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156-510 - Check Point NG with Application Intelligence - Management III - Dump Information

Vendor : CheckPoint
Exam Code : 156-510
Exam Name : Check Point NG with Application Intelligence - Management III
Questions and Answers : 165 Q & A
Updated On : November 14, 2018
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156-510 Questions and Answers

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156-510 Check Point NG with Application Intelligence - Management III

Study Guide Prepared by Killexams.com CheckPoint Dumps Experts


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156-510 exam Dumps Source : Check Point NG with Application Intelligence - Management III

Test Code : 156-510
Test Name : Check Point NG with Application Intelligence - Management III
Vendor Name : CheckPoint
Q&A : 165 Real Questions

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Taliban assault checkpoint, killing 13 security forces | killexams.com Real Questions and Pass4sure dumps

KABUL — Taliban militants attacked a newly established joint Afghan military and police checkpoint in eastern Ghazni province on Monday, killing at the least 13 soldiers and police officers, according to a provincial professional.

Afghan reinforcements had been dispatched to the web site of the assault in Khogyani district but have been many times ambushed alongside the manner.

earlier than the assault in Ghazni, the Taliban struck in southern Kandahar province late Sunday and killed as a minimum four police officers.

The assaults got here as a resurgent Taliban cling very nearly half of Afghanistan, with near-day by day attacks on Afghan security forces. The Taliban view the U.S.-backed executive in Kabul as a dysfunctional Western puppet and have refused repeated presents to barter with it.

Arif Noori, spokesman for the provincial governor in Ghazni, referred to seven troopers and 6 law enforcement officials had been killed in Monday’s attack on the checkpoint, and 4 soldiers were wounded.

based on Noori, six insurgents have been killed and more than 10 others were wounded during the following three-hour fight with Afghan forces. Zabihullah Mujahid, a Taliban spokesman, claimed accountability for the Ghazni and Kandahar assaults.

The joint army-police checkpoint turned into install simply two days in the past in a strategic enviornment to bring to a halt a key provide route for the Taliban. It was absolutely burned down and destroyed, Noori referred to.

“Reinforcements had been rushed to support the forces beneath attack however they had been ambushed by means of different Taliban warring parties at least 4 instances whereas on their solution to the checkpoint,” talked about Noori.

The Taliban have stepped up assaults in risky Ghazni, and in August overran components of the provincial capital, also referred to as Ghazni. at the time, lots of of people fled the city amid excessive fighting between Afghan forces and the Taliban that killed about one hundred twenty contributors of the protection forces and civilians. based on Afghan authorities, practically 200 insurgents, lots of them international fighters, have been also killed.

Ghazni is the only one out of 34 Afghan provinces the place the nation’s October parliamentary elections could not take vicinity for safety reasons. vote casting turned into postponed for a yr. Elections were delayed for every week in Kandahar after an attack by way of an elite Afghan take care of killed two suitable government officers.

Rahim Faiez is an associated Press creator.


Immune-checkpoint medicine in Oncology: Analytical tool | killexams.com Real Questions and Pass4sure dumps

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Afghan forces killed in Taliban assault on Ghanzi checkpoint | killexams.com Real Questions and Pass4sure dumps

Witnesses spoke of Taliban set govt buildings on fireplace and blocked a few areas all over the assault on Ghazni [Mustafa Andaleb/Reuters]

A Taliban assault on a checkpoint within the japanese province of Ghazni has killed at least 13 troopers and policemen, officials referred to.

Afghan reinforcements have been dispatched to the site after Monday's assault in Khogyani district - observed on the main street between the capital, Kabul, and the Afghan south - but had been time and again ambushed along the style.

The checkpoint was a part of a belt of strongholds built around Ghazni after the metropolis become in short overrun by using the Taliban in August in one of their greatest offensives in years.

at the time, tons of of people fled the city amid severe combating between Afghan forces and the Taliban that killed about 120 contributors of the security forces and civilians.

articleGUID

Arif Noori, spokesperson for the provincial governor in Ghazni, referred to that seven soldiers and six policemen have been killed in Monday's raid.

in response to Noori, six Taliban opponents had been killed and more than 10 others wounded all through a three-hour gun battle with Afghan forces after the preliminary assault.

In a press release sent to the media, Taliban spokesperson Zabihullah Mujahid noted his neighborhood claimed responsibility for the raid. 

The joint military and police checkpoint was installation simply two days in the past in a strategic area to bring to an end a provide route for the Taliban but turned into now completely burned down and destroyed, Noori talked about.

"Reinforcement have been rushed to support the forces beneath assault however they have been ambushed by other Taliban opponents at least 4 instances whereas on their option to the checkpoint," noted Noori.

Ghazni is the only one out of 34 Afghan provinces the place the nation's October parliamentary elections could not take vicinity for protection motives.

voting there was postponed for a 12 months.

