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4A0-105 Alcatel-Lucent Virtual Private LAN Services

Exam Name: Nokia Virtual Private LAN Services
Exam Number: 4A0-105
Credit Towards Certifications: Nokia Service Routing Architect
Exam Duration: 90 Minutes
Exam Appointment Duration: 135 minutes
Number of Questions: 60
Language: English

Alcatel-Lucent Virtual Private LAN Services
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Killexams : Alcatel-Lucent Alcatel-Lucent certification - BingNews https://killexams.com/pass4sure/exam-detail/4A0-105 Search results Killexams : Alcatel-Lucent Alcatel-Lucent certification - BingNews https://killexams.com/pass4sure/exam-detail/4A0-105 https://killexams.com/exam_list/Alcatel-Lucent Killexams : ISA Certification and Certificate Programs

ISA certification and certificate programs offer a standards-based learning approach to critical syllabus within the automation industry. Certificate programs increase professional recognition and validate specific knowledge areas such as safety and cybersecurity, while certification programs provide an objective, third-party assessment and confirmation of your skills and experience.

Benefits for Individuals

  • Documents education, knowledge, and experience
  • Provides an objective, third-party assessment of skill level
  • Provides a tangible way to validate industry experience
  • Increases preparation for additional job responsibilities

Benefits for Employers

  • Recognizes automation professionals with the appropriate credentials and helps accelerate workforce development
  • Provides hiring and promoting qualifications for managers
  • Promotes safety and efficiency
  • Improves productivity and increases ROI by impacting mission-critical decisions

Certification Programs

ISA offers the following certification programs. When you earn ISA certification, you will receive a digital badge and can be listed in the ISA credential directory.

Earning an ISA certification demonstrates your mastery of working with a standardized body of automation knowledge. By verifying your expertise with ISA—the global leader in automation education and training—you can showcase your automation proficiency to employers and stand out among your peers. These programs leverage the Automation Competency Model, which outlines the core skills needed to excel in today's automation environments.


Certificate Programs

ISA certificate programs are designed to increase knowledge and skills across a broad range of syllabus including cybersecurity, safety instrumented systems, automation project management, and many others. We offer certificate programs based on industry-developed job performance criteria and IEC adopted standards.

Learn more about our certificate programs and how they can add value to your career.

Support of the Control Systems Engineer (CSE) License Program

ISA supports the Control Systems Engineer (CSE) License, a specialized Professional Engineering (PE) license recognized in the United States for engineers working in automation and control. ISA offers training courses and review materials to help engineers prepare for state boards' exams held each October. Learn about the CSE Licensure Preparation Program.


Product Certification and Conformance

For over 75 years, ISA has been developing international standards for the industrial automation and control systems industry. Currently, ISA runs two conformity programs based on third-party conformity assessment and/or certification.

Together, these programs establish that a product meets expectations regarding safety, security, performance, and other essential criteria. For more information or questions about product certification and conformance programs, please contact Andre Ristaino.

Thu, 22 Sep 2022 10:31:00 -0500 en text/html https://www.isa.org/certification
Killexams : Scrum Master Certification: What Is It, And Why Pursue It?

Editorial Note: We earn a commission from partner links on Forbes Advisor. Commissions do not affect our editors' opinions or evaluations.

Scrum is an Agile methodology that allows your team to work in sprints as they complete small increments of work toward a final product. This involves consistently reviewing and adapting outcomes to make improvements each step of the way until completion.

Scrum is a framework that was initially known for creating software products in the IT industry. Now it is used in many industries, including financial services, product development, construction, advertising and marketing, consulting and government offices. Earning Scrum Master certification allows you to play a leadership role using Scrum methodology.

What Is Scrum Master Certification?

Earning the Certified ScrumMaster® (CSM) credential can help you expand your knowledge of Scrum principles and Agile methodologies. CSM certification is an official designation that demonstrates your skills as a Scrum Master. The Scrum Alliance confers the CSM credential, which is an entry-level certification. This certification focuses on the fundamentals of Scrum, iterative progress, accountability and team performance.

Becoming a CSM reflects your knowledge of Scrum as an Agile practice. It also shows that you are a reliable leader who can guide your team toward creating products and achieving your organization’s goals.

This credential signifies that you understand Scrum principles and practices, such as working with cross-functional teams in short cycles, encouraging timely feedback and implementing and evaluating improvements to the product your team is creating.

