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Protect Customer Data Centers with AMD Infinity Guard

AMD’s 4th Gen EPYC server processors can keep your customers safe with Infinity Guard, a set of innovative and powerful security features.

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When AMD released its 4th generation EPYC server processors, the company also doubled down on its commitment to enterprise data-center security. AMD did so with a set of security features it calls AMD Infinity Guard.

The latest EPYC processors—previously code-named Genoa—include an array of silicon-level security assets designed to resist increasingly sophisticated cyberattacks.

CIOs and IT managers who deploy AMD’s latest security tech may sigh with relief as they sidestep mounting threats such as ransomware, malicious virtual machines (VMs) and hypervisor-based attacks like data replay and memory re-mapping.

Growing concerns

Hackers are relentless. Beguiled by the siren song of easy riches through cybercrime, they spend countless hours devising new ways to exploit even the slightest hardware vulnerability. The bigger the organization, the more money these cyber criminals can extort—which is why they often target enterprise data centers.

AMD took this into account when designing the EPYC server processor series. The company had three goals: to address hardware-level vulnerabilities, eliminate likely threat vectors, and deny hackers access to any surface they could exploit.

Perhaps just as vital, AMD set a goal of addressing security concerns without impacting system performance. This is especially important for modern application workloads that require both high performance and low latency.

For instance, organizations that offer streaming content and mass storage could be just as easily crushed by glitches and malfunctions as they could by a significant security breach.

Security tech within

AMD is taking a decidedly ain’t-messin’-around approach to its latest security tech. Rather than paying lip service to IT Ops’ concerns, AMD engineers went deep down into the heart of their processor architecture to identify and remedy threat vectors.

The impressive security portfolio includes 4 primary tools to guard against threats:

  • Secure Encrypted Virtualization: SEV provides individual encryption for every virtual machine on a given server. Each VM is assigned one of up to 509 unique encryption keys known only to the processor. This protects data confidentiality in the event that a malicious VM breaches a system’s memory, or a compromised hypervisor reaches into a guest VM.
  • Secure Memory Encryption: Full memory encryption protects against internal and physical attacks such as the dreaded cold boot attack. There, an attacker with physical access to a computer conducts a memory dump by performing a hard reset of the target machine. SME ensures that the data remains encrypted even if the main memory is physically removed from a server.
  • Secure Boot: To help mitigate the threat of malware, AMD EPYC processors employ an embedded security checkpoint called a “root of trust.” This validates the initial BIOS software boot without corruption.
  • Shadow Stack: It may sound like a Marvel superhero, but in fact this guards against threat vectors such as return-oriented programming (ROP) attacks. Shadow Stack does this by compiling a record of return addresses so a comparison can be made to help ensure software-code integrity.

A well-rounded engine

A modern server processor serves many masters. While addressing security concerns is vitally important, so are ensuring high performance, impressive energy efficiency and a decent return on investment (ROI).

Your customers may appreciate knowing that AMD’s latest EPYC processor series addresses these factors. Rather than focusing solely on headline-grabbing tech like speeds & feeds, AMD took a more holistic approach, addressing many issues endemic to modern data-center operations.

EPYC CPUs also boast broad ecosystem support. For AMD, this means fostering collaboration with a network of solution providers. And for your customers, this means worry-free migration and seamless integration with their existing x86 infrastructures.

Your data-center customers are probably concerned about security. Who isn’t, these days? So talk to them about AMD Infinity Guard. After all, a secure customer is a happy customer.

 

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For Greener Data Centers, Look to Energy-Efficient Components

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For Greener Data Centers, Look to Energy-Efficient Components

Energy-efficient systems can help your customers lower their data-center costs while supporting a cleaner environment. 

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Creating a more energy-efficient data center isn’t only good for the environment, but also a great way for your customers to lower their total cost of ownership (TCO).

In many organizations, the IT department is the single biggest consumer of power. Data centers are filled with power-hungry components, including servers, storage devices, air conditioning and cooling systems.

