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Unlocking the Value of the Cloud for Mid-size Enterprises

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Unlocking the Value of the Cloud for Mid-size Enterprises

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  • Microsoft Azure

Organizations around the world are requiring new options for their next-generation computing environments. Mid-size organizations, in particular, are facing increasing pressure to deliver cost-effective, high-performance solutions within their hyperconverged infrastructures (HCI). Recent collaboration between Supermicro, Microsoft Azure and AMD, leveraging their collective technologies, has created a fresh approach that lets enterprises maintain performance at a lower operational cost while helping to reduce the organization’s carbon footprint in support of sustainability initiatives. This cost-effective, 1U system (a 2U version is available) offers both power, flexibility and modularity in large-scale GPU deployments.

The results of the collaboration combine the latest technologies, supporting multiple CPU, GPU, storage and networking options optimized to deliver uniquely configured and highly scalable systems. The product can be optimized for SQL and Oracle databases, VDI, productivity applications and database analytics. This white paper explores why this universal GPU architecture is an intriguing and cost-effective option for CTOs and IT administrators who are planning to rapidly implement hybrid cloud, data center modernization, branch office/edge networking or Kubernetes deployments at scale.

Get the 7-page white paper that provides the detail to assess the solution for yourself, including the new Azure Stack HCI certified system, specifications, cost justification and more.

 

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Enter Your Animation in Pixar’s RenderMan NASA Space Images Art Challenge

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Enter Your Animation in Pixar’s RenderMan NASA Space Images Art Challenge

For the first time, challengers can run their designs using thousands of AMD EPYC™ core CPUs, enabling artists to develop the most complex animations and the most amazing visualizations. “The contestants have access to this professional-grade render farm just like the pros. It levels the playing field,” said James Knight, the director of entertainment for AMD. “You can make scenes that weren’t possible before on your own PC,” he said.

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One of the biggest uses of performance-intensive computing is the creation of high-resolution graphic animations used for entertainment and commercial applications. To that end, AMD and Pixar Animation Studios have announced the ninth RenderMan Art Challenge, which is open to the public. The idea is to encourage creative types to use some of the same tools that professional graphic designers and animators use to build something based on actual NASA data.

 

The winners will be determined by a set of Pixar, NASA and Industrial Light and Magic judges. The projects must be submitted by November 15 and the winning entries will be announced at the end of November.

 

This year’s challenge provides access to the AMD virtual Azure virtual machines, letting contestants use the highest-performing compute instances. Contestants will be given entrance to The AMD Creator Cloud, a render farm powered by Azure HBv3 composed of high-performance AMD EPYC™ processors using AMD 3D V-Cache™ technology.

 

For the first time, challengers can run their designs using thousands of AMD EPYC™ core CPUs, enabling artists to develop the most complex animations and the most amazing visualizations. “The contestants have access to this professional-grade render farm just like the pros. It levels the playing field,” said James Knight, the director of entertainment for AMD. “You can make scenes that weren’t possible before on your own PC,” he said.

 

The topic focus for this year’s challenge is space-related, in keeping with NASA’s involvement. The challenge provides scientifically accurate 3D NASA models, including telescopes, space stations, suits and planets. One of the potential advantages: many of past contests have ended up working at Pixar. “The RenderMan challenge gives everyone a chance to learn new things and show their abilities and creativity. The whole experience was great," said Khachik Astvatsatryan, a previous RenderMan Challenge winner.

 

Dylan Sisson, a RenderMan digital artist at Pixar, said “With the advancements we are seeing in hardware and software, individual artists are now able to create images of ever-increasing sophistication and complexity. It is a great opportunity for challengers to unleash their creative vision with these state-of-the-art technologies."

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Register to Watch Supermicro's Sweeping A+ Launch Event on Nov. 10

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Register to Watch Supermicro's Sweeping A+ Launch Event on Nov. 10

Join Supermicro online Nov. 10th to watch the unveiling of the company’s new A+ systems -- featuring next-generation AMD EPYC™ processors. They can't tell us any more right now. But you can register for a link to the event by scrolling down and signing-up on this page.
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Energy-Efficient AMD EPYC™ Processors Bring Significant Savings

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Energy-Efficient AMD EPYC™ Processors Bring Significant Savings

Cut electricity consumption by up to half with AMD's power-saviing EPYC™ processors.

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  • Ateme, DBS, Nokia

Nokia was able to target up to a 40% reduction in server power consumption using EPYC. DBS and Ateme each experienced a 50% drop in energy costs. AMD’s EPYC™ processors can provide big energy-saving benefits, so you can meet your most demanding application performance requirements and still provide planetary and environmental efficiencies.

