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Nvidia, Oracle extend Cloud GPU Ties for AI, HPC | killexams.com existent Questions and Pass4sure dumps

Oracle is taking fraction with Nvidia to convey the GPU chief’s unified AI and HPC platform to the general public cloud for accelerating analytics and desktop discovering workloads.

The stream makes Oracle the primary public cloud seller to pilot Nvidia’s HGX-2 platform, the partners stated this week. The Oracle cloud will wait on both bare-metallic and virtual computer cases of the HGX-2, which is designed to “multi-precision computing,” double and single-precision floating aspect for remedy HPC, and decreased precision (FP16 and INT8) for AI.  Nvidia’s NVSwitch interconnect with NVLink know-how offers 300 GB/sec of GPU-to-GPU bandwidth to in the reduction of the information bottlenecks encountered with HPC and profound getting to know workloads.

The partners talked about Wednesday (Oct. 10) their collaboration addresses turning out to exist exact for cloud-based mostly GPU acceleration in records analytics as well as profound and desktop gaining information of applications. “other than enabling HPC and AI workloads, we’re concentrated on information science and analytics as an immense enviornment of investment,” Karan Batta, an Oracle product supervisor, referred to in a blog post.

The increased collaboration with Nvidia for cloud-based mostly GPU acceleration underscores Oracle’s strategy of stirring from a database dealer to a participant in the cutthroat public cloud market. much of the emphasis has been unique platform and infrastructure functions along with computerized capabilities akin to “self-using” cloud database carrier unveiled in August. Batta notable that these and different services target facts science teams, enabling them to work collaboratively on huge data initiatives.

Oracle prior to now supported Nvidia’s Pascal GPU architecture cloud circumstances and, extra recently, provided naked-metallic circumstances of its Tesla V100 Tensor Core GPUs. those chips were used to accelerate profound researching workloads.

along with wait on for the HGX-2 platform, Oracle stated its unique cloud instances additionally can exist backed through as much as 48 cores of Intel Xeon processors (working at three.5 GHz with rapid increase). the brand unique instances should exist purchasable in early 2019, the cloud vendor stated, noting it additionally had plans to offer a 16-manner case in the future.

The collaboration is the latest endeavor through Oracle to differentiate its cloud choices from public cloud leader Amazon internet capabilities, Microsoft Azure and Google Cloud. The partnership besides reflects Nvidia’s thrust into high-end statistics analytics via its simply-announced RAPIDS platform, which Oracle is besides supporting.

RAPIDS is a collection of application libraries for operating facts science and analytics pipelines completely on GPUs. The open supply libraries are intended to leverage GPU parallel processing and excessive-band reminiscence by way of the Python programing language. among the many makes Use of is accelerating desktop studying training whereas improving model accuracy.

RAPIDS will exist obtainable this week on Oracle’s cloud infrastructure by the Use of Nvidia’s GPU cloud service.

Oracle besides introduced aid for Nvidia’s GPU cloud container registry that enables cloud clients to set up container purposes and frameworks on Oracle’s GPU-accelerated cloud circumstances. those cases are available in diverse areas in the U.S. and Europe.


Kinetica could enhance NVidia In $70B massive facts Market | killexams.com existent Questions and Pass4sure dumps

SAN FRANCISCO, CA JUNE 23, 2018: Orange nVidia emblem on balloon in an city environment

just because you delivery an organization and raise tens of hundreds of thousands of greenbacks to gasoline it exist growth, there's no assure you acquire what it takes to build a titanic enterprise.

in fact, some 60% of founders carry out not live to inform the tale their collection D circular of project funding.

This involves intellect in in view that San Francisco-based database corporation, Kinetica. founded in 2009, Kinetica raised $50 million in June 2017 -- bringing its complete funding to $63 million. Six months later, Kinetica's board changed its cofounder and CEO -- Amit Vij -- with Paul Appleby, an experienced revenue government.