The average data center uses anywhere from 2 to 4 Terawatt hours (TWh) of electricity per year. That works out to nearly 3% of total global energy use, according to Supermicro. Looking ahead, that’s forecast to reach as high as 8% by 2030.

One important measure of data-center efficiency is Power Usage Effectiveness (PUE). It’s calculated by taking the total electricity in a data center and dividing it by the electricity used by center’s IT components. The difference is how much electricity is being used for cooling, lighting and other non-IT components.

The lower a data center’s PUE, the better. The most energy-efficient data centers have a PUE of 1.0 or lower. The average PUE worldwide last year was 1.55, says the Uptime Institute, a benchmarking organization. That marked a slight improvement over 2021, when the average PUE was 1.57.

Costly power

All that power is expensive, too. Among the short list of ways your customers can lower that cost, moving to energy-efficient server CPUs is especially effective.

For example, AMD says that 11 servers based on of its 4th gen AMD EPYC processors can use up to 29% less power a year than the 17 servers based on competitive CPUs required to handle the same workload volume. And that can help reduce an organization’s capital expenditures by up to 46%, according to AMD.

As that example shows, CPUs with more cores can also reduce power needs by handling the same workloads with fewer physical servers.

Yes, a high-core CPU typically consumes more power than one with fewer cores, especially when run at the same frequency. But by handling more workload volume, a high-core CPU lets your customer do the same or more work with fewer racks. That can also reduce the real estate footprint and lower the need for cooling.

Greener tactics

Other tactics can contribute to a greener data center, too.

One approach involves what Supermicro calls a “disaggregated” server architecture. Essentially, this means that a server’s subsystems—including its CPU, memory and storage—can be upgraded without having to replace the entire chassis. For a double benefit, this lowers TCO while reducing E-waste.

Another approach involves designing servers that can share certain resources, such as power supplies and fans. This can lower power needs by up to 10%, Supermicro says.

Yet another approach is designing servers for maximum airflow, another Supermicro feature. This allows the CPU to operate at higher temperatures, reducing the need for air cooling.

It can also lower the load on a server’s fans. That’s a big deal, because a server’s fans can consume up to 15% of its total power.

Supermicro is also designing systems for liquid cooling. This allows a server’s fan to run at a lower speed, reducing its power needs. Liquid cooling can also lower the need for air conditioning, which in turn lowers PUE.

Liquid cooling functions similarly to a car’s radiator system. It’s basically a circular system involving an external “chiller” that cools the liquid and a series of pipes. The liquid is pumped to run through one or more pipes over a server’s CPU and GPU. The heat from those components warms the liquid. Then the now-hot liquid is sent back to the chiller for cooling and then recirculation.

Green vendors

Leading suppliers can help you help your customers go green.

AMD, for one, has pledged itself to delivering a 30x increase in energy efficiency for its processors and accelerators by 2025. That should translate into a 97% reduction in energy use per computation.

Similarly, Supermicro is working hard to help customers create green data centers. The company participates in industry consortia focused on new cooling alternatives and is a leader in the Liquid Cooling Standing Working Group of The Green Grid, a membership organization that fosters energy-efficient data centers.

Supermicro also offers products using its disaggregated rack-scale design approach to offer higher efficiency and lower costs.

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What are Your Server Customers Looking For? It Depends on Who They Are

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What are Your Server Customers Looking For? It Depends on Who They Are

While hyperscalers and enterprises both buy servers powered by the latest CPUs, their purchase decisions are based on very different criteria. Knowing who you’re selling to, and what they’re looking for, can make all the difference.

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Think all buyers of servers powered by the latest-generation CPUs are all looking for the same thing? Think again.
 
It pays to think of these customers as falling into one of two major groups. On the one hand are the so-called hyperscalers, those large providers of public cloud services. On the other are CIOs and other IT executives at large enterprises who are looking to improve their on-premises data centers. 
 
