The Channel Company

Sponsored by:

Visit AMD Visit Supermicro

Performance Intensive Computing

Capture the full potential of IT

Tech Explainer: What’s special about an AI server?

Featured content

Tech Explainer: What’s special about an AI server?

What’s in an AI server that a general-purpose system lacks?

Learn More about this topic
  • Applications:
  • Featured Technologies:

The Era of Artificial Intelligence requires its own class of servers, and rightly so. The AI tech that increasingly powers our businesses, finance, entertainment and scientific research is some of the most resource-intensive in history. Without AI servers, all this would grind to a halt.

But why? What’s so special about AI servers? And how are they able to power successive evolutions of large language models, generative AI, machine learning, and all the other AI-based workloads we’ve come to rely on day in and day out?

Put another way: What do AI servers have that standard servers don’t?

The answer can be summed up in a single word: More.

When it comes to AI servers, it’s all about managing a symphony. The musical instruments include multiple processors, GPUs, memory modules, networking hardware and expansion options.

Sure, your average general-purpose server has many similar components. But both the quantity and performance of each component is considerably lower than those of an AI server. That helps keep the price affordable, heat low, and workload options open. But it certainly doesn’t have the integrated GPU needed to run AI workloads.

Best of the Beasts

Supermicro specializes in the deployment of jaw-dropping power. The company’s newest 8U GPU Server (AS -8126GS-TNMR) is engineered to chew through the world’s toughest AI workloads. It’s powered by dual AMD EPYC processors and eight AMD Instinct MI350X or Instinct MI325X accelerators. This server can tackle AI workloads while staying cool and scaling up to meet increasing demand.

Keeping AI servers from overheating can be a tough job. Even a lowly, multipurpose business server kicks off a lot of heat. Temperatures build up around vital components like the CPU, GPU and storage devices. If that heat hangs around too long, it can lead to performance issues and, eventually, system failure.

Preventing heat-related issues in a single general-purpose server can be accomplished with a few heatsinks and small-diameter fans. But when it comes to high-performance, multi-GPU servers like Supermicro’s new 4U GPU A+ Server (AS -4126GS-NMR-LCC), liquid cooling becomes a must-have.

It’s also vital that AI servers be designed with expansion in mind. When an AI-powered app becomes successful, IT managers must be able to scale up quickly and without interruption.

Supermicro’s H14 8U 8-GPU System sets the standard for scalability. The H14 offers up to 20 storage drives and up to 12 PCI Express 5.0 (PCIe) x16 expansion slots.

Users can fill these high-bandwidth slots with a dizzying array of optional hardware, including:

  • Network Interface Cards (NICs) like the new AI-focused AMD AI NIC for high-speed networking.
  • NVMe storage to provide fast disk access.
  • Field Programmable Gate Array (FPGA) modules, which can be set up for custom computation and reconfigured after deployment.
  • Monitoring and control management cards. These enable IT staff to power servers on and off remotely, and also access BIOS settings.
  • Additional GPUs to aid in AI training and inferencing.
  • AI Accelerators. The AMD Instinct series is designed to tackle computing for AI, both training and inference.

A Different Class of Silicon

Hardware like the Supermicro GPU Server epitomizes what it means to be an AI server. That’s due in part to the components it’s designed to house. We’re talking about some of the most advanced processing tech available today.

As mentioned above, that tech comes courtesy of AMD, whose 5th Gen AMD EPYC 9005 series processors and recently announced AMD Instinct MI350 Series GPUs are powerful enough to tackle any AI workload.

AMD’s Instinct MI350 accelerators deliver a 4x generation-on-generation AI compute increase and a 35x generational leap in inferencing.

Say the word, and Supermicro will pack your AI Server with dual AMD EPYC processors containing up to 192 cores. They’ll install the latest AMD Instinct M1350X platform with 8 GPUs, fill all 24 DIMM slots with 6TB of DDR5 memory, and add an astonishing 16 NVMe U.2 drives. 