Kinetica -- which looks completely blissful with its tackle "the perception engine for the fierce facts fiscal system" -- says that its know-how "combines simulated intelligence and desktop learning, facts visualization and placement-primarily based analytics, and the accelerated computing energy of a GPU [Graphical Processing Units made by the likes of Nvidia to shun video games] database."

effortlessly put, Kinetica joins different companies -- similar to MapD, about which I wrote in July and lately modified its identify to OmniSci -- that location the GPU on the core of their technology rather than the CPU [central processing unit] that powers usual databases. Given the demand for quick graphical betray of information analysis, the GPU-based mostly technologies acquire to acquire an audience beyond video game enthusiasts and animation enthusiasts.

To its credit, Kinetica has developed relationships with businesses and expertise companions to deliver this conception to existence. Kinetica seeks consumers from industries including healthcare, energy, telecommunications, retail, and economic features. And its know-how and advertising and marketing partners consist of NVIDIA, Dell, HP, and IBM.

Kinetica competes with Microsoft, Oracle and IBM which give usual databases.

I carry out not suppose Kinetica should still exist concerned these competitors on account that the startup is so small. but due to the fact Kinetica and OmniSci -- which counts the chipmaker as an investor -- are the Use of the NVidia GPU -- peculiarly the Tesla and DGX for AI, information scientists and titanic information researchers; and GRID for cloud-based visible computing users, according to its latest quarterly document -- their success may still exist efficient for NVidia investors.

(I haven't any fiscal pastime in the securities outlined).

The brains at the back of Kinetica are Vij and his Kinetica co-founder Nima Negahban. As Fortune wrote, "They worked at the u.s. military Intelligence and safety Command and the countrywide security company creating a device to track and trap terrorists in real-time. The U.S. Postal provider has used Kinetica in view that 2014 in a gadget that optimizes routes and tracks programs."

Vij misplaced the remedy spot at Kinetica to Appleby in December 2017. The enterprise changed into attempting to find "income momentum" and in Appleby -- who had most recently served as president, global sales and advertising, at BMC application (and in the past as an government at Salesforce, C3 IoT, and Siebel programs) -- Kinetica director, Ray Lane, appeared to believe he healthy the bill.

As Lane notable remaining December,

2017 has been a breakout year for Kinetica, doubling headcount whereas it onboards and grows unique consumers and partners All over.  there is appreciable exact these days for Kinetica’s speed and capabilities produced with the aid of its autochthonous GPU-accelerated, in-reminiscence architecture.  Paul acknowledges the strategic nature of the business records challenges Fortune 2000 companies face, and the way Kinetica can speed up precise-time insights from any records sources, regardless of volume, pace and constitution.  Paul’s confirmed journey main international extend teams, plus the constrain to elect Kinetica to the next stage, makes him a discrete alternative for Kinetica.

Appleby has delivered growth -- but isn't yet profitable. As he referred to in a September 16 interview, "initially of the 12 months they had 70 to 80 americans and now they acquire a hundred and ten. in the first half of 2018, they grew bookings 156% and the number of web unique customers via one hundred ninety%. a significant variety of their latest valued clientele are expanding their relationship with Kinetica. They could grow [with a scalable business model]."

To entangle Kinetica to the next stage, Appleby notable the business is equipped by feature. "We’re an innovation-pushed company, and the vast majority of their personnel, two-thirds of the company, are engineering and innovation-focused. just about half of their personnel are primarily based out of their Arlington, Virginia engineering office. Their admin, finance, individuals, and advertising features are San Francisco-based mostly, and their earnings crew is distributed across Europe, Asia, and the U.S.," he pointed out.

Appleby believes that All and sundry who works with a company -- including its management, employees, and companions -- should still exist "aligned to a common set of strategic dreams and goals. As such, developing an environment where All parties believe possession of the business way and alignment to it truly is the exact priority. Their objectives span product, ecosystem, client success, and tradition. They Use them to formulate their personnel' MBOs [Management by Objectives], and to e-book their company course holistically."

He chairs Kinetica's executive leadership group (ELT) which includes executives from its "product construction, client success, revenue, advertising, and finance [functions]. ELT meets continuously to plot, track, and execute on their key objectives. each member of the crew has specific dashboards that map to key metrics that measure progress in opposition t their aims."