Customers in both groups are serious buyers of the latest, greatest servers. But their buying criteria? Two very different things.
 
Hyperscalers: TCO, x86, VM
 
When it comes to cutting-edge servers, hyperscalers including Amazon Web Services (AWS), Microsoft Azure and Google Cloud are attracted to the cost advantage.
 
As Mark Papermaster, chief technology officer at AMD, explained in a recent technology conference sponsored by Morgan Stanley, “For the hyperscalers, new server processors are an easy transition. Because they’re massive buyers, hyperscalers see the TCO [total cost of ownership] advantage.”
 
Hyperscalers also like the fact that most if not all new server CPUs still adhere to the x86 family of instruction-set architectures. “For their workloads,” Papermaster said, “it lifts and shifts.”
 
Big hyperscalers are also big implementers of containers and virtual machines. That’s an efficient workload application for today’s high-density CPUs. The higher the CPU density, the more VMs can be supported on a single server. 
 
For example, AMD’s 4th gen EPYC processors (formerly code-named Genoa) pack in 96 cores, or 50% more than the previous generation. That kind of density suits hyperscalers well, because they have such extensive inventories of VMs.
 
Enterprise CIOs: different priorities
 
For CIOs and other enterprise IT executives, server priorities and buying criteria are quite different. These buyers are looking mainly for ease of migration, broad ecosystem support, robust security and energy efficiency (which can also be a component of TCO). 
 
CIOs also need to keep their CFOs and boards happy, so they’re also looking for a clear and easily explainable return on investment (ROI). They may also need to tie this calculation to their organization’s strategic goals. For example, if a company were looking to increase its market share, the CIO might want to explain how purchasing new servers could help achieve that goal. 
 
One relatively new and increasingly important priority is energy efficiency. Enterprises increasingly need to demonstrate their support for “green” initiatives. One way a company can do that is by showing how their computer technology gets more done with less electric power.
 
Also, many data centers are already receiving as much electric power as they’re configured for. In other words, they can’t add power to get more work done. But they can add energy-efficient servers able to get more work done with the same or even less power than the systems they replace.
 
A third group, too
 
During his recent Morgan Stanley presentation, Papermaster of AMD also discussed a third group of server buyers: Organizations with hybrid IT orchestrations, both cloud and on-premises, that want the ability to move workloads back and forth. Essentially, this means mimicking the cloud in an on-prem environment.
 
Looking ahead, Papermaster discussed a forthcoming EPYC processor, code-named Bergamo, which he said is “right on track” to ship in this year’s first half. 
 
The new CPU will be aimed at cloud-native applications that need high levels of both throughput and per-socket performance. As previously announced, Bergamo will have up to 128 “Zen 4c” cores, and will come with the same software and security features as Genoa. 
 
“We listen to our customers,” Papermaster said, “and we see where workloads are going.” That’s a good practice for channel partners, too.
 
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What is the AMD Instinct MI300A APU?

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What is the AMD Instinct MI300A APU?

Accelerate HPC and AI workloads with the combined power of CPU and GPU compute. 

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The AMD Instinct MI300A APU, set to ship in this year’s second half, combines the compute power of a CPU with the capabilities of a GPU. Your data-center customers should be interested if they run high-performance computing (HPC) or AI workloads.

More specifically, the AMD Instinct MI300A is an integrated data-center accelerator that combines AMD Zen 4 cores, AMD CDNA3 GPUs and high-bandwidth memory (HBM) chiplets. In all, it has more than 146 billion transistors.

This AMD component uses 3D die stacking to enable extremely high bandwidth among its parts. In fact, nine 5nm chiplets that are 3D-stacked on top of four 6nm chiplets with significant HBM surrounding it.

And it’s coming soon. The AMD Instinct MI300A is currently in AMD’s labs. It will soon be sampled with customers. And AMD says it’s scheduled for shipments in the second half of this year. 