Other organizations offer certifications that are alternatives to CSM. For example, Scrum.org offers three levels of professional Scrum Master (PSM) certifications. Scrum Inc. provides training to become a registered Scrum Master (RSM).

Other organizations offer Scrum classes that result in an online certificate of completion. These courses cover the Scrum framework but do not lead to the official CSM designation.

Benefits of Scrum Master Certification

If you enjoy working in teams and are interested in the Scrum framework, you can benefit from earning your Scrum Master certification. This certification verifies your knowledge and skills in the Scrum framework. This helps you stand out among other job candidates, improves your risk assessment and collaboration skills and can open up new career opportunities for you.

Strengthen Your Risk Assessment Skills

By learning Scrum methodology, you’ll anticipate events and problems before they occur and identify risks and hazards before they become serious problems. You’ll also learn to prevent or eliminate any bottlenecks that might otherwise cause projects to stall, which will save time and money.

Help Your Resume Stand Out

When you list your Scrum Master certification on your resume, you’re letting potential employers know that you’ve taken the steps necessary to stay updated on industry standards, current trends and technologies in product development. You’re also showing that you understand how to use Scrum principles and techniques to guide your team to reach positive outcomes.

As a CSM, you are prepared to guide your team through creating a product from beginning to end by evaluating the team’s work and adapting it as needed to reach the end goal.

Increase Your Team’s Effectiveness

Earning your Scrum Master certification gives you the skills to work with your team more effectively and efficiently. You’ll know how to motivate your team to stay organized and on task as they work toward each goal. You’ll lead collaboration among teammates, identify problems early on and find ways to solve them. Your entire team should work together better using Scrum principles.

Prepare Yourself for More Career Opportunities

As a CSM, you can move forward in your career and earn additional certifications. Other relevant credentials include Advanced Certified ScrumMaster and Certified Scrum Professional – ScrumMaster®.

Earning an additional certification can increase your earning potential and help you Improve engagement, encourage accountability within teams and scale Scrum and Agile with multiple teams.

What to Consider Before Earning Scrum Master Certification

If you’re trying to determine if earning your CSM fits with your career path, here are a few things you should consider.

Can You Meet the Required Time Commitment?

The Scrum Alliance requires candidates to study Scrum principles through a CSM course, which typically involves 16 hours of training over two days. Before you take the course, consider studying any prerequisite materials to prepare. The Scrum Alliance provides many free articles and resources on its website.

Many training organizations offer Scrum Master classes. Make sure to find one that fits your schedule and availability. When you finish your training, you can schedule your exam. This exam is administered by the Scrum Alliance and has a 60-minute time limit. To pass the exam, you must answer at least 37 out of 50 questions correctly.

While your course time and exam time amount to about three days, it can take a few weeks to earn certification. Time to certification depends on factors like how long you plan to study, how soon you can find a course and sign up for it and whether you pass your exam on the first attempt.

Does Your Company or Future Career Value or Require It?

If you plan to work for a company that uses Scrum principles, consider earning your CSM certification. This certification may supply you an advantage over other job applicants, and it shows that you have a thorough understanding of Scrum principles and methodologies.

With this certification, you’ll be able to guide teams through projects efficiently and effectively. This is a valuable skill set for staff members at many businesses.

Do You Enjoy Working in Teams?

Scrum principles encourage collaboration and ongoing feedback among team members. As a certified Scrum Master, you can guide your team members and inspire them to share their ideas and skills as they complete projects. Working in this way requires trust among team members, allowing all to feel valued as they play essential roles in completing the work.

If you enjoy working as part of a team, earning CSM designation may benefit your career.

Frequently Asked Questions About Scrum Master Certification

How long does it take to become a certified Scrum Master?

The CSM course and exam typically require three days, but it can take a few weeks to become a certified Scrum Master. Time to certification depends on how long you spend studying, how soon you can schedule your course and the subsequent exam and whether or not you pass your exam on the first attempt.

How do you get certified as a Scrum Master?

To earn your Scrum Master certification, you must complete a Scrum certification course. This two-day course covers all of the Scrum framework elements you need to know. After completing the course, you’ll take and pass the CSM exam.

How do I renew my CSM certification?

To maintain your CSM certification, you need to renew it every two years. The renewal fee is $100. You also need to earn 20 hours of Scrum education units (SEUs) every two years to renew your certification.

Which is better: CSM or PMP?