Advances Just Around the Corner

It seems like each new day brings stories about bold advances in AI. Apparently, our new robot friends may have the answer to some very human questions like, how can we cure our most insidious diseases? And how do we deal with the looming threat of climate crisis?

The AI models that could answer those questions—not to mention the ones that will help us find even better movies on Netflix—will require more power as they grow.

To meet those demands, AI server engineers are already experimenting with the next generation of advanced cooling for dense GPU clusters, enhanced hardware-based security, and new, more scalable modular infrastructure.

In fact, AI server designers have begun using their own AI models to create bigger and better AI servers. How very meta.

Do More:

 

Featured videos

Events


Find AMD & Supermicro Elsewhere

Related Content

Meet Supermicro’s newest AI servers, powered by AMD Instinct MI350 Series GPUs

Featured content

Meet Supermicro’s newest AI servers, powered by AMD Instinct MI350 Series GPUs

Supermicro’s new AI servers are powered by a combination of AMD EPYC CPUs and AMD Instinct GPUs.

Learn More about this topic
  • Applications:
  • Featured Technologies:

Supermicro didn’t waste any time supporting AMD’s new Instinct MI350 Series GPUs. The same day AMD formally introduced the new GPUs, Supermicro announced two rack-mount servers that support them.

The new servers, members of Supermicro’s H14 generation of GPU optimized solutions, feature dual AMD EPYC 9005 CPUs along with the AMD Instinct MI350 series GPUs. They’re aimed at organizations looking to achieve a formerly tough combination: maximum performance at scale in their AI-driven data centers, but also a lower total cost of ownership (TCO).

To make the new servers easy to upgrade and scale, Supermicro has designed the new servers around its proven building-block architecture.

Here’s a quick look at the two new Supermicro servers:

4U liquid-cooled system with AMD Instinct MI355X GPU

This system, model number AS -4126GS-NMR-LCC, comes with a choice of dual AMD EPYC 9005 or 9004 Series CPUs, both with liquid cooling.

On the GPU front, users also have a choice of the AMD Instinct MI325X or brand-new AMD Instinct MI355X. Either way, this server can handle up to 8 GPUs.

Liquid cooling is provided by a single direct-to-chip cold plate. Further cooling comes from 5 heavy-duty fans and an air shroud.

8U air-cooled system with AMD Instinct MI350X GPU

This system, model number AS -8126GS-TNMR, comes with a choice of dual AMD EPYC 9005 or 9004 Series CPUs, both with air cooling.

This system also supports both the AMD Instinct MI325X and AMD Instinct MI350X GPUs. Also like the 4U server, this system supports up to 8 GPUs.

Air cooling is provided by 10 heavy-duty fans and an air shroud.

The two systems also share some features in common. These include PCIe 5.0 connectivity, large memory capacities (up to 2.3TB), and support for both AMD’s ROCm open-source software and AMD Infinity Fabric Link connections for GPUs.

“Supermicro continues to lead the industry with the most experience in delivering high-performance systems designed for AI and HPC applications,” says Charles Liang, president and CEO of Supermicro. “The addition of the new AMD Instinct MI350 series GPUs to our GPU server lineup strengthens and expands our industry-leading AI solutions and gives customers greater choice and better performance as they design and build the next generation of data centers.”

Do More:

 

Featured videos

Events


Find AMD & Supermicro Elsewhere

Related Content

AMD presents its vision for the AI future: open, collaborative, for everyone

Featured content

AMD presents its vision for the AI future: open, collaborative, for everyone

Check out the highlights of AMD’s Advancing AI event—including new GPUs, software and developer resources.

Learn More about this topic
  • Applications:
  • Featured Technologies:

AMD advanced its AI vision at the “Advancing AI” event on June 12. The event, held live in the Silicon Valley city of San Jose, Calif., as well as online, featured presentations by top AMD executives and partners.

As many of the speakers made clear, AMD’s vision for AI is that it be open, developer-friendly, collaborative and useful to all.