‘Most complex chip’

The AMD Instinct MI300A was publicly displayed for the first time earlier this year, when AMD CEO Lisa Su held up a sample of the component during her CES 2023 keynote. “This is actually the most complex chip we’ve ever built,” Su told the audience.

A few tech blogs have gotten their hands on early samples. One of them, Tom’s Hardware, was impressed by the “incredible data throughput” among the Instinct MI300A’s CPU, GPU and memory dies.

The Tom’s Hardware reviewer added that will let the CPU and GPU work on the same data in memory simultaneously, saving power, boosting performance and simplifying programming.

Another blogger, Karl Freund, a former AMD engineer who now works as a market researcher, wrote in a recent Forbes blog post that the Instinct MI300 is a “monster device” (in a good way). He also congratulated AMD for “leading the entire industry in embracing chiplet-based architectures.”

Previous generation

The new AMD accelerator builds on a previous generation, the AMD Instinct MI200 Series. It’s now used in a variety of systems, including Supermicro’s A+ Server 4124GQ-TNMI. This completely assembled system supports the AMD Instinct MI250 OAM (OCP Acceleration Module) accelerator and AMD Infinity Fabric technology.

The AMD Instinct MI200 accelerators are designed with the company’s 2nd gen AMD CDNA Architecture, which encompasses the AMD Infinity Architecture and Infinity Fabric. Together, they offer an advanced platform for tightly connected GPU systems, empowering workloads to share data fast and efficiently.

The MI200 series offers P2P connectivity with up to 8 intelligent 3rd Gen AMD Infinity Fabric Links with up to 800 GB/sec. of peak total theoretical I/O bandwidth. That’s 2.4x the GPU P2P theoretical bandwidth of the previous generation.

Supercomputing power

The same kind of performance now available to commercial users of the AMD-Supermicro system is also being applied to scientific supercomputers.

The AMD Instinct MI25X accelerator is now used in the Frontier supercomputer built by the U.S. Dept. of Energy. That system’s peak performance is rated at 1.6 exaflops—or over a billion billion floating-point operations per second.

The AMD Instinct MI250X accelerator provides Frontier with flexible, high-performance compute engines, high-bandwidth memory, and scalable fabric and communications technologies.

Looking ahead, the AMD Instinct MI300A APU will be used in Frontier’s successor, known as El Capitan. Scheduled for installation late this year, this supercomputer is expected to deliver at least 2 exaflops of peak performance.

 

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Learn, Earn and Win with AMD Arena

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Learn, Earn and Win with AMD Arena

Channel partners can learn about AMD products and technologies at the AMD Arena site. It’s your site for AMD partner training courses, redeemable points and much more.

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Interested in learning more about AMD products while also earning points you can redeem for valuable merch? Then check out the AMD Arena site.

There, you can:

  • Stay current on the latest AMD products with training courses, sales tools, webinars and quizzes;
  • Earn points, unlock levels and secure your place in the leaderboard;
  • Redeem those points for valuable products, experiences and merchandise in the AMD Rewards store.

Registering for AMD Arena is quick, easy and free. Once you’re in, you’ll have an Arena Dashboard as your control center. It’s where you can control your profile, begin a mission, track your progress, and view your collection of badges.

Missions are made of learning objectives that take you through training courses, sales tools, webinars and quizzes. Complete a mission, and you can earn points, badges and chips; unlock levels; and climb the leaderboard.

The more missions you complete, the more rewards you’ll earn. These include points you can redeem for merchandise, experiences and more from the AMD Arena Rewards Store.

Courses galore

Training courses are at the heart of the AMD Arena site. Here are just 3 of the many training courses waiting for you now:

  • AMD EPYC Processor Tool: Leverage the AMD processor-selector and total cost of ownership (TCO) tools to match your customers’ needs with the right AMD EPYC processor.
  • AMD EPYC Processor – Myth Busters: Get help fighting the myths and misconceptions around these powerful CPUs. Then show your data-center customers the way AMD EPYC delivers performance, security and scalability.