A US watchdog agency referred to remaining week that the Afghan government become struggling to get better control of districts misplaced to the Taliban whereas casualties among protection forces had reached list stages.

The government had handle or have an impact on over sixty five percent of the inhabitants however only fifty five.5 % of Afghanistan's 407 districts, the special Inspector widely wide-spread for Afghanistan Reconstruction pointed out in a report previous this year.

The newest section of Afghanistan's a long time of warfare all started in late 2001, when US-led troops overthrew the Taliban in accordance with the September 11 assaults that year on the united states.

supply: Al Jazeera and news businesses


156-510 Check Point NG with Application Intelligence - Management III

Study Guide Prepared by Killexams.com CheckPoint Dumps Experts


Killexams.com 156-510 Dumps and Real Questions

100% Real Questions - Exam Pass Guarantee with High Marks - Just Memorize the Answers



156-510 exam Dumps Source : Check Point NG with Application Intelligence - Management III

Test Code : 156-510
Test Name : Check Point NG with Application Intelligence - Management III
Vendor Name : CheckPoint
Q&A : 165 Real Questions

it's miles incredible ideal to put together 156-510 examination with dumps.
inside the wake of trying a few aids, I at final halted at Dumps and it contained specific solutions delivered in a primarymanner that become exactly what I required. i used to be struggling with with topics, when my examination 156-510 changed into simplest 10 day away. i used to be scared that i would no longer have the potential to attain passing rating the basebypass imprints. I at ultimate surpassed with 78% marks without a whole lot inconvenience.


just attempt these today's dumps and success is yours.
156-510 examination modified into absolutely tough for me as i used to be now not getting enough time for the training. Locating no way out, I took help from the unload. I additionally took assist from reliable Certification manual. The dump was exceptional. It dealt with all the topics in an smooth and friendly way. May additionally want to get thru maximum of them with little attempt. Responded all of the query in only 80 one minutes and were given ninety seven mark. Felt simply satisfied. Thanks lots to killexams.Com for his or her treasured guidance.


Use authentic 156-510 dumps. brain unload high-quality and popularity does remember.
I skip in my 156-510 exam and that was now not a easy bypass however a terrific one which I should inform all of us with proud steam filled in my lungs as I had got 89% marks in my 156-510 exam from studying from killexams.com.


Get those 156-510 Q&A, prepare and chillout!
After trying numerous books, i was quite disenchanted now not getting the proper substances. I used to besearching out a guiding principle for exam 156-510 with smooth language and properly-prepared content cloth. Killexams.Com Q&A fulfilled my need, as it defined the complicated subjects inside the only way. Within the real exam I were given89%, which become beyond my expectation. Thanks killexams.com, in your exquisite guide-line!


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Check Point NG with Application Intelligence - Management III

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Product Management in Artificial Intelligence | killexams.com real questions and Pass4sure dumps

Something from Andrew Ng

I. Introduction

AI has been booming in recent years, and nothing will make it grows slower. Although Many applications such as voice cognition and computer vision have been applied in industry maturely, the AI industry has just entered its early stage of developing. Getting more people involving the AI by knowing how to code is no longer a comparatively urgent issue. Instead, the process of how AI product should be managed by communicating with engineers is a brand new challenge that every leader in AI industry is trying to develop.

Supervised Learning is the most popular method which is broadly adopted in many industries nowadays, whereas the other methods are still in the research phase. According to Wikipedia, “the Supervised learning is the machine learning task of inferring a function from labeled training data. The training data consist of a set of training examples. In supervised learning, each example is a pair consisting of an input object (typically a vector) and a desired output value (also called the supervisory signal).” https://en.wikipedia.org/wiki/Supervised_learning

The sweet spot for AI problem is in the case of if a human can process less than 1 second, that is good for AI to solve.

II. What is the typical PM role in Silicon Valley?

This picture below well-defined in a team, particularly in Silicon Vally, that how a product is designed and launched. It is PM’s job to figure out what users’ love, whereas the engineer’s job to find figure out what is feasible. The bilateral bar on the top of the picture connects between PMs and Engineers means they must communicate to make the product meets both requirement to be great. Needless to say, they are many failed products in Silicon Valley that are only settled in the right half of the picture, which is only existed in engineers’ dream.