For example: To provide a collection of 1,200 virtual machines, AMD would require 10 servers compared to 15 for those built using equivalent Intel CPUs. This translates into a 41% lower total cost of ownership over a three-year period, with a third less energy consumption, saving on carbon emissions too. For deep detail and links to case studies by the companies mentioned above. Find out how they  saved significantly on energy-costs while reducing their carbon footprints, check out the infographic.

 

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The Perfect Combination: The Weka Next-Gen File System, Supermicro A+ Servers and AMD EPYC™ CPUs

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The Perfect Combination: The Weka Next-Gen File System, Supermicro A+ Servers and AMD EPYC™ CPUs

Weka’s file system, WekaFS, unifies your entire data lake into a shared global namespace where you can more easily access and manage trillions of files stored in multiple locations from one directory.

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  • Weka.io

One of the challenges of building machine learning (ML) models is managing data. Your infrastructure must be able to process very large data sets rapidly as well as ingest both structured and unstructured data from a wide variety of sources.

 

That kind of data is typically generated in performance-intensive computing areas like GPU-accelerated applications, structural biology and digital simulations. Such applications typically have three problems: how to efficiently fill a data pipeline, how to easily integrate data across systems and how to manage rapid changes in data storage requirements. That’s where Weka.io comes into play, providing higher-speed data ingestion and avoiding unnecessary copies of your data while making it available across the entire ML modeling space.

 

Weka’s file system, WekaFS, has been developed just for this purpose. It unifies your entire data lake into a shared global namespace where you can more easily access and manage trillions of files stored in multiple locations from one directory. It works across both on-premises and cloud storage repositories and is optimized for cloud-intensive storage so that it will provide the lowest possible network latencies and highest performance.

 

This next-generation data storage file system has several other advantages: it is easy to deploy, entirely software-based, plus it is a storage solution that provides all-flash level performance, NAS simplicity and manageability, cloud scalability and breakthrough economics. It was designed to run on any standard x86-based server hardware and commodity SSDs or run natively in the public cloud, such as AWS.

 

Weka’s file system is designed to scale to hundreds of petabytes, thousands of compute instances and billions of files. Read and write latency for file operations against active data is as low as 200 microseconds in some instances.

 

Supermicro has produced its own NVMe Reference Architecture that supports WekaFS on some of its servers, including the Supermicro A+ AS-1114S-WN10RT and AS-2114S-WN24RT using the AMD EPYC™ 7402P processors with at least 2TB of memory, expandable to 4TB. Both servers support hot-swappable NVMe storage modules for ultimate performance. Also check out the Supermicro WekaFS A/I and HPC Solution Bundle.

 

 

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Mercedes-AMG F1 Racing Team Gains an Edge with AMD’s EPYC™ Processors

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Mercedes-AMG F1 Racing Team Gains an Edge with AMD’s EPYC™ Processors

In F1, fast cars and fast computers go hand in hand. Computational performance became more important when F1 IT authorities added rules that dictate how much computing and wind tunnel time each team can use. Mercedes was the top finisher in 2021 giving it the biggest compute/wind tunnel handicap. So, when it selected a new computer system, it opted for AMD EPYC™ processors, gaining 20% performance improvement to get more modeling done in less time.

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  • Mercedes-AMG Petronas F1 racing team

In the high-stakes world of Formula One racing, finding that slight edge to build a better performing car often means using the most powerful computers to model aerodynamics. The Mercedes-AMG Petronas F1 racing team found that using AMD EPYC™ processors helps gain that edge. Since 2010, the team has brought home 124 race wins and nine driver’s championships across the F1 racing circuit.

 

Thanks to the increased performance of these AMD EPYC™ CPUs, the team is able to run twice the number of daily simulations. The key is having the best computational fluid dynamics models available. And time is of the essence because the racing association’s IT authorities have added rules that dictate how much computing and wind tunnel time each team can use, along with a dollar limit on computing resources to level the playing field despite resource differences.

 

Teams that traditionally have been top finishers of the race are allowed a third less computing time, and since the Mercedes team was the top 2021 finisher, it has the least computing allocation. The 2022 race limited computing expenditures to $140M, and for 2023, the number will be further cut to $135M. The result is that teams are focused on finding the highest performing computers at the lowest cost. In F1, fast cars and fast computers go hand in hand.

 

“Performance was the key driver of the decision making,” said Simon Williams, Head of Aero Development Software for the team. “We looked at AMD and the competitors. We needed to get this right, because we're going to be using this hardware for the next three years.” Mercedes replaced its existing three-year old computers with AMD EPYC™-based systems and gained 20% performance improvements, letting it run many more simulations in parallel. “I can't stress enough how important the fast turnaround is,” Williams said. “It's been great having AMD help us achieve that."