Get started

There’s lots more training in AMD Arena, too. The site supports virtually all AMD products across all business segments. So you can learn about both products you already sell as well as new products you’d like to cross-sell in the future.

To learn more, you can take this short training course: Introducing AMD Arena. In just 10 minutes, this course covers how to register for an AMD Arena account, use the Dashboard, complete missions and earn rewards.

Ready to learn, earn and win with AMD Arena? Visit AMD Arena now

 

 

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AMD and Supermicro Sponsor Two Fastest Linpack Scores at SC22’s Student Cluster Competition

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AMD and Supermicro Sponsor Two Fastest Linpack Scores at SC22’s Student Cluster Competition

The Student Cluster Computing challenge made its 16th appearance at the SuperComputer 22 (SC22) event in Dallas. The two student teams that were running AMD EPYC™ CPUs and AMD Instinct™ GPUs were the two teams that aced the Linpack benchmark. That's the test used to determined the TOP500 supercomputers in the world.

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Last month, the annual Supercomputing Conference 2022 (SC22) was held in Dallas. The Student Cluster Competition (SCC), which began in 2007, was also performed again. The SCC offers an immersive high-performance computing (HPC) experience to undergraduate and high school students.

 

According to the SC22 website: Student teams design and build small clusters, learn scientific applications, apply optimization techniques for their chosen architectures and compete in a non-stop, 48-hour challenge at the SC conference to complete real-world scientific workloads, showing off their HPC knowledge for conference attendees and judges.

 

Each team has six students, at least one faculty advisor, a sutdent team leader, and is associated with vendor sponsors, which provide the equipment. AMD and Supermicro jointly sponsored both the Massachusetts Green Team from MIT, Boston University and Northeastern University and the 2MuchCache team from UC San Diego (UCSD) and the San Diego Supercomputer Center (SDSC). Running AMD EPYC™ CPUs and AMD Instinct™-based GPUs supplied by AMD and Supermicro, the two teams came in first and second in the SCC Linpack test.

 

The Linpack benchmarks measure a system's floating-point computing power, according to Wikipedia. The latest version of these benchmarks is used to determine the TOP500 list, ranks the world's most powerful supercomputers.

 

In addition to chasing high scores on benchmarks, the teams must operate their systems without exceeding a power limit. For 2022, the competition used a variable power limit: at times, the power available to each team for its competition hardware was as high as 4000-watts (but was usually lower) and at times it was as low as 1500-watts (but was usually higher).

 

The “2MuchCache” team offers a poster page with extensive detail about their competition hardware. They used two third-generation AMD EPYC™ 7773X CPUs with 64 cores, 128 threads and 768MB of stacked-die cache. Team 2MuchCache used one AS-4124GQ-TNMI system with four AMD Instinct™ MI250 GPUs with 53 simultaneous threads.

 

The “Green Team’s” poster page also boasts two instances of third-generation AMD 7003-series EPYC™ processors, AMD Instinct™ 1210 GPUs with AMD Infinity fabric. The Green Team utilized two Supermicro AS-4124GS-TNR GPU systems.

 

The Students of 2MuchCache:

Longtian Bao, role: Lead for Data Centric Python, Co-lead for HPCG

Stefanie Dao, role: Lead for PHASTA, Co-lead for HPL

Michael Granado, role: Lead for HPCG, Co-lead for PHASTA

Yuchen Jing, role: Lead for IO500, Co-lead for Data Centric Python

Davit Margarian, role: Lead for HPL, Co-lead for LAMMPS

Matthew Mikhailov Major, role: Team Lead, Lead for LAMMPS, Co-lead for IO500

 

The Students of Green Team:

Po Hao Chen, roles: Team leader, theory & HPC, benchmarks, reproducibility

Carlton Knox, roles: Computer Arch., Benchmarks, Hardware

Andrew Nguyen, roles: Compilers & OS, GPUs, LAMMPS, Hardware

Vance Raiti, roles: Mathematics, Computer Arch., PHASTA

Yida Wang, roles: ML & HPC, Reproducibility

Yiran Yin, roles: Mathematics, HPC, PHASTA

 

Congratulations to both teams!