III. What are the current challenges for AI Product Managers?
  • No well-defined wireframes.
  • Such as UI/UX user interface design wireframes, there are no such things in AI product.
  • Agile and Code review techniques don’t work for AI PM, yet!
  • There are no such techniques like Agile development or Coding Reviews in AI product development yet, that can be efficiently used to communicate between PMs and engineers. On the other side, however, I think it is a great opportunity to become a product manager.
  • One of the most efficient processes for PM to communicate with engineers, for example in voice cognition, is PM provide the datasets from customers to engineers.
  • IV. Current Concerns
  • job displacement.
  • People are worried about job displacement, but it happens all the time since ancient time. Instead of worrying about your is going to be replaced, let’s focusing on what are the facts, and which of those are positive facts. First of all, It is still the early phase of job displacement for AI and job displacement is inevitable. Secondly, AI will gradually create massive new jobs, just as semiconductor had done in a few decades ago, as well as the electric industry had done in about one hundred fifty years ago. Lastly, but the most important is, education. The most challenge for education is motivation. Despite the facts of how our jobs will be displaced, we need a new education system to re-skill ourselves to fit new jobs. The government should provide the safety to its people by paying the un-employees to study so they can contribute to the society by paying the tax as the return. The circulatory system can be then healthy operated to benefit the whole society.
  • How long does the AI era will last?
  • AI will last decades. Thinking about silicon industry, such as transistors and all the application of using silicons. Right now is the eternal spring of the silicon technology, whereas AI hasn’t reached this phase yet. And when it hits the point it will last even longer than silicon industry did, because AI has created so much value already and there is a clear map to transfer the industry, even only with the ideas we have.
  • V. Reference "Andrew Ng: Artificial Intelligence is the New Electricity", https://www.youtube.com/watch?v=21EiKfQYZXc.

    Andrew Ng is one of the leading thinkers of AI industry, his research focusing on Deep learning. He taught machine learning on 100,000+ students through his online course on Coursera. He also found Google project, coherent VP and chief scientist at Baidu. He is the co-chairman and co-founder of Coursera. Last but not least, he is also the adjunct Professor at Stanford University. All the credits of this content goes to this lecture.


    Comparing the best NGFWs on the market | killexams.com real questions and Pass4sure dumps

    Next-generation firewalls (NGFWs) ably protect enterprise networks from intrusions and attacks with integrated network security platforms that include in-line deep packet inspection firewalls, intrusion prevention systems (IPSes), application inspection and control, SSL/SSH inspection, website filtering and quality of service/bandwidth management. Once an organization has decided to go this route, choosing the best next-generation firewall for its IT environment can be a challenging process, however.

    Choosing the best NGFW for a particular enterprise requires research. Organizations need to investigate and compare NFGW products and come up with a short list. They do not have to choose the top-rated NGFW product in the industry, however. What they need to do is choose the best NGFW that fits and meets their specific enterprise requirements, as best doesn't always mean "best" for you.

    So who are the players? The nine NGFW vendors covered in this article are Check Point, Dell Sonicwall, Palo Alto, Cisco, Fortinet, HP TippingPoint, McAfee, Barracuda and Juniper.

    Questions to consider when looking for the best NGFW vendor product include: What is their product line? Is their NGFW for cloud service providers, large enterprises, or small and medium-sized businesses? What are the NGFW features that come with the base product? What features need an extra license(s)? How is the firewall sold and priced? What differentiates their product from other vendor products?

    As one might anticipate, there are many similarities between NGFWs. However, the differences are worth mentioning and comparing. So while individual write-ups on each of the vendors are forthcoming, here we delve into the similarities and (more importantly) the differences between these nine vendors' NGFW products.

    Who is the NGFW for?

    All NGFWs are designed to protect mid to large enterprises. Cisco, Check Point, Fortinet, Barracuda and Juniper, however, also offer NGFW products for small to medium-sized businesses (SMBs). All the NGFWs covered in this article, meanwhile, support both virtual and physical deployments, as well as deployments in cloud environments such as Azure and AWS.

    What features are available?

    Common features available in all NGFW products include unified threat management (UTM), nondisruptive in bump-in-the-wire configuration, NAT, stateful packet inspection, virtual private network (VPN), integrated signature-based IPS engine and application awareness. They also tend to include the ability to incorporate information from outside the firewall (e.g., directory-based policy, blacklists, whitelists, among others), provide an upgrade path to include future information feeds and security threats, and offer SSL decryption to enable the identification of undesirable encrypted applications.

    Noncommon NGFW features vary by vendor, so this is where organizations can start to differentiate between products and choose the best NGFW for them.