Kinetica holds All and sundry dependable for effects. "On a quarterly foundation, their government group determines key effects they want to obtain, in response to their strategic objectives. These leaders then meet with their groups and examine MBOs for each employee that support us meet those pursuits. The MBOs trade each quarter, however they are All the time formulated to fulfill their strategic dreams," Appleby informed me.

every person in the business knows how their success can exist measured. As he mentioned, "We link metrics and targets by using following the objectives & Key consequences (OKR) model used with the aid of facebook, Amazon and Salesforce. The metrics, or key outcomes, are in location, at company, departmental and particular person ranges to gauge development. every worker has a selected set of measurable, quarterly MBOs that act because the metrics to music progress in opposition t their company ambitions."

Kinetica's MBOs materialize tons more selected and measurable than its desires/goals which are supposed to inspire. for instance, Appleby observed one of the crucial company's pursuits is "change the realm by using helping companies innovate and transform in the location up-massive information world."

Two MBOs associated with that purpose appear to power individuals to discovering decent income leads and reaching immoderate client retention. the first MBO is "establish the number of companies that are tackling unique initiatives. This gives us an illustration that groups can Use their technology to drive their enterprise ahead as they enter the extreme records fiscal system."

The 2nd is to achieve "excessive consumer retention quotes [which] provide us a way to exhibit we’re delivering cost and are vital to their valued clientele’ enterprise," he mentioned.

With Kinetica and OmniSci becoming abruptly, exact for NVidia chips may grow as smartly. In its second quarter, NVidia enjoyed seventy seven% boom in its so-known as Datacenter profits, which protected Tesla, GRID and DGX, in accordance with its 10Q.

It continues to exist to exist seen even if that might exist enough to propel its stock.


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After spending time at a London fintech accelerator last year, enterprise database startup ZeroDB scrapped its first business way and mapped out a unique one. By January this year it had a unique name: NuCypher. It was no longer going to try to persuade enterprises to switch out their Oracle databases — but rather to sell them on a specialized encryption layer to enhance their capacity to accomplish titanic data analytics by tapping into the cloud. Its slogan: cadaver armor for titanic data.

Today it’s launching an open source version of its general release product here at TechCrunch Disrupt unique York. At this point, the almost 1.5-year-old startup is besides running a handful of pilots with major banks, says co-founder MacLane Wilkison.

“It’s a combination of cloud and titanic data,” he says of the underlying drivers which the team reckons are creating a need for the technology. “Now All of a sudden you’re working in computing environments that are distributed across hundreds or thousands of machines, and that could exist spanning both some on-prem, some private and even public cloud. And that sort of scenario presents a lot of unique and different security challenges.”

Instead of building an open source end-to-end encrypted database, NuCypher is selling a proxy re-encryption platform for corporates with big amounts of sensitive data stored in encrypted databases to let them securely tap into the power of cloud computing. An concept that might need a bit of explaining to appreciate, but one that’s grounded in a genuine need — at least based on what NuCypher’s early banking partners are telling it.

On the competitors front Wilkison names the likes of HP-owned Voltage and Protegrity as the largest existing players in the space. Albeit, he says they’re both doing tokenization of data, whereas NuCypher reckons proxy re-encryption technology offers greater security for certain types of data.

Unlike some other approaches to processing titanic data in the cloud, he emphasizes that NuCypher is not using tokenization to mask any data — arguing this is necessary for the target customers because certain types of data when masked with tokens can exist vulnerable to statistical attacks.

While proxy re-encryption is an existing district of cryptography, applying it to titanic data is what’s novel here, according to Wilkison, who says the tech has mostly been used in academia thus far. “We’re the only people that applied it to titanic data platforms enjoy Hadoop and Spark,” he says. “As far as I know we’re the only one using proxy re-encryption in business.”

So while the team’s early ideas focused mostly on looking at data archiving and encryption to enable banks to fabricate Use of cloud storage, he says the business was pulled onto its current rails after banks asked if they could apply the encryption tech the team had been structure for data archiving to titanic data cloud processing.

Safe to say, this mini pivot is a confidential sage for enterprise startups — after all, who knows better the business needs than the target customers?

“When they originally started the company, my co-founder and I had built an open-source database and then an encrypted database that allows you to operate unencrypted data without sharing encryption keys with the database server… What the banks were particularly interested in was taking some of what they had built for that and applying it to more compute-heavy type of workloads,” says Wilkison.