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Some Key Drivers behind AMD’s Plans for Future EPYC™ CPUs

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Some Key Drivers behind AMD’s Plans for Future EPYC™ CPUs

A video discussion between Charles Liang, Supermicro CEO, and Dr. Lisa Su, AMD CEO.

 

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Higher clock rates, more cores and larger onboard memory caches are some of the traditional areas of improvement for generational CPU upgrades. Performance improvements are almost a given with a new generation CPU. Increasingly, howeer, the more difficult challenges for data centers and performance-intensive computing are energy efficiency and managing heat. Energy costs have spiked in many parts of the world and “performance per watt” is what many companies are looking for. AMD’s 4th-gen EPYC™ CPU runs a little hotter than its predecessor, but its performance gains far outpace the thermal rise, making for much greater performance per watt. It’s a trade-off that makes sense, especially for performance-intensive computing, such HPC and technical computing applications.

In addition to the energy efficiency and heat dissipation concerns, Dr. Su and Mr. Liang discuss the importance of the AMD EPYC™ roadmap. You’ll learn one or two nuances about AMD’s plans. SMC is ready with 15 products that leverage the Genoa, AMD’s fourth generation EPYC™ CPU. This under 15-minute video recorded on November 15, 2022, will bring you up to date on all things AMD EPYC™. Click the link to see the video:

Supermicro & AMD CEOs Video – The Future of Data Center Computing

 

 

 

 

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Match CPU Options to Your Apps and Workloads to Maximize Efficiency

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Match CPU Options to Your Apps and Workloads to Maximize Efficiency

The CPU package is configurable at time of purchase with various options that you can match up to the specific characteristics of your workloads. Ask yourself the three questions the story poses.

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In a previous post, Performance-Intensive Computing explored the benefits of making your applications and workloads more parallel. Chief among the paybacks may be being able to take advantage of the latest innovations in performance-intensive computing.

 

Although it isn’t strictly a parallel approach, the CPU package is configurable at the time of purchase with various options that you can match up to the specific characteristics of your workloads. The goal of this story is to outline how to match up the appropriate features to purchase the best processors for your particular application collection. For starters: You should be asking yourself these three questions:

 

Question 1. Does your application require a great deal of memory and storage? Memory-bound apps are typically found when an application has to manipulate a large amount of data. To alleviate potential bottlenecks, purchase a CPU with the largest possible onboard caches to avoid swapping data from storage. Apps such as Reveal and others used in the oil and gas industry will typically require large onboard CPU caches to help prevent memory bottlenecks as data moves in and out of the processor.

 

Question 2. Do you have the right amount and type of storage for your data requirements? Storage has a lot of different parameters and how it interacts with the processor and your application isn’t one-size-fits-all. Performance-Intensive Computing has previously written about specialized file systems such as the one developed and sold by WekaIO that can aid in onboarding and manipulating large data collections.

 

Question 3. Does your application spend a lot of time communicating across networks, or is your application bound by the limits of your processor? For either of these situations, it might mean you might need CPUs with more cores and/or higher-processing clock speeds. This is the case, for example, with molecular dynamic apps such as Gromacs and Lammps. These situations might call for parts such as AMD’s Threadripper.

 

As you can see, figuring out the right kind of CPU – and its supporting chipsets – is a lot more involved than just purchasing the highest clock speed and largest number of cores. Knowing your data and applications will guide you to buying CPU hardware that makes your business more efficient.

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Locating Where to Drill for Oil in Deep Waters with Supermicro SuperServers® and AMD EPYC™ CPUs

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Locating Where to Drill for Oil in Deep Waters with Supermicro SuperServers® and AMD EPYC™ CPUs

Energy company Petrobas, based in Brazil, is using high-performance computing techniques to aid it in its oil and gas exploration, especially in deep-water situations. Petrobas used system integrator Atos to provide more than 250 Supermicro SuperServers. The cluster is ranked 33 on the current top500 list and goes by the name Pegaso.