    For example:

  • Dell SonicWall provides security services such as gateway antimalware, content filtering and client antivirus and antispyware that are licensed on an annual subscription contract. Dell SecureWorks premium Global Threat Intelligence service is an additional subscription.
  • Cisco provides application visibility and control as part of the base configuration at no cost, but separate licenses are required for next-generation intrusion prevention systems (NGIPS), advanced malware protection and URL filtering.
  • McAfee provides clustering and multilink as standard features with McAfee Next Generation Firewall license.
  • Barracuda requires an optional subscription for malware protection (AV engine by Avira), threat intelligence and for advanced client network access control VPN/SSL VPN features.
  • Juniper offers advanced software security services (NGFW/UTM/IPS/threat intelligence service) shipped with its SRX Series Services Gateways that can be turned on with the purchase of an additional license, which can be subscription-based or perpetual. No additional components are required to turn services on/off.
  • Check Point provides a full NGFW solution package with all of its software blades included under a single license. However, it does not provide mobile device controls or Wi-Fi network control without purchasing a different Check Point product.
  • The key message in this comparison is that in addition to the common features, organizations need to carefully review those features that require additional licenses and whether they are significant enough to decide on specific products for procurement. For example, if a company requires data loss prevention (DLP), it might consider a NGFW that offers DLP, such as Check Point. Or, should it determine that the DLP components of NGFWs aren't sufficiently powerful enough for its purposes, it may decide to go with a standalone DLP (rather than an integrated) product. The same would apply for Web application firewall (WAF) technology in, say, the Dell SonicWall NGFW. WAF features are there, but it is -- again -- not a full-featured WAF. Another example would be Cisco. Although malware protection is available, additional licenses are required for its Advanced Malware Protection, NGIPS and URL filtering. Barracuda NG Firewall also requires an additional license for malware protection (antivirus engine by Avira), for instance.

    In addition, there are some vendors that provide threat intelligence services as part of their NGFW offerings, such as Fortinet, McAfee and HP TippingPoint. Juniper's Threat Intelligence Service, however, is shipped with its SRX NGFW model, but needs to be activated with the purchase of an additional license.

    How is the NGFW sold, licensed and priced?

    When an organization purchases a product, it receives a copy of the software or appliance and a license to use it. It doesn't actually own the software -- ownership rights belong to the software company, and customers are limited by the terms and conditions (T&C) of the license. All NGFW products are licensed per physical device. Additional licenses are required for the noncommon features stated above. Closely read the T&Cs to determine what services are available in the base NGFW products and what services require an additional license.

    While Check Point and Fortinet are sold through channel organizations, the remaining NGFW vendors sell direct and channel partners. All NGFW products, meanwhile, are priced by scale based on the type of hardware utilized and the service contract. Of particular importance are the wide price range differences not just between vendors, but between the various offerings by individual vendors themselves.

    Cisco, for example, is priced by user. The cost structure is $1,100 (1 to 99 users), $6,500 (100 to 999 users), $25,000 (1,000 to 4,999) and $100,000 (5,000+ users). Palo Alto, by contrast (based on data sheets reviewed), has 2,707 different pricing options ranging from $1,300 to $38,640,000 for its enterprise three-year contracts (PAN-ENT-SUB-4W-3YR).

    While pricing structure appears disparate, similarities do exist in the lower-end product lines -- the smaller the NGFW need, the simpler the pricing. The larger the enterprise and volume purchase potential, the greater the disparity, but also the greater the bargaining power on the part of the customer.

    Licenses typically come in one-, two- and three-year subscriptions. As the number of users increase, volume discounts often apply. We generally recommend not paying MSRP on security products; however, keep in mind that vendors tend to be less flexible with single purchases. One approach is to time purchases for month- or quarter-end, as vendor personnel at these times are often under pressure to meet and exceed sales quotas.

    Is there a free trial version of the NGFW available?

    The only NGFW vendor that does not provide a free trial version at this time is HP TippingPoint. All others provide a free 30-day downloadable full virtual appliance or virtual machine (VM) version to test. Juniper does a bit better than the others, providing potential customers with a 30- to 90-day free trial version run through its paces on their network.

    The key differentiators between NGFW products

    What makes the best NGFW standout among its peers is clearly of great interest. Below are some highlights of the noted differentiators.

  • Check Point is the inventor of stateful firewalls. It has the highest block rate of IPS among its competitors, largest application library (over 5,000) than any other, DLP with over 600 file types, change management (i.e. configuration and rule changes) that no one else has, and agent or agentless Active Directory integration.
  • Dell SonicWall has patented Reassembly-Free Deep Packet Inspection, a technology that allows for centralized management for users to deploy, manage and monitor many thousands of firewalls through a single-pane of glass.
  • Cisco ASA with FirePOWER Services provides an integrated defense solution with greater firewall features detection and protection threat services than other vendors.
  • Fortinet lauds its 11-year-old in-house dedicated security research team, FortiGuard Labs. It is one of the few NGFW vendors that has its own, as most others OEM this activity. Fortinet also purports to have NGFW FortiGate, which can deliver five times better performance of comparatively priced competitor products.
  • HP TippingPoint is known for its NGFW's simple, effective and reliable implementation. The security effectiveness coverage is high with over 8,200 filters that block known and unknown threats and over 383 zero-day filters in 2014 alone.
  • McAfee NGFW provides "intelligence aware" security controls, advanced evasion prevention and a unified software core design.
  • Barracuda purports the lowest total cost of ownership (TCO) in the industry due to advanced troubleshooting capabilities and smart lifecycle management features built into large scaling central management server. The NGFW is also the only one that provides NGFW application control and user identity functions for SMBs.
  • Juniper SRX is the first NGFW to offer customers validated (Telcordia) 99.9999% availability (in its SRX 5000 line). The SRX Series is also the first NGFW to deliver automation of firewall functions via JunoScript and open API to programming tools. Open attack signatures in the IPS also allow customers to add or customize signatures tailored for their network.
  • Although we will dive deeper in individual NGFW products in the product profiles, it is clear each NGFW vendor has established a foothold in unique areas that sets them apart from the rest. The key for customers is to identify the deciding differentiators that meet and/or exceed their needs.