This depends on your career goals since both credentials serve different purposes. PMP is the gold standard in project management certifications, and it requires years of experience and several thousand hours of training and education. CSM focuses on the Scrum framework and requires no experience and a single two-day course.

Mon, 07 Nov 2022 16:36:00 -0600 Sheryl Grey en-US text/html https://www.forbes.com/advisor/education/scrum-master-certification/
Killexams : Alcatel-Lucent Enterprise and CORTEX2 collaborate to make video conferencing an Extended Reality experience No result found, try new keyword!Alcatel-Lucent Enterprise RainbowTM will support the ... business meetings and remote training. Industrial production: Creating an immersive XR experience to carry out remote industrial ... Wed, 30 Nov 2022 13:00:00 -0600 text/html https://www.nasdaq.com/press-release/alcatel-lucent-enterprise-and-cortex2-collaborate-to-make-video-conferencing-an Killexams : Alcatel-Lucent Enterprise Achieves FERPA Compliance Ensuring Data Protection in the Education Sector

Calabasas, California --News Direct-- Alcatel-Lucent Enterprise

Alcatel-Lucent Enterprise, a leading provider of communications, networking, and cloud solutions tailored to customers’ industries, today announces that it has achieved compliance under the Family Educational Rights and Privacy Act (FERPA) for the US market.

FERPA is a Federal law that requires schools and their service providers to protect the privacy of students’ education records. This entails the establishment and maintenance of administrative, physical, and technical safeguards that are designed to ensure the confidentiality, integrity, and availability of all education records to which a school or service provider has access.

FERPA compliance will enable Alcatel-Lucent Enterprise to provide its RainbowTM communications solutions, including Rainbow Classroom, to its education customers.

“ALE has been proactive in taking on the critical role of protecting students’ education records and providing educational agencies or institutions with the technology they need to ensure student success. We take great pride in offering peace of mind to education professionals, parents, and students alike,” said Salvatore Zoida, Senior Attorney and FERPA Compliance Officer at ALE USA Inc.

“Achieving this milestone allows us to extend the benefits of our Rainbow communications platform, through its licensing model, to educational institutions at all levels, which is a priority vertical for ALE. We are committed to our education customers and will continue to propose the solutions they need while ensuring all the necessary protection for them to offer services in optimal conditions,” said Mike Mullarkey, Senior Vice President, Sales and Marketing, Americas at ALE USA Inc.

ALE is a key supplier of unified communications solutions tailored to organisations of all sizes across various industries. The company also provides cloud-based solutions enhancing its customers’ ability to address client needs as they increasingly move to the cloud. Rainbow Classroom by Alcatel-Lucent Enterprise delivers a standardized virtual learning experience that leverages existing Learning Management Systems or ALE’s standalone online learning platform and enriches it with real-time collaboration and communication capabilities. The solution provides everything educators need in an online virtual classroom, tailored to their requirements, using a web browser and internet connection.

About Alcatel-Lucent Enterprise

Alcatel-Lucent Enterprise delivers the customised technology experiences enterprises need to make everything connect.

ALE provides digital-age networking, communications, and cloud solutions with services tailored to ensure customers’ success, with flexible business models in the cloud, on premises, and hybrid. All solutions have built-in security and limited environmental impact.

Over 100 years of innovation have made Alcatel-Lucent Enterprise a trusted advisor to more than a million customers all over the world.

With headquarters in France and 3,400 business partners worldwide, Alcatel-Lucent Enterprise achieves an effective global reach with local focus.

al-enterprise.com | LinkedIn | Twitter | Facebook | Instagram

Contact Details

Global Press

Carine Bowen

press@al-enterprise.com

Company Website

https://www.al-enterprise.com/

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Mon, 21 Nov 2022 01:09:00 -0600 en-US text/html https://www.yahoo.com/lifestyle/alcatel-lucent-enterprise-achieves-ferpa-150000088.html
Killexams : Six Sigma Certification: Definition and How To Complete It

What Is Six Sigma Certification?

Six Sigma certification is a verification of an individual's command of a well-regarded quality assurance method. Certifications for Six Sigma training are awarded in levels using a belt classification system similar to belt levels used in martial arts.

Six Sigma is a set of quality management techniques and tools developed in the 1980s and adopted by American corporations, including General Electric. Development of the Six Sigma system is credited to Bill Smith and Mikel Harry, two Motorola engineers, and the name was trademarked by Motorola in 1993.