“After a era of talking to customers… they took some of what they had built for that and made it into a more generalized encryption layer for different platforms — specifically for the titanic data space. So Hadoop, Kafka and Spark.”

So what is proxy re-encryption — aka NuCypher’s “secret sauce,” as Wilkison puts it — and why is the technique useful for banks?

“Proxy re-encryption is a set of encryption algorithms that allow you to transform encrypted data. Specifically… it allows you to re-encrypt data — so you acquire data that’s encrypted under one set of keys, you can re-encrypt the data without de-encrypting it first, so that now it’s encrypted under a second, different set of keys,” is how Wilkison explains it.

He gives the case of a person who has some encrypted files stored in Dropbox. If they want to share the files with someone else that could exist achieved by downloading them, decrypting them with their key and then re-encrypting them with the public key of the person they want to share with. But obviously — at scale — that’s a pretty network-intensive and cumbersome process.

Even more naively, this person could just share their private encryption key with the person they want to share the file with. But then they’re abandoning All control of their security.

Clearly neither scenario is ideal for NuCypher’s target customers — with their vast lakes of sensitive, highly regulated data. This is where NuCypher reckons proxy re-encryption can step in to offer an edge.

“What I can carry out with proxy re-encryption that’s much more elegant and secure than either of those alternatives is I can basically delegate access to my encrypted data to someone else’s public key,” he adds.

The platform creates a re-encryption token off of the public key of the entity with whom its customers wants to share data. That token can then exist uploaded to the cloud where the third party can access it — in turn enabling them to decrypt and access the data.

Wilkison says re-encrypted tokens can exist created and used to delegate access to “as many people as I like.”

Ensuring compliance with regulations around the processing of sensitive data — data such as a bank or healthcare company might hold — is one key selling point for the platform.

He points to a regulation enjoy HIPAA, which sets standards for protecting healthcare data, as one case where a lot of supervision is needed when handling data to ensure compliance. He besides flags up the European Union’s incoming GDPR (General Data Protection Regulation), which ramps up penalties for violations of rules on processing citizens’ personal data, as another instance of data-centric laws creating data processing pain-points that NuCypher’s platform is setting out to fix.

Other target data-laden industries could include telecoms and insurance, though the team has kicked-off focusing on fiscal services, and the current pilot facet of the platform is with “major banks.”

Wilkison says there are essentially three main use-cases for the platform:

  • “cloud enablement” — so giving target customers a way to walk their on-premise Hadoop titanic data workloads to the public cloud and fabricate Use of services like AWS, particularly for “burst or transient workloads.” “What they carry out there is give them a way to maintain their encryption keys in their own data centers, under their control so they can Use the throng to store and process data but they don’t necessarily acquire to trust the throng with their encryption keys,” he adds.
  • “regulatory compliance” — currently NuCypher is working with customers in the U.S. and Europe needing to comply with regulations such as HIPAA, PCI, GDPR and PSD2.
  • “secure sharing of sensitive encrypted data” — with multiple third parties, be it a customer, partner, supplier or even a regulator. On this he besides notes one of the benefits is that the system segregates the data and the encryption keys — which means, for example, a regulator could not subpoena the cloud provider in order to entangle their hands on the decrypted data.”It’s very important, particularly in fiscal services, for customers to acquire that segmentation between the data and the keys,” he adds.
  • Another profit he notes is that NuCypher’s proxy re-encryption technology enables it to give customers the capacity to manage access controls without needing to provide replete access to the data — which means it can remove any single point of failure (i.e. via an admin who has to acquire replete access control to All of the data).

    “With NuCypher a hacker would acquire to hack into each node individually in order to entangle All the data,” he adds.

    Given the complexities of the technology, customer education is clearly one of the titanic challenges, with Wilkison saying this boils down to explaining how the approach differs from standard encryption.

    And on that front, he says one selling point for the platform is that the proxy re-encryption tech works with NIST standardized encryption algorithms. Which means NuCypher customers don’t acquire to abandon the tried and tested encryption algorithms they’re restful using, such as AES-256, in order to fabricate Use of the tech.