    Which is the best NGFW product for you?

    The stratagem to thwart attacks on enterprise network environments will always be based on risk. The level of protection (controls) should be commensurate with the value of the asset (risks). If protection requires a NGFW, familiarization of NGFW vendor products and models to fit your organization and business model is critical.

    For example, if an organization is a small to medium-sized business, it may not consider the McAfee NGFW since its SMB appliance requires the Firewall License only, with its somewhat limited feature set. Barracuda similarly has a NGFW for large enterprises and a firewall offering for SMB, each with separate appliances and licenses.

    All vendors considered here offer NGFW products for large enterprises. Check Point, Palo Alto, Fortinet and Cisco -- in particular -- stood out in the April 2015 Gartner Magic Quadrant for Enterprise Network Firewalls. The remaining NGFW products fall in the lower left-hand quadrant of the report, where they identify as "niche players." Niche players, for example, include those NGFWs offered primarily to SMBs. Clients that this author has encountered in assessment work, meanwhile, have commented on features available in their NGFW of choice but have not activated due to either time constraints or sufficient knowledge on how make use of features.

    Consider the following criteria in selecting the NGFW vendor and model for your enterprise: identify the players; develop a short list; perform a proof of concept; make reference calls; consider cost; obtain management buy-in; and work out contract negotiations. TCO is also critical. Lastly, but no less important, consider the skill set of your staff and the business model and growth expectation for your enterprise -- these are all important factors in making your decision.


    Foundries Accelerate Auto Efforts | killexams.com real questions and Pass4sure dumps

    Foundries are ramping up their efforts in automotive chip production in preparation for a surge in semiconductors used in assisted and autonomous driving.

    All of the major foundry vendors are scrambling to assemble the pieces and expand their process portfolios for automotive customers. The foundries are seeing a growing demand from automotive IC customers amid the push toward advanced driver assist systems (ADAS), electric/hybrid vehicles and traditional cars with more connectivity features. Automotive also is attractive for foundries because many devices don’t require leading-edge processes, meaning a large number of vendors can participate.

    Automotive isn’t a new market for foundry vendors. In fact, many of them have participated in the sector for years. Fabless design houses with automotive chips outsource their production to the foundries. Even automotive IDMs, which have their own fabs, outsource some chip production to the foundries.

    Until recently, though, automotive wasn’t a top priority for most foundries. “In the past, automotive was not considered a big money maker for the foundries,” said Jim Feldhan, president of Semico Research. “It took too long to qualify a process. There weren’t a lot of automotive customers, and it wasn’t a high-volume market when compared to computing or communications.”

    The attitude has recently changed, however. “The recent demand for automotive electronics, such as ADAS, AI, sensor hubs and connectivity, has changed the foundry perspective,” Feldhan said. “The automotive market is wide open (for foundries now). TSMC has qualified their automotive process and others are doing the same. The automotive supplier landscape has also been transformed. Because of Artificial Intelligence and the ‘big brain’ requirements for autonomous driving, there is now a scramble for new designs from companies such as Intel, Nvidia and Qualcomm. Of course, Nvidia and Qualcomm are major foundry customers.”

    Both automotive device makers and foundries are benefiting from a surge in demand for various devices in cars, such as analog, memory, MCUs, sensors and others. In fact, the average semiconductor content per car has grown from $62 in 1990, to $312 in 2013, and to $350 today, according to figures compiled from TI, IHS and others. By 2022, the figure is projected to reach $460, according to IHS. But even today, the chip content for hybrids is $600, while luxury models are hovering around $1,000, according to McKinsey.

    In total, the automotive semiconductor market is expected to reach $41.7 billion in 2017, up 11% over 2016, according to Semico. In 2016, the automotive IC market grew 8.1% over 2015, according to Semico. The figures include power discretes, sensors and optoelectronics.