AMD certainly believes the market opportunity is huge. During the day’s keynote, CEO Lisa Su said AMD now believes the total addressable market (TAM) for data-center AI will exceed $500 billion by as soon as 2028.

And that’s not all. Su also said she expects AI to move beyond the data center, finding new uses in edge computers, PCs, smartphone and other devices.

To deliver on this vision, Su explained, AMD is taking a three-pronged approach to AI:

  • Offer a broad portfolio of compute solutions.
  • Invest in an open development ecosystem.
  • Deliver full-stack solutions via investments and acquisitions.

The event, lasting over two hours, was also filled with announcements. Here are the highlights.

New: AMD Instinct MI350 Series

At the Advancing AI event, CEO Su formally announced the company’s AMD Instinct MI350 Series GPUs.

There are two models, the MI350X and MI355X. Though both are based on the same silicon, the MI355X supports higher thermals.

These GPUs, Su explained, are based on AMD’s 4th gen Instinct architecture, and each GPU comprises 10 chiplets containing a total of 185 billion transistors. The new Instinct solutions can be used for both AI training and AI inference, and they can also be configured in either liquid- or air-cooled systems.

Su said the MI355X delivers a massive 35x general increase in AI performance over the previous-generation Instinct MI300. For AI training, the Instinct MI355X offers up to 3x more throughput than the Instinct MI300. And in comparison with a leading competitive GPU, the new AMD GPU can create up to 40% more tokens per dollar.

AMD’s event also featured several representatives of companies already using AMD Instinct MI300 GPUs. They included Microsoft, Meta and Oracle.

Introducing ROCm 7 and AMD Developer Cloud

Vamsi Boppana, AMD’s senior VP of AI, announced ROCm 7, the latest version of AMD’s open-source AI software stack. ROCm 7 features improved support for industry-standard frameworks; expanded hardware compatibility; and new development tools, drivers, APIs and libraries to accelerate AI development and deployment.

Earlier in the day, CEO Su said AMD’s software efforts “are all about the developer experience.” To that end, Boppana introduced the AMD Developer Cloud, a new service designed for rapid, high-performance AI development.

He also said AMD is giving developers a 25-hour credit on the Developer Cloud with “no strings.” The new AMD Developer Cloud is generally available now.

Road Map: Instinct MI400, Helios rack, Venice CPU, Vulcano NIC

During the last segment of the AMD event, Su gave attendees a sneak peek at several forthcoming products:

  • Instinct MI400 Series: This GPU is being designed for both large-scale AI inference and training. It will be the heart of the Helios rack solution (see below) and provide what Su described as “the engine for the next generation of AI.” Expect performance of up to 40 petaflops, 432GB of HBM4 memory, and bandwidth of 19.6TB/sec.
  • Helios: The code name for a unified AI rack solution coming in 2026. As Su explained it, Helios will be a rack configuration that functions like a single AI engine, incorporating AMD’s EPYC CPU, Instinct GPU, Pensando Pollara network interface card (NIC) and ROCm software. Specs include up to 72 GPUs in a rack and 31TB of HBM3 memory.
  • Venice: This is the code name for the next generation of AMD EPYC server CPUs, Su said. They’ll be based on a 2nm form, feature up to 256 cores, and offer a 1.7x performance boost over the current generation.
  • Vulcano: A future NIC, it will be built using a 3nm form and feature speeds of up to 800Gb/sec.

Do More:

 

 

Featured videos

Events


Find AMD & Supermicro Elsewhere

Related Content

Tech Explainer: What’s a NIC? And how can it empower AI?

Featured content

Tech Explainer: What’s a NIC? And how can it empower AI?

With the acceleration of AI, the network interface card is playing a new, leading role.

Learn More about this topic
  • Applications:
  • Featured Technologies:

The humble network interface card (NIC) is getting a status boost from AI.

At a fundamental level, the NIC enables one computing device to communicate with others across a network. That network could be a rendering farm run by a small multimedia production house, an enterprise-level data center, or a global network like the internet.