There is no standard Six Sigma curriculum. Programs are offered by many colleges, online and on-campus, and are offered in-house by many corporations.

Key Takeaways

  • Six Sigma is a set of quality management techniques and tools that have been widely adopted by American corporations.
  • Six Sigma originated as a method of minimizing errors or defects in manufacturing processes.
  • It has since had a pervasive influence on management practices in the U.S. and abroad.

Understanding Six Sigma Certification

The name Six Sigma stems from a statistical measurement represented by the lowercase Greek symbol sigma (σ). On a bell curve measuring data and standard deviation, sigma represents one standard deviation from the mean of a set of data. So, six sigma refers to the data that falls with six standard deviations on either side of the mean of the dataset.

On the curve, any data points outside of six sigma represent products outside acceptable norms—these are generally called defects. The Six Sigma bell curve represent one million data points. Therefore, if your product falls within six sigma—or six standard deviations from the mean on either side—there is a likelihood that you only have 3.4 defects per million items produced.

In a manufacturing process, this is the ultimate level to strive for, ensuring error-free delivery of a product 99.99966% of the time. Six Sigma training, therefore, focuses on developing management processes that reliably lead to virtually defect-free results in manufacturing or in any business activity.

The Six Sigma Belt Levels

Six Sigma certifications are awarded belt levels relevant to the position in the employee's business within an organization. They are earned through practical experience, course-based training, and exams. The belt levels are:

  • White belt: Awarded for completing an entry-level overview of the tools used in Six Sigma, its history, and the system's structure.
  • Yellow belt: Awarded for assisting a project at a practical level and passing an exam demonstrating an understanding of implementing, performing, and applying Six Sigma.
  • Green belt: Awarded for learning the principles of Six Sigma and implementing them under the guidance of a black belt in real projects. Must pass an exam demonstrating thorough knowledge of the phases of the Six Sigma Method.
  • Black belt: Plans and executes projects using Six Sigma principles. Must pass an exam demonstrating a complete knowledge of the phases of the Six Sigma Method.
  • Master black belt: Manages the implementation of Six Sigma projects across functions. Demonstrates through an exam an expert understanding of the philosophies and principles of Six Sigma.
  • Champion: An upper-level executive who is responsible for the implementation of Six Sigma across all departments.

Benefits of Six Sigma

For Employers

Six Sigma helps employers in many ways. In addition to improving employee and process performance, businesses benefit from:

  • Reduced waste
  • Increased efficiency
  • Increased revenue
  • Reduced errors and defects
  • Increased customer satisfaction and loyalty
  • Increased brand recognition

For Employees

Employees benefit from Six Sigma training and application as much as businesses do. Many experience:

  • Increased pay
  • An increase in opportunities
  • Higher job security
  • Leadership opportunities

Lean Six Sigma

Lean Six Sigma is derived from a combination of Lean and Six Sigma principles. Lean focuses on removing waste of physical and personnel resources by identifying the causes of defects, overproduction, waiting, non-utilized talent, transportation waste, inventory waste, waste of motion, and extra processing.

Lean Six Sigma uses Six Sigma techniques to identify and eliminate wasted resource use that doesn't generate value for the end user while continually working to achieve a goal of 3.4 defects per million products.

No Official Standards for Six Sigma

No unifying standard or organization sets a standard for Six Sigma belt certification. Instead, each company, school, or certifying organization determines its own criteria.

In some organizations, certification may require completing an exam or a series of exams. In others, an individual must complete several Six Sigma-based projects. In addition, certification services charge a fee.

How Much Does Six Sigma Cost?

Because Six Sigma training is not standardized, costs will vary based on who is conducting the training. For example, a company training employees in Six Sigma will likely not charge the employees but will incur the costs of employing people who can teach the subject, developing the curriculum, and losing the employee's time at their regular job.

You can take certification tests through various sources, such as Purdue University, The Council for Six Sigma Certification, or Project Management Academy. Project Management Academy charges $495 for its Beginner Yellow Belt certification, $2,295 for its Green Belt Training, and $3,595 for its Black Belt Training.

The Council for Six Sigma Certification offers free white belt certification and charges $99 for a yellow belt, $159 for a green belt, and $229 for a black belt (for primary certifications—level II certifications are more expensive).

What Is a Six Sigma Certification?

Six Sigma certification signifies you have received a specific level of training and understand the concepts involved in a particular quality improvement method.