    Still, the automotive IC market represents a small percentage—roughly 10%—of the overall IC market. It pales in comparison to the smartphone chip market. “Keep in mind that 100 million vehicles are sold each year compared to 2 billion cellphones,” Feldhan said.

    Automotive represents a small but growing business for foundries. Some foundries have seen their automotive businesses grow from zero a decade ago to about 5% to 10% of their overall sales today. Others have a larger percentage mix in automotive.

    But foundries face some challenges in automotive. The requirements are rigid, while the product qualification process remains arduous and expensive. And competition is fierce.

    Inside the carGenerally, the industry divides a car into five main domains—body, connectivity, fusion/safety, infotainment, and power train. Body involves the basic body controls, such as the door access, lighting and windows. Connectivity consists of the cellular, WiFi and related capabilities.

    Fig. 1: Semiconductors used pervasively in automobiles. Source: UMC

    Fusion/safety consists of cameras, LiDAR and radar. Infotainment involves driver information and entertainment. And the powertrain domain includes engine control and the transmission. Some fold the chassis, such as the brakes and steering, into the powertrain domain.

    Fig. 2: Diversified silicon technologies required. Source: UMC

    Each car also has dozens of specialized embedded computers called electronic control units (ECUs), which control the various domains in a vehicle. The ECUs are all connected via a network in what some call a distributed architecture.

    Many vehicles will continue to incorporate a distributed architecture, although some higher-end models are undergoing some radical changes. “We are really at an inflection point now, where the amount of content that’s coming into the vehicle is no longer sustainable by the current architectures,” said Glen De Vos, chief technology officer at automotive technology giant Delphi. “We have to make a change there in order to enable that content will continue to grow and grow in a cost-effective way.”

    OEMs can no longer just cram more electronics into in cars. “As you continue down that line, this is where you basically run out of headroom in the current architectures. We can’t simply add more content, more ECUs and more wiring every time we add another function,” De Vos said at a recent event. “The vehicle cost structure can’t afford it. The OEMs can’t afford it. When you think about how you budget a vehicle, you only have so much to spend on all that content.”

    To address the issues for some models, Delphi has developed a domain centralization architecture. For this, electronic content is aggregated in fewer multi-domain controllers as a means to reduce cost and weight.

    Fig. 3: Vehicle computing evolution. Source: Delphi

    Audi, for one, is using this concept in its recently announced A8 luxury car. The A8 also incorporates some autonomous driving capabilities. It can automatically take charge of driving in slow-moving traffic at up to 37.3 mph on freeways.

    Fig. 4: Delphi’s Smart Architecture. Source: Delphi

    The A8 has “Level 3,” or “limited self-driving” capabilities. In the ADAS world, “Level 1” involves the automation of one or more control functions in a car, while “Level 2” is the automation of two or more functions. Tesla is currently at “Level 2.” “Level 4” has high self-driving capabilities, while “Level 5” is fully autonomous, steering-wheel optional.

    Full self-driving technology may not reach the mainstream for a decade or longer. Even if it never reaches the masses, ADAS is fueling the development of new devices on several fronts. According to Semico, technology drivers include adaptive cruise control, auto parking, and collision avoidance, lane departure warning and blind-spot detection.

    Outsourcing trendsFor years, Bosch, NXP, On Semiconductor, Renesas, STMicroelectronics, TI and other IDMs with fabs have dominated the automotive landscape.

    Generally, automotive devices are manufactured in both 200mm and 300mm fabs. “In automotive, you have ADAS, telematics and infotainment. We have the miniaturization of things like LiDAR. That’s going onto a single chip. This is all happening, for the most part, on 200mm,” said Mike Rosa, director of marketing for Applied Global Services at Applied Materials.

    Up until a decade or so ago, X-Fab Silicon Foundries was one of the few foundries that served the automotive sector. Other foundries did some business with automotive customers, while some stayed on the sidelines.

    Over the years, though, there were two main events that changed the landscape for foundries in automotive. First, many IDMs went to a “fab lite’’ or fabless model. Second, the chip content in cars began to grow.

    Starting in the 2000s, the cost of building new fabs and developing leading-edge processes became too expensive for many IDMs. Many stopped building leading-edge fabs. In general, they kept their proprietary processes in-house and outsourced some production to the foundries.

    Automotive is just one of the product areas outsourced to foundries. “Historically, in automotive, a lot of the focus has been at IDMs. Foundries had some of that business,” said Walter Ng, vice president of business management at UMC. “But with the movement towards fab lite on the IDM side, a lot more of that is coming out.”

    Foundries are also seeing a different product mix being outsourced from the IDMs. “Traditionally, you’ve seen some of the less critical automotive products being manufactured at foundries,” added Wenchi Ting, associate vice president at UMC. “Infotainment is an example. Display drivers are another example.”