 

Servers such as the Supermicro A+ series can bring home big wins as well.

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Eliovp Increases Blockchain-Based App Performance with Supermicro Servers

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Eliovp Increases Blockchain-Based App Performance with Supermicro Servers

Eliovp, which brings together computing and storage solutions for blockchain workloads, rewrote its code to take full advantage of AMD’s Instinct™ MI100 and MI250 GPUs. As a result, Eliovp’s blockchain calculations run up to 35% faster than what it saw on previous generations of its servers.

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  • Eliovp

When you’re building blockchain-based applications, you typically need a lot of computing and storage horsepower. This is the niche that Belgium-based Eliovp fills. They have developed a line of extremely fast cloud-based servers designed to run demanding blockchain workloads.

 

Eliovp has been recognized as the top Filecoin storage provider in Europe. This refers to a decentralized blockchain-based protocol that lets anyone rent spare local storage and is a key Web3 component.

 

To satisfy the compute  and storage needs, Eliiovp employs Supermicro’s A+ AS-1124US® and AS-4124GS® servers, running quad-core AMD EPYC™ 7543 and 7313 CPUs and as many as 8 AMD Instinct™ MI100 and MI250 GPUs to further boost performance.

 

What makes these servers especially potent is that Eliovp rewrote its code to run on this specific AMD Instinct™ GPU family. As a result, Eliovp’s blockchain calculations run up to 35% faster than what it saw on previous generations of its servers.

 

One of the attractions of the Supermicro servers is the capability to leverage the high-density core count and higher clock speeds as well as the 32 memory slots. And it comes packaged in a relatively small form factor.

 

“By working with Supermicro, we get new generations of servers with AMD technology earlier in our development cycle, enabling us to bring our products to market faster," said Elio Van Puyvelde, CEO of Eliovp. The company was able to take advantage of new CPU and GPU instructions and memory management to make its code more efficient and effective. Eliovp was also able to reduce overall server power consumption, which is always important in blockchain applications that span dozens of machines.

 

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Microsoft Azure’s More Capable Compute Instances Take Advantage of the Latest AMD EPYC™ Processors

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Microsoft Azure’s More Capable Compute Instances Take Advantage of the Latest AMD EPYC™ Processors

Azure HBv3 series virtual machines (VMs) are optimized for HPC applications, such as fluid dynamics, explicit and implicit finite element analysis, weather modeling, seismic processing, and various simulation tasks. HBv3 VMs feature up to 120 Third-Generation AMD EPYC™ 7v73X-series CPU cores with more than 450 GB of RAM.

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  • Azure

Increasing demands for higher-performance computing mean that the cloud-based computing needs to ratchet up its performance too. Microsoft Azure has introduced more capable compute virtual machines (VMs) that take advantage of the latest from AMD EPYC™ processors. This means that developers can easily spin up VMs that normally cost thousands of dollars if they were to purchase their physical equivalents.

 

This story's focus is on two of Azure's series: HBv3 and NVv4. In most cases, a single virtual machine is used to take advantage of all its resources. High-performance examples of Azure HBv3 series VMs are optimized for HPC applications, such as fluid dynamics, explicit and implicit finite element analysis, weather modeling, seismic processing, and various simulation tasks. HBv3 VMs feature up to 120 Third-Generation AMD EPYC™ 7v73X-series CPU cores with more than 450 GB of RAM. This series of VMs has processor clock frequencies up to 3.5GHz. All HBv3-series VMs feature 200Gb/sec HDR InfiniBand switches to enable supercomputer-scale HPC workloads. The VMs are connected and optimized to deliver the most consistent performance. Get more information about AMD EPYC™ and Microsoft Azure virtual machines.

 

A Dutch construction company, TBI, is using the Azure NVv4 to run computer-aided design and building modeling tasks on a series of virtual Windows desktops. The NVv4 VMs are only available running Windows powered by from four to 32 AMD EPYC™ vCPUs and offering a partial to full AMD Instinct™ M125 GPU with memory ranging from 2GB to 17GB. Previous generations of NV instances used Intel CPUs and NVIDIA GPUs that offer less performance.

 

TBI chose this solution because it was cheaper, easier to support and keep its software collection updated. Using virtual desktops meant that no client data was stored on any laptops, making things more secure. Also, these instances delivered equivalent performance, taking advantage of the SR-IOV technology.