How Long Does It Take to Get Six Sigma Certification?

The time it takes to get a Six Sigma certification depends on many factors. If you're receiving the training through your employer, it may take one week or more. On the other hand, studying in your free time can take as long as you need to study and pass the exam.

What Does Six Sigma Certification Cost?

Six Sigma certification costs vary by level from $99 to $3,595. The costs also depend on how much instruction you receive or whether you're only paying for the exam.

The Bottom Line

Six Sigma is a quality control certification that attempts to educate people on analyzing processes and outcomes to reduce waste and decrease defects. There are several levels of certifications, from a primary end user to a master Six Sigma user who acts as a senior quality control member.

Six Sigma benefits both employees and employers because using it can reduce waste and defects, thereby increasing a business's value to consumers and end-users. This can lead to high levels of customer satisfaction, more revenue, higher compensation, and better products.

Mon, 28 Nov 2022 10:00:00 -0600 en text/html https://www.investopedia.com/terms/s/six-sigma-certification.asp
Killexams : Alcatel-Lucent No result found, try new keyword!For Sara Rossmann, good leadership is about recognizing that we’re all human, we all make mistakes, and we all have our bad days as well Kinaxis (TSX:KXS) has a new executive in charge of its supply ... Tue, 22 Nov 2022 18:46:00 -0600 en-US text/html https://obj.ca/company/alcatel-lucent/ Killexams : Alcatel Lucent Teletas Telekomunikasyon AS (ALCTL)

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Fri, 02 Dec 2022 01:09:00 -0600 en text/html https://www.investing.com/equities/alcatel-lucent-teletas
Killexams : NVIDIA H100 GPU Performance Shatters Machine Learning Benchmarks For Model Training

NVIDIA’s Hopper H100 Tensor Core GPU made its first benchmarking appearance earlier this year in MLPerf Inference 2.1. No one was surprised that the H100 and its predecessor, the A100, dominated every inference workload. The H100 set world records in all of them and NVIDIA is the only company to have submitted to every workload for every MLPerf round.

A few weeks ago, a new set of MLCommons training results were released, this time for MLPerf 2.1 Training, which the NVIDIA H100 and A100 also dominated.

Unfortunately, NVIDIA’s dominance of MLPerf benchmarking suites for inference and training has deflected submissions and reports by many important AI companies.

The industry would benefit from the participation of more organizations as we have seen in other sectors like CPUs, it drives competition and innovation. Broad involvement in benchmarking suites is significant because machine learning is growing exponentially. Almost every industry segment uses machine learning for a wide range of applications. As usage increases, so does model size. Since 2018, MLCommons has held testing rounds that alternate between MLPerf Training and MLPerf Inference testing rounds.

In the four years between the first MLPerf test in 2018 and this year’s results, machine learning model size has increased by five orders of magnitude. With the increased model size and larger data sets, standardized tools like MLPerf Training and MLPerf Inference are more crucial than ever. Machine learning model performance must be measured before it can be improved.

MLPerf 2.1 Training benchmarks

MLPerf Training and MLPerf Inference use the same eight workloads shown in the above graphic. Mini Go is an exception because it is only used to evaluate reinforcement learning. Each benchmark test is defined by its own specific dataset and quality target. The Key is how much time it takes to train the model using the specified dataset with the specified quality target.

MLPerf is vital to AI and machine learning because it is an industry-standard benchmark with peer review results that provides valid comparisons for model training and inference. It is supported by Amazon, Arm, Baidu, Google, Harvard University, Intel, Meta, Microsoft, Stanford University, and the University of Toronto.

Multiple single models form high performance, multiple models

It is common for multiple AI models to be chained together to satisfy a single input. An example of multimodal networks is the verbal request in the above graphic. The question requires ten machine learning models to produce an answer. Not only must multiple models operate sequentially, but it must also deliver real-time solutions.

Some cloud services also use multiple networks to deliver services accelerated by NVIDIA GPUs. All of NVIDIA's networks and application frameworks are available on its MLPerf repo, on NGC (NVIDIA’s online container repository), and its GitHub repo.

A100 and H100 benchmark training performance

As shown in the MLPerf Training 2.1 performance chart, H100 provided up to 6.7 x more performance for the BERT benchmark compared to how the A100 performed on its first MLPerf submission in 2019.

A100 is still producing record results and high performance with improved performance of up to 2.5X. This gain is the result of software optimization. It will likely be an NVIDIA offering for quite some time.