    To one degree or another, IDMs also outsource analog chips, mixed-signal ICs and sensors. “Traditionally, for the more critical applications like the power train or the chassis control components, the IDMs tend to make these components themselves,” Ting said. “Going into the future, this may change. We’re seeing chips being planned for future engine control, which requires tremendous memory bandwidth. The chips need embedded flash memories together with state-of-the-art logic processes.”

    In fact, IDMs already are outsourcing some of the critical applications to foundries. For example, ADAS requires advanced microcontrollers (MCUs), and many IDMs don’t have the logic processes to make them. “They are using 28nm and 40nm for making the processors for ADAS, for example,” Ting said. “That’s a sector where most of the automotive IDMs cannot serve. They simply don’t have the in-house capabilities.”

    Another area involves power discretes, which are used in hybrids and electric vehicles. IDMs still make discretes, although they are turning to foundries for other reasons. “People are running out of capacity for power discretes,” he said. “Those products are coming to foundries.”

    Besides the outsourcing trend, foundries have witnessed another major event in more recent times. “We started to see a real inflection point over the last couple of years,” said Mark Granger, vice present of automotive at GlobalFoundries. “You can start to see the amount of semiconductor content in a vehicle starting to grow. With the addition of ADAS, there is certainly a surge over the last couple of years.”

    As a result, foundry vendors continue to bolster their efforts in automotive. Each vendor has a different strategy. Many take processes from other markets and offer them for automotive customers. Many have also developed processes tuned for automotive.

    There is one constant, however. The requirements are more stringent in automotive, compared to other markets. “You want to strive towards zero dppm, or defective parts per million,” Granger said. “You work continuously to improve both on the foundry side as well as the device manufacturers’ side to get to the highest levels of reliability and the lowest level of failures in customers’ hands.”

    Both automotive device makers and foundries must adhere to various quality standards, such as the AEC-Q100. This standard involves the failure mechanism stress test for chips. There are other requirements as well. “There is a reason for (these requirements),” said Rajeev Rajan, vice president of IoT at GlobalFoundries. “It’s functional safety. Whatever goes into manufacturing and product development needs to tie back to the regulatory aspects for safety as well as the traceability of parts if anything goes defective.”

    These requirements create some challenges. For example, foundries typically develop a process technology and qualify it with a relatively normal sampling size.

    In automotive, though, foundries must conduct more and rigorous inspection, test and other screening steps. “You can’t have parts fail because it impacts safety,” said Robert Cappel, senior director of marketing at KLA-Tencor. “So you’re seeing a much different level of quality and yield. There also is a focus on latent reliability defects. A part may pass a test but fail over time within a car. The requirements are changing.”

    This becomes particularly important as carmakers begin pushing logic—the brains behind autonomous and assisted driving—into the most advanced process nodes. The goal is to use the latest technology to achieve performance improvements, but how these devices will fare over time in an automobile’s harsh environment isn’t clear.

    “Reliability is critical,” said Tom Quan, a director at TSMC. “Right now we’re at 16nm FFC, moving down to 7nm, which will be the autonomous driving platform. There’s a 150˚ C junction, IP, and an SoC has to be validated. It also requires IP that is ISO 26262 compliant, which is more like a checklist, and the IP has to be certified by the manufacturer.”

    Along with this, customers are looking for the potential failure rates for devices. It falls back on the foundries to do more inspection, testing and simulation using a larger sampling size, all of which takes time and adds cost to the process.

    MCU process trendsDevice makers, meanwhile, are outsourcing a slew of products to the foundries, including MCUs. MCUs perform the central processing functions in a system. More than 100 MCUs are used in a vehicle in various places.

    For instance, MCUs are used in the body control domain. “Those use microcontrollers that range from 8- and 16-bit with a certain amount of integrated nonvolatile memory combined with high-voltage analog content to interface with the battery,” said Ron Martino, vice president of application processors at NXP.

    Other domains require high-end MCUs. “As time has gone on, different requirements have pushed into 32-bit and now 64-bit compute (functions),” Martino said.

    Last year, for example, NXP unveiled the i.MX 8 family of 64-bit applications processors. The devices are designed to enhance the automotive dashboard graphics, such as the instrument clusters, infotainment visuals, heads-up displays and rear-seat screens. Based on a 28nm FD-SOI process from Samsung, NXP’s devices include up to six 64-bit ARM v8-A cores, DSPs and memory. Many of NXP’s MCUs use bulk CMOS, although FD-SOI makes sense for the i.MX 8 and related chips.

    “(FD-SOI) has a much larger dynamic range in terms of the ability to tune the device,” Martino said. “That allows us to get a much wider range of power/performance optimization on a single platform.”