 

Supermicro offers a wide range of servers that incorporate the AMD EPYC™ CPU and a number of servers optimized for applications that use GPUs. These servers range from 1U rackmount servers to high end 4U GPU optimized systems. Whether you’re using it on-prem or you’re building your own cloud, Supermicro’s Aplus servers are optimized for performance and technical computing applications and they run Azure and other systems well. Get more information about Supermicro servers with AMD’s EPYC™ CPUs.

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Supermicro SuperBlades®: Designed to Power Through Distributed AI/ML Training Models

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Supermicro SuperBlades®: Designed to Power Through Distributed AI/ML Training Models

Running heavy AI/ML workloads can be a challenge for any server, but the SuperBlade has extremely fast networking options, upgradability, the ability to run two AMD EPYC™ 7000-series 64-core processors and the Horovod open-source framework for scaling deep-learning training across multiple GPUs.

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Running the largest artificial intelligence (AI) and machine learning (ML) workloads is a job for the higher-performing systems. Such loads are often tough for even more capable machines. Supermicro’s SuperBlade combines blades using AMD EPYC™ CPUs with competing GPUs into a single rack-mounted enclosure (such as the Supermicro SBE-820H-822). That leverages an extremely fast networking architecture for these demanding applications that need to communicate with other servers to complete a task.

 

The Supermicro SuperBlade fits everything into an 8U chassis that can host up to 20 individual servers. This means a single chassis can be divided into separate training and model processing jobs. The components are key: servers can take advantage of the 200G HDR InfiniBand network switch without losing any performance. Think of this as delivering a cloud-in-a-box, providing both easier management of the cluster along with higher performance and lower latencies.

 

The Supermicro SuperBlade is also designed as a disaggregated server, meaning that components can be upgraded with newer and more efficient CPUs or memory as technology progresses. This feature significantly reduces E-waste.


The SuperBlade line supports a wide selection of various configurations, including both CPU-only and mixed CPU/GPU models, such as the SBA-4119SG, which comes with up to two AMD EPYC™ 7000-series 64-core CPUs. These components are delivered on blades that can easily slide right in. Plus, they slide out as easily when you need to replace the blades or the enclosure. The SuperBlade servers support a wide network selection as well, ranging from 10G to 200G Ethernet connections.

 

The SuperBlade employs the Horovod distributed model-training, message-passing interface to let multiple ML sessions run in parallel, maximizing performance. In a sample test of two SuperBlade nodes, the solution was able to process 3,622 GoogleNet images/second, and eight nodes were able to scale up to 13,475 GoogleNet images/second.


As you can see, Supermicro’s SuperBlade improves performance-intensive computing and boosts AI and ML use cases, enabling larger models and data workloads. The combined solution enables higher operational efficiency to automatically streamline processes, monitor for potential breakdowns, apply fixes, more efficiently facilitate the flow of accurate and actionable data and scale up training across multiple nodes.

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Supermicro and Qumulo Deliver High-Performance File Data Management Solution

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Supermicro and Qumulo Deliver High-Performance File Data Management Solution

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  • Qumulo

One of the issues that’s key to delivering higher-performing computing solutions is something that predates the PC itself: managing distributed file systems. The challenge becomes more acute when the applications involve manipulating large quantities of data. The tricky part is in how they scale to support these data collections, which might consist of video security footage, life sciences data collections and other research projects.

 

Storage systems from Qumulo integrate well into a variety of existing environments, such as those involving multiple storage protocols and file systems. The company supports a wide variety of use cases that allow for scaling up and out to handle Petabyte data quantities. Qumulo can run at both the network edge, in the data center and on various cloud environments. Their systems run on Supermicro’s all non-volatile memory express (NVMe) platform, the highest performing protocol designed for manipulating data stored on SSD drives. The servers are built on 24-core 2.8 GHz AMD EPYC™ processors.


 

Qumulo provides built-in near real-time data analytics that let IT administrators predict storage trends and better manage storage capacity so that they can proactively plan and optimize workflows.

 

The product handles seamless file and object data storage, is hardware agnostic, and supports single data namespace and burstable computing running on the three major cloud providers (AWS, Google and Azure) with nearly instant data replication. Its distributed file system is designed to handle billions of files and works equally well on both small and large file sizes.

 

Qumulo also works on storage clusters, such as those created with Supermicro AS-1114S servers, which can accommodate up to 150TB per storage node. Qumulo Shift for Amazon S3 is a feature that lets users copy data to the Amazon S3 native format for easy access to AWS services if the required services are not available in an on-prem data center. 

For more information, see the white paper on the Supermicro and Qumulo High-Performance File Data Management and Distributed Storage solution, powered by AMD EPYC™ processors.

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