exploiting the EDA utensil Flow

Using commercially available EDA solutions, the first job to breathe automated was rapid and accurate entry of design concepts, including managing design intent in a pass that flowed naturally in the schematic.  This allowed designers to visualize and understand the many interdependencies of an analog or mixed-signal design and its effects on circuit performance.

In designing this 4-Mb memory, about 10 percent of the design required the layout team to import a GDSII netlist developed by another internal team.  The job of merging the existing layout with the repose of the reminiscence design was a simple process requiring a day of manual station and route or connecting I/Os and routing power and ground. 

The team made spend of the aptitude to embed design constraints in the netlist passed between the front-end design team and the implementation team.  Up until that point, those constraints were communicated by cryptic notes on the schematic.  For example:  Specify that two gates needed to breathe matched or a specific net is censorious and its maximum length must not breathe exceeded in the layout.  Communicated the antiquated way, when the schematic was given to the implementation engineer, the designer could only hope that the implementation team achieved the desired result. 

Managing Complexity

The implementation team built a original reminiscence by creating a separate reminiscence cell then replicated it to build the more complex arrays — a bottom-up approach versus the conventional top-down approach that great digital SoC design teams employ.  The reminiscence consisted of a bit cell comprising two transistors.  

Once the bit cell was created and optimized, the cell was replicated along a horizontal line of length n (32, for example), as specified in the schematic.  Once the line of reminiscence cells was created, it was replicated vertically m number of rows (32, for example), as specified in the schematic.  In this manner, the implementation engineer created a 1-Mb reminiscence array.  The process was repeated three more times to create the 4-Mb memory, a two-by-two matrix of 1-Mb arrays.

In developing the initial netlist, the front-end designer labeled each of the bit cells and its associated power, ground, bit line and word line.  He then specified the number of bit cells to breathe powered by a given power net to ensure that each cell received the selfsame amount of current.

The aptitude to set constraints in the netlist passed to the implementation engineer ensured the design intent was captured in final layout. 

Automating Repetitive Manual Tasks

Automating repetitive tasks greatly reduced the time to complete the layout as well.  For example, labeling the bit line, word line, sense amplifier, and power and ground for a 4-Mb reminiscence can prefer considerable time if done manually.  Surrendering the job to the EDA utensil reduced the chore to a handful of keyboard operations.

In a pull-down menu, the implementation engineer completed a form that asked for the signal name, number of pins to breathe labeled, x and y coordinates of the first signal, spacing between pins, and the size of the text.  From this information, the design utensil created each individual signal name.

Once the reminiscence IP was implemented for the 40-nanometer (nm) process at foundry A, the layout team was confronted with converting the reminiscence to 40 nm at another foundry.  With the automated EDA flow, this was reduced to a two-step process:  layer mapping followed by data manipulation.  In the first step, the mapping table for foundry A’s 40-nm library was replaced with the mapping table for foundry B’s 40-nm library.  The utensil then automatically produced a layout for foundry B.  The process was not completely automated, as each foundry has its own unique rules; thus exceptions that conclude not map one-to-one are highlighted.

The implementation engineer examined every bit of generated exceptions then made necessary adjustments.  For example, in foundry A, the bit cell may spend layer C and D, whereas in foundry B, layer D and E are used.  Once the conversion was completed, a design rule check (DRC) was performed along with final verification. 

This automation took half the time compared with starting from scratch, enabling rapid migration of IP from one foundry to another.  While designing original reminiscence IP, such as Kilopass’ Gusto anti-fuse NVM, continues to breathe mostly a manual effort, elements can breathe automated, enabling the layout and implementation team to concentrate on censorious analog elements that must breathe tailored for an individual foundry and process.  

Author Bio:  Bernd Stamme is Director for Marketing and Applications at Kilopass Technology.  He has more than 15 years of experience in the IP and semiconductor industry. Prior to Kilopass, he was the Director of IP Technology at SiRF Technology managing the licensing and successful integration of third-party IP into SiRF’s GPS chip sets.  Before SiRF, he held management positions in LSI Logic’s CoreWare organization and worked on high-speed SerDes IP, communication interfaces and processor core.  Stamme holds a Dipl.-Ing. Degree in Electrical Engineering from FH Bielefeld in Germany.


Android's "Treble" interface | killexams.com actual questions and Pass4sure dumps

[Posted May 12, 2017 by corbet]

The Android Developers Blog carries an announcement for an upcoming feature called "Treble", which looks enjoy a separate, guaranteed stable interface for device drivers. "The core concept is to divorce the vendor implementation - the device-specific, lower-level software written in great portion by the silicon manufacturers - from the Android OS Framework. This is achieved by the introduction of a original vendor interface between the Android OS framework and the vendor implementation." Details are scarce, and there is no information on how this might suitable into the portion of the "Android OS framework" that many of us believe of as "the Linux kernel". (Log in to post comments)


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