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  • Atos

Brazilian energy company Petrobas is using high-performance computing techniques to aid it in its oil and gas exploration, especially in deep-water situations. These techniques can help reduce costs and make finding and extracting new hydrocarbon deposits quicker. Petrobras' geoscientists and software engineers quickly modify algorithms to take advantage of new capabilities as new CPU and GPU technologies become available.

 

The energy company used system integrator Atos to provide more than 250 Supermicro SuperServer AS-4124GO-NART+ servers running dual AMD EPYC™ 7512 processors. The cluster goes by the name Pegaso (which in Portuguese means the mythological horse Pegasus) and is currently listed at number 33 on the top500 list of fastest computing systems. Atos is a global leader in digital transformation with 112,000 world-wide employees. They have built other systems that appeared on the top500 list, and AMD powers 38 of them.

 

Petrobas has had three other systems listed on previous iterations of the Top500 list, using other processors. Pegaso is now the largest supercomputer in South America. It is expected to become fully operational next month.  Each of its servers runs CentOS and has 2TB of memory, for a total of 678TB. The cluster contains more than 230,000 core processors, is running more than 2,000 GPUs and is connected via an InfiniBand HDR networking system running at 400Gb/s. To give you an idea of how much gear is involved with Pegaso, it took more than 30 truckloads to deliver and consists of over 30 tons of hardware.

 

The geophysics team has a series of applications that require all this computing power, including seismic acquisition apps that collect data and is then processed to deliver high-resolution subsurface imaging to precisely locate the oil and gas deposits. Having the GPU accelerators in the cluster helps to reduce the processing time, so that the drilling teams can locate their rigs more precisely.

 

For more information, see this case study about Pegaso.

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Choosing the Right AI Infrastructure for Your Needs

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Choosing the Right AI Infrastructure for Your Needs

AI architecture must scale effectively without sacrificing cost efficiency. One size does not fit all.

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Building an agile, cost-effective environment that delivers on a company’s present and long-term AI strategies can be a challenge, and the impact of decisions made around that architecture will have an outsized effect on performance.

 

“AI capabilities are probably going to be 10%-15% of the entire infrastructure,” says Ashish Nadkarni, IDC group vice president and general manager, infrastructure systems, platforms and technologies. “But the amount the business relies on that infrastructure, the dependence on it, will be much higher. If that 15% doesn’t behave in the way that is expected, the business will suffer.”

 

Experts like Nadkarni note that companies can, and should, avail themselves of cloud-based options to test and ramp up AI capabilities. But as workloads increase over time, the costs associated with cloud computing can rise significantly, especially when workloads scale or the enterprise expands its usage, making on-premises architecture a valid alternative worth consideration.

 

No matter the industry, to build a robust and effective AI infrastructure, companies must first accurately diagnose their AI needs. What business challenges are they trying to solve? What forms of high-performance computing power can deliver solutions? What type of training is required to deliver the right insights from data? And what’s the most cost-effective way for a company to support AI workloads at scale and over time? Cloud may be the answer to get started, but for many companies on-prem solutions are viable alternatives.

 

“It’s a matter of finding the right configuration that delivers optimal performance for [your] workloads,” says Michael McNerney, vice president of marketing and network security at Supermicro, a leading provider of AI-capable, high-performance servers, management software and storage systems. “How big is your natural language processing or computer vision model, for example? Do you need a massive cluster for AI training? How critical is it to have the lowest latency possible for your AI inferencing? If the enterprise does not have massive models, does it move down the stack into smaller models to optimize infrastructure and cost on the AI side as well as in compute, storage and networking?”

 

Get perspective on these and other questions about selecting the right AI infrastructure for your business in the Nov. 20, 2022, Wall Street Journal paid program article:

 

Investing in Infrastructure

 

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