H100 superior performance on the BERT NLP model is attributed to its Transformer Engine. The A100 does not have a training engine. The new engine, combined with NVIDIA Hopper FP8 Tensor Cores, delivers up to 9x faster AI training and 30x faster AI inference speedups on large language models than the A100. The H100 is based on Hopper architecture and uses fourth-gen tensor cores.

Training speed is crucial and necessary because of AI model size. NVIDIA’s transformer engine achieves additional speed using 16-bit floating-point precision and a new 8-bit floating-point data format. This combination increases Tensor Core throughput by 2x and reduces memory requirements by 2x compared to 16-bit floating-point.

Those improvements, plus advanced Hopper software algorithms, speed up AI performance and capabilities allowing the H100 to train models within days or hours instead of months. The faster a model can move into operation, the earlier its ROI can begin contributing to the bottom line.

The Hopper architecture can dynamically determine if FP8 or 16-bit calculations are needed for accuracy. As the transformer engine trains layer by layer, it analyzes the data to determine if reduced precision should be used. Depending on the degree of usage, reduced precision can cause rounding errors which affect model accuracy.

MLPerf training tests measure the time to solution, so a model not only has to run fast, but it also has to converge. Therefore, it is essential to remember that many errors can prevent a model from converging.

NVIDIA’s transformer engine technology was designed for large transformer-based networks like BERT. However, it is not restricted to NLP. It can be applied to other areas, such as stable diffusion.

Stable Diffusion is a deep learning, compute-intensive text-to-image model released this year. It can generate detailed images or videos conditioned on text descriptions. It can also be applied to tasks such as inpainting, outpainting, and generating image-to-image translations using a text prompt.

Time to train at scale

NVIDIA A100 was the only platform to run all workloads in the time to train at scale. NVIDIA was able to train every workload at scale in under 5 minutes except for Mini Go, which took about 17 minutes.

Mini Go uses reinforcement learning which is very compute-intensive. It takes longer to train the network because it requires playing Mini Go turn-by-turn, then rolling it back through the network after each turn.

Training at scale demonstrates that A100 remains a solid platform for training. H100 is a solution for the most advanced models, such as language models with massive datasets and billions of hyperparameters.

While Intel and Habana didn't turn in record-setting performances, its participation was nevertheless important for the ecosystem and the future of MLPerf.

This graphic shows relative per accelerator speedup normalized to A100. The H100 (in preview) was submitted for every benchmark and scored superior performance for each. It was 2.6X faster than the A100, which has made significant software gains.

Habana Gaudi2 submitted for Resnet-50 and BERT, and Intel's Sapphire Rapids submitted for DLRM, ResNet-50, and BERT.

Habana Gaudi2 performed marginally better than A100 on BERT and about 0.75 better than A100 for ResNet-50. Intel acquired Habana in late 2019 for $2 billion. Gaudi2 is Habana’s second-generation deep learning processor. It has 24 tensor cores and 96 GB of memory.

Dave Salvator, Director of AI, Benchmarking and Cloud for NVIDIA, is expecting higher performance from the H100 in the future.

“The H100 turned in a very compelling performance,” he said. “But in the future, we will make software gains with the H100 as we did with the A100. This is the first round we’re submitting H100 for training, and it won’t be the last.”

HPC MLPerf 2.0 Supercomputing benchmarking

MLPerf HPC 2.0 measures the time to train supercomputer models for scientific applications. Additionally, there is an optional throughput measurement for multi-user supercomputing systems. This round was the third iteration of MLPerf HPC. Like MLPerf for training and inference, MLPerf HPC is considered an industry-standard system performance measure for workloads performed on supercomputers.

For this round, five of the world's largest supercomputers submitted 20 results: Dell (first time for submission), Fujitsu/RIKEN, Helmholz AI, NVIDIA, and Texas Advanced Computing Center (TACC).

This is version 2.0 of the benchmarks, however, there have been no major changes since these same three workloads were run in 1.0. MLPerf HPC benchmarks measure training time and throughput for three high-performance simulations that have adopted machine learning techniques – Cosmoflow, DeepCAM, and OpenCatalyst.

Because of climate change, a great deal of concentrated work is being done on weather and climate modeling. NVIDIA is also working on a digital twin of the planet called Earth Two. This giant climate model simulates the entire world.