    Not all are pushing FD-SOI, however. Many say bulk CMOS is suitable for most applications. Both camps, however, are seeing other integration trends for MCUs. “For automotive, we are getting requests to put embedded flash together with BCD,” UMC’s Ting said. “It’s an MCU with BCD and embedded flash. This is replacing existing solutions, which require an external standalone memory to record certain parameters for the car.”

    In automotive, bipolar-CMOS-DMOS (BCD) is a specialty processes used for motor-control applications, such as mirror positioning and seat adjustment. BCD combines the advantages of bipolar for analog, CMOS for digital, and DMOS for power and high-voltage.

    MCUs are also integrating NOR or EEPROM. The mainstream market for embedded NOR flash is 40nm and above, although the industry is moving toward 28nm.

    NOR flash suffers from data loss over time, however. So, the automotive industry is taking a harder look at the next-generation memory types, such as MRAM and ReRAM. These technologies have the non-volatility features of flash with unlimited endurance.

    “The emerging memories, such as MRAM and ReRAM, are very attractive,” Ting said. “They have characteristics that the traditional memories can’t match. The problem is that they are only in small-scale production at most today. The industry needs to accumulate more experience and flush out all of the potential problems. That will take some time.”

    Driverless carsClearly, meanwhile, autonomous driving is receiving a lot of attention, if not hype. But the technology and the associated chips are in its infancy.

    For example, Audi’s A8 car incorporates a central driver assistance controller, dubbed the zFAS, which enables Level 2/3 autonomous driving. Developed by Delphi, the zFAS board incorporates some older-generation chips. The latest chips weren’t available when Delphi began the project.

    The board, for example, includes Mobileye’s EyeQ3 processor and Nvidia’s Tegra K1, according to Audi. Nvidia’s Tegra K1 is a 28nm GPU. Based on a 40nm process, the EyeQ3 enables visual recognition and detection. Mobileye, which was recently acquired by Intel, is also developing chips based on 28nm FD-SOI and finFETs at 10nm and below.

    Today’s autonomous-enabled cars also incorporate 6-8 cameras, 6-8 LiDAR devices and 6-8 radar units, according to Delphi’s De Vos. With those devices, a vehicle is collecting 50 terabytes of data every hour, but that’s not nearly enough for full self-driving technology.

    Fig. 5: ADAS Centralized fusion/control. Source: Delphi

    “Even with all that data, the perception system is still the limiting factor in automated driving,” De Vos said. “We are not at that point where our sensor systems are even close.”

    For Level 5, a vehicle may require the ability to collect 150 terabytes of data an hour, meaning the industry requires some new breakthroughs to enable the next wave of both traditional and self-driving cars.

    So what’s next? “ADAS and autonomous require a lot of sensors,” GlobalFoundries’ Granger said. “You also have to process all this data. There are two trends in the industry. One is to make the sensors smart. So there is processing in each one of those sensors.”

    Then, the industry is developing more powerful MCU/MPUs as a means to handle the data. “When you start to get into Level 3, 4 and 5, you need advanced nodes to be able to process all of the sensor data in one holistic view to enable the car to make the best decision,” Granger said.

    There is also work taking place in LiDAR and radar. Radar detects objects, but it can’t discern one object from another. Using laser-based light, LiDAR measures the distance to a target with more precision. In some cases, LiDAR devices are based on gallium nitride (GaN), a III-V technology.

    For radar, a device may incorporate an MCU, DSPs as well as RF blocks based on silicon-germanium (SiGe) at 77-GHz. Seeking to reduce the cost of radar, GlobalFoundries and its partners are developing a CMOS-based mmWave radar chip. Using 22nm FD-SOI, the device would include the MCU as well as short- and long-range radar. It also eliminates the need for SiGe.

    “It allows you to do fast processing, so that people can implement radar that will attempt to improve upon the previous capabilities and to challenge LiDAR,” he said. “LiDAR is a very interesting technology, but it has also traditionally been expensive.”

    Autonomous driving, of course, requires a software component. For example, startup AImotive recently rolled out a neural networking technology for the automotive industry. “All of these sensors are great,” GlobalFoundries’ Rajan said. “But a lot of stuff they do is triangulate data from different input points. You need something in the backend, either inside the car or in the cloud, that has the ability to process this data, crunch it away and give meaningful and actionable decisions as well as focused responses back to the car or anybody in control from a mission critical standpoint.”

    Clearly, automotive is bringing new opportunities for foundries. Automotive may take more time to win customers, but it’s a more steady and predictable business, at least for now.

    Related StoriesElectric Vehicles Set The PaceRethinking Car DesignConnecting The CarAutomotive’s Unsung TechnologyAutonomous Cars Drive New SoftwareSelf-Driving Cars Rattle Supply ChainThe LiDAR Gold RushRethinking Verification For CarsTest More Complex For Cars, IoT



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