    “That was one of the pieces that they added that took a pretty significant amount of research to develop for us — to entangle proxy re-encryption to work with things like ECIES, which is a standard elliptic curve, NIST-certified,” he notes. “So they can Go to a customer and say, everything that we’re doing on a crypto flush is very standardized, very well understood by industry. So they’re not having to depend on newly rolled crypto.”

    NuCypher’s platform exists as an SDK and an encryption library, so its business model is licensing the software — it’s not hosting any data itself, confirms Wilkison; customers can install the software on premise, such as within an existing Hadoop deployment, or directly in the cloud on the infrastructure they’re managing.

    Funding-wise, the team has raised a $750,000 seed round to date, from Valley investors including basis Ventures, NewGen Capital and some angels. It besides went through Y Combinator final summer. Wilkison says it will exist looking to raise again in Q3 this year.

    How titanic carry out they reckon this market is? Wilkison says he’s hoping the current six to seven pilot customers of NuCypher will turn into “high double digit” or maybe “low triple digits” in a year’s time. But with those target big enterprises typically spending vast amounts of money on securely storing the sensitive data they’re entrusted with, there’s besides a very sizeable incentive for them to shift some of that compute load into the cloud. And, potentially, a lot of money at stake if NuCypher can convince them to buy in.

    [gallery ids="1490532,1490543,1490542,1490539,1490537,1490533"]

    Judges mp;A

    Q: Can you talk a bit more about how far along you are with some of the early clients?A: We’re in pilot stage prerogative now. The bulk of their early customers are in fiscal services. We’re starting to entangle traction in healthcare and telcos as well. Pilot facet at this stage.

    Q: inform me a bit more on the competitionA: There’s a couple of ways to search at this. One: the platforms that they support carry out acquire some autochthonous data protection built in. So Hadoop for example. These tend not to exist robust enough for the types of enterprise customers that we’re working with. Other alternatives include data masking and tokenization. HP Voltage for example.

    Q: You worked before at Morgan Stanley. Why did you leave a steady job with nice salary and Wall Street and went into this kindly of adventure?A: Ultimately I wanted to entangle back to a more technical role, and actually start structure a product in a company again – as opposed to structure fiscal models and pitch decks

    Q: And this is the actually launching of the product?A: We’re launching the open source version. We’ve had Hadoop available for a while. And then Kafka is launching as well

    Q: What did your mother gainsay when you told her that you were leaving Morgan Stanley for this adventure?A: She was supportive. Although maybe didn’t quite understand what they were doing

    Q: Can you inform me more about the implementation? What does it search enjoy as you deploy to enterprise – how carry out you entangle All of their existing data encrypted and how carry out you carry out key management?A: On the key management side they actually integrate with hardware security modules – so at lots of banks they Use HSM from vendors enjoy Thales or SafeNet.

    For Hadoop they encrypt at the HFS layer. And everything is transparent to applications running on top of Hadoop, so it doesn’t change the suffer for someone running Hive queries for example.

    And they besides integrate with access control tools enjoy Ranger and Sentry. So people can maintain using the standard tools that they use.

    Q: Is your business a classic SaaS model?A: We’re not hosting anything. It’s not software as a service. They acquire term-based subscriptions, and then besides a consumption-based model for cloud deployments.

    Q: How carry out you intend to Go to market? Sales force? direct sales?A: Some combination of direct sales, which we’ve done today, and then besides the channel partners and titanic data vendors… and the cloud service providers as well, folks enjoy Amazon and Microsoft.

    Q: Who are your main competitors?A: The data masking and tokenization companies are the one they shun into most regularly. Voltage which is now fraction of HP. In Europe they descry a company called Protegrity pretty frequently. And then as I mentioned before a lot of the underlying platforms will acquire some sort of protection tools natively.

    Q: carry out you shun into people enjoy Ciphercloud or Ionic?A: Not so much anymore. We’re similar in some ways to them… we’re more focused on infrastructure enjoy Hadoop and data platforms

    Q: How many people are you now?A: We’re the two founders and then seven people total on the team

    Q: And how much money did you raise?A: We’ve raised $750K so far from Y Combinator, NewGen Capital and basis Ventures

    Q: How long ago?A: final fall

    Q: How hard would it exist for your competitors to replicate the work that you’ve done?A: Certainly it’s a lot easier now that it’s open source… That said they carry out acquire an open core approach so they acquire certain enterprise features that are still proprietary that are only available in the enterprise version. Additionally if the Hadoop vendors integrated what we’re doing natively into Hadoop that’s still just for Hadoop.