NVIDIA HPC Platform Performance Leadership

MLPerf HPC 2.0 has two performance metrics:

  • Strong Scaling measures time and quality for training the dataset. NVIDIA Selene had the lowest training time of all submissions for all three benchmarks.
  • Weak Scaling measures throughput and quality for simultaneously training multiple models on the dataset. Again, NVIDIA trained more models per minute than any submission.
  • For CosmoFlow, NVIDIA has made a 9X improvement in time to train over two years.

Although the NVIDIA A100 Tensor Core GPU and the NVIDIA DGX-A100 SuperPOD are almost three years old, MLPerf 2.0 performance shows that A100 is still the highest performing system for training HPC use cases.

HPC results are for NVIDIA Selene, an implementation of the DGX SuperPOD and demonstrate the A100’s potential. Other supercomputing sites using NVIDIA technology are also delivering good performance.

Wrapping up

It is important to mention that NVIDIA was the only organization to run all AI training workloads for this and all previous MLPerf Training and inference rounds. It has delivered consistent leadership results from the first MLPerf Training 0.5 in December 2018 to the latest MLPerf Training 2.1 that was released a few weeks ago.

For training, inference, and HPC, MLPerf has proven NVIDIA has the broadest ecosystem support for all the deep learning frameworks. It is advantageous for customers that NVIDIA GPUs are available from all major cloud providers and all major systems for on-prem solutions. Those application frameworks allow customers to deploy solutions rapidly.

NVIDIA has an end-to-end open platform with software that helps expand the full potential of its hardware. NVIDIA’s full-stack solution includes application frameworks such as Merlin and Nemo. With Nemo Megatron service, it is possible to leverage huge language models using custom datasets.

ANALYST NOTES

  1. There are many reasons why model speed is so vital for inference and training. One overlooked reason relates to the necessity of multiple training runs. Building a model is an experimental process that involves trial and error to get the model properly tuned. The model must be rerun each time something is tweaked to see the results. The ability to run the model faster means more trials can be run in a given time. That allows a solution to be found and deployed more quickly. The faster a model can be deployed, the earlier its benefits can contribute to improved operations and its ROI can be generated.
  2. MLPerf provides peer-reviewed apples-to-apples comparisons for training and inference. It eliminates the need to rely on a company’s cherry-picked stats from its performance testing that may or may not be valid.
  3. NVIDIA works with many of the top AI researchers. I spend much time reviewing research papers on AI and quantum. A lot of AI research work uses NVIDIA platforms. So far this year, over 400 preprint research papers have been published on deep learning using NVIDIA technology. It will be interesting to see future research results using the H100 as its availability increases.
  4. Power consumption is a significant issue in the AI ecosystem. Although measurement of power consumption isn’t currently part of MLPerf Training, it is under consideration. However, power is a measurement in MLPerf Inference. For MLPerf Inference 2.1 in September, 2,400 power measurement results were submitted. For reference, A100 requires 400 watts, and H100 requires 700 watts. When juggling these two figures, consideration needs to be given to performance and speed. BERT is an excellent example because the H100 enjoys a 6X advantage in speed.
  5. Like the A100, the H100 can be partitioned into seven smaller accelerators that can independently run different networks. That is a way to get optimal utilization out of the part on the inference side and reduce the number of total GPUs needed to deploy multiple networks. Ideally, the feature is more useful for training advanced models, but it also has applications on the inference side.

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Moor Insights & Strategy founder, CEO, and Chief Analyst Patrick Moorhead is an investor in dMY Technology Group Inc. VI, Dreamium Labs, Groq, Luminar Technologies, MemryX, and Movand

Note: Moor Insights & Strategy writers and editors may have contributed to this article.

Mon, 21 Nov 2022 01:39:00 -0600 Paul Smith-Goodson en text/html https://www.forbes.com/sites/moorinsights/2022/11/21/nvidia-h100-gpu-performance-shatters-machine-learning-benchmarks-for-model-training/
Killexams : Alcatel-Lucent Enterprise and CORTEX2 collaborate to make video conferencing an Extended Reality experience

Paris, FRANCE --News Direct-- Alcatel-Lucent Enterprise

Alcatel-Lucent Enterprise RainbowTM will support the Horizon Europe research and innovation programme in developing extended reality-based tools for effective business telecommunication

Alcatel-Lucent Enterprise, a leading provider of network, communications and cloud solutions, is taking part in the CORTEX2 (COoperative Real-Time EXperiences with EXtended reality) consortium.