    So NuCypher’s meant to exist layered, it sits across All of the organization’s titanic data platforms. prerogative now they’ve Use Hadoop, Kafka, Spark. In the future that could include some unique SQL databases, and potentially structured databases as well

    Q: Judging from your suffer with your colleague how carry out you compare the American flush of mathematics and physics to the Russian one?A: The American approach is lacking. I’m hugely impressed. Not only is my co-founder Russian educated, and Russian born, a lot of their engineers are as well, so we’ve been very fortunate in that regard


    Transaction Processing Performance Council (TPC) Launches TPCx-HS Version 2 – Augmenting Its Arsenal of titanic Data Benchmarks – and Introduces Pricing Specification for Cloud ... | killexams.com existent questions and Pass4sure dumps

    SAN FRANCISCO--(BUSINESS WIRE)--Today the Transaction Processing Performance Council (TPC) announced the immediate availability of TPCx-HS Version 2, extending the original benchmark’s scope to include the Spark execution framework and cloud services.

    The original TPCx-HS benchmark was the industry’s first objective specification enabling measurement of both hardware and software including Hadoop Runtime™, Hadoop Filesystem API compatible systems and MapReduce layers. TPCx-HS Version 2 is designed to broaden the ambit of system topologies and implementation methodologies in a technically rigorous, directly comparable and vendor-neutral manner. TPCx-HS Version 2 models continuous system availability 24 hours a day, seven days a week and – as an “Express” class benchmark – is publicly available for download via the TPC’s Web site at the following URL: www.tpc.org/tpcx-hs.

    “Enterprise investment in titanic Data analytics tools is growing exponentially, to maintain pace with the rapid expansion of datasets,” said Tariq Magdon-Ismail, chairman of the TPCx-HS committee and staff engineer at VMware. “This is leading to an explosion in unique hardware and software solutions for collecting and analyzing data. So there is stupendous exact for robust, industry standard benchmarks to enable direct comparison of disparate titanic Data systems across both hardware and software stacks, either on-premise or in the cloud. TPCx-HS Version 2 significantly enhances the original benchmark’s scope, and based on industry feedback, they await immediate widespread interest.”

    TPCx-HS Version 2 was developed as researchers and industry experts identified titanic Data as a priority district for further benchmark progress during the 2016 TPC Technology Conference on Performance Evaluation and Benchmarking (TPCTC). This year’s TPCTC conference will exist held in Munich, Germany on August 28, co-located with VLDB 2017. Individuals who wish to contribute to the benchmark progress process are encouraged to submit abstracts via the following URL: http://www.tpc.org/tpctc/tpctc2017/default.asp

    Organizations interested in contributing to the TPC’s benchmark progress process are encouraged to become members. Additional information is available via the following URL: http://www.tpc.org/information/about/join.asp.

    Updated Pricing Specification

    TPC benchmarks are unique in that they provide the industry with verifiable performance, price-performance and availability metrics. Considering the emergence of cloud deployments, the TPC pricing specification has been updated to accommodate executing benchmarks in cloud environments. The unique specification is available via the following URL: http://www.tpc.org/tpc_documents_current_versions/current_specifications.asp.

    About the TPC

    The TPC is a non-profit corporation founded to define transaction processing and database benchmarks and to disseminate objective, verifiable TPC performance data to the industry. The TPC currently has 21 replete members: Actian, Cisco, Dell, DataCore Software, Fujitsu, Hewlett Packard Enterprise, Hitachi, Huawei, IBM, Inspur, Intel, Lenovo, Microsoft, Nutanix, Oracle, Pivotal, Red Hat, SAP, Teradata, TTA and VMware; and three associate members: China Academy of Information and Communications Technology (CAICT), Ideas International, and the University of Coimbra. Further information is available at http://www.tpc.org.



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