With AI (Artificial Intelligence) and ML (Machine Learning) at the heart of its technology development, ALE will support CORTEX2 on its mission to democratise access to remote collaboration offered by next-generation XR (Extended Reality) experiences across a wide range of industries and SMEs.

CORTEX2 is an eight-million-euro initiative funded by the European Commission through the Horizon Europe research and innovation programme. The consortium is composed of 10 organisations across seven countries that will work together for 36 months.

The CORTEX2 platform will be operated from the ALE cloud, and RainbowTM by Alcatel-Lucent Enterprise will be used as a backbone for the innovative extended reality-based tele-cooperation concept to ensure large scale adoption and rapid scaling.

The global health crisis accelerated remote working and led to a sharp increase in the use of videoconferencing and platforms enabling teamwork. Today, XR-based tools, which can enhance remote collaboration communications, present significant challenges for most businesses.

Through the partnership of all ten organisations CORTEX2 aims to simplify XR technology adoption and will provide:

  • Full support for Augmented Reality (AR) experiences as an extension of video conferencing systems when using heterogeneous service end devices through a novel Mediation Gateway platform.

  • Resource-efficient teleconferencing tools through innovative transmission methods and automatic summarisation of shared long documents.

  • Easy-to-use and powerful XR experiences with instant 3D reconstruction of environments and objects, and using recognised gestures to trigger corresponding actions in collaborative meetings.

  • Fusion of visual and audio elements for multichannel semantic interpretation and enhanced tools such as virtual conversational agents and automatic meeting summarisation.

  • Full integration of internet of things (IoT) devices into XR experiences to optimise interaction with running systems and processes.

Half of the total budget of the project will be dedicated to recruiting tech startups and SMEs to support with co-development. This investment aims to engage new use-cases to demonstrate CORTEX2 capabilities and assess the social impact associated with the adoption of XR technology in both external and internal use cases.

As a part of its mission, the consortium will enable third parties, including small and medium enterprises, to use the CORTEX2 generic framework to develop their own services. The Rainbow cloud-based Communication Platform as a Service (CPaaS) will be a key component of the project that supports fully interactive XR-based cooperation and will be showcased in three planned pilots: industrial production, business meetings and remote training.

  • Industrial production: Creating an immersive XR experience to carry out remote industrial maintenance using various mobile devices in limited bandwidth environments.

  • Business meetings: Offering Virtual Reality/Augmented Reality enriched business meetings for seamless inclusion of remote participants and improved productivity.

  • Remote technical training: Using VR/AR for efficient knowledge transmission where the remote instructor can demonstrate complex operations to multiple trainees using an immersive 3D model of industrial equipment.

"We are delighted to take part in this amazing project that will put Extended Reality at European users’ fingertips. With CORTEX2, we will bring XR capabilities into Rainbow’s collaborative space through the use of VR, AR and AI. It's an exciting time to be at cutting edge of these technologies," said Sylvain Rivier, CORTEX2 coordinator for Alcatel-Lucent Enterprise.

The ultimate goal for this partnership is to extend video conferencing to more than just screen-to-screen interactions, enabling the integration of XR-based tools into business communications for seamless remote communication collaboration.

This project has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement N° 101070192.

About Alcatel-Lucent Enterprise

Alcatel-Lucent Enterprise delivers the customised technology experiences enterprises need to make everything connect.

ALE provides digital-age networking, communications and cloud solutions with services tailored to ensure customers’ success, with flexible business models in the cloud, on premises, and hybrid. All solutions have built-in security and limited environmental impact.

Over 100 years of innovation have made Alcatel-Lucent Enterprise a trusted advisor to more than a million customers all over the world.

With headquarters in France and 3,400 business partners worldwide, Alcatel-Lucent Enterprise achieves an effective global reach with a local focus.

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Contact Details

Alcatel-Lucent Enterprise

Katherine Skidmore

+44 20 3750 6688

katherine@fox.agency

Company Website

https://www.al-enterprise.com/

View source version on newsdirect.com: https://newsdirect.com/news/alcatel-lucent-enterprise-and-cortex2-collaborate-to-make-video-conferencing-an-extended-reality-experience-650847285

Thu, 01 Dec 2022 01:44:00 -0600 en-US text/html https://finance.yahoo.com/news/alcatel-lucent-enterprise-cortex2-collaborate-080000855.html
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