From smartphones to supercomputers, most modern devices use a NIC for this purpose. On laptops, phones and other mobile devices, the NIC typically connects via a wireless antenna. For servers in enterprise data centers, it’s more common to connect the hardware infrastructure with Ethernet cables.

Each NIC—or NIC port, in the case of an enterprise NIC—has its own media access control (MAC) address. This unique identifier enables the NIC to send and receive relevant packets. Each packet, in turn, is a small chunk of a much larger data set, enabling it to move at high speeds.

Networking for the Enterprise

At the enterprise level, everything needs to be highly capable and powerful, and the NIC is no exception. Organizations operating full-scale data centers rely on NICs to do far more than just send emails and sniff packets (the term used to describe how a NIC “watches” a data stream, collecting only the data addressed to its MAC address).

Today’s NICs are also designed to handle complex networking tasks onboard, relieving the host CPU so it can work more efficiently. This process, known as smart offloading, relies on several functions:

  • TCP segmentation offloading: This breaks big data into small packets.
  • Checksum offloading: Here, the NIC independently checks for errors in the data.
  • Receive side scaling: This helps balance network traffic across multiple processor cores, preventing them from getting bogged down.
  • Remote Direct Memory Access (RDMA): This process bypasses the CPU and sends data directly to GPU memory.

Important as these capabilities are, they become even more vital when dealing with AI and machine learning (ML) workloads. By taking pressure off the CPU, modern NICs enable the rest of the system to focus on running these advanced applications and processing their scads of data.

This symbiotic relationship also helps lower a server’s operating temperature and reduce its power usage. The NIC does this by increasing efficiency throughout the system, especially when it comes to the CPU.

Enter the AI NIC

Countless organizations both big and small are clamoring to stake their claims in the AI era. Some are creating entirely new AI and ML applications; others are using the latest AI tools to develop new products that better serve their customers.

Either way, these organizations must deal with the challenges now facing traditional Ethernet networks in AI clusters. Remember, Ethernet was invented over 50 years ago.

AMD has a solution: a revolutionary NIC it has created for AI workloads, the AMD AI NIC card. Recently released, this NIC card is designed to provide the intense communication capabilities demanded by AI and ML models. That includes tightly coupled parallel processing, rapid data transfers and low-latency communications.

AMD says its AI NIC offers a significant advancement in addressing the issues IT managers face as they attempt to reconcile the broad compatibility of an aging network technology with modern AI workloads. It’s a specialized network accelerator explicitly designed to optimize data transfer within back-end AI networks for GPU-to-GPU communication.

To address the challenges of AI workloads, what’s needed is a network that can support distributed computing over multiple GPU nodes with low jitter and RDMA. The AMD AI NIC is designed to manage the unique communication patterns of AI workloads and offer high throughput across all available links. It also offers congestion avoidance, reduced tail latency, scalable performance, and fast job-completion times.

Validated NIC

Following rigorous validation by the engineers at Supermicro, the AMD AI NIC is now supported on the Supermicro 8U GPU Server (AS -8126GS-TNMR). This behemoth is designed specifically for AI, deep learning, high-performance computing (HPC), industrial automation, retail and climate modeling.

In this configuration, AMD’s smart AI-focused NIC can offload networking tasks. This lets the Supermicro SuperServer’s dual AMD EPYC 9000-series processors run at even higher efficiency.

In the Supermicro server, the new AMD AI NIC occupies one of the myriad PCI Express x16 slots. Other optional high-performance PCIe cards include a CPU-to-GPU interconnect and up to eight AMD Instinct GPU accelerators.

In the NIC of time

A chain is only as strong as its weakest link. The chain that connects our ever-expanding global network of AI operations is strengthened by the advent of NICs focused on AI.

As NICs grow more powerful, these advanced network interface cards will help fuel the expansion of the AI/ML applications that power our homes, offices, and everything in between. They’ll also help us bypass communication bottlenecks and speed time to market.

For SMBs and enterprises alike, that’s good news indeed.

Do More:

1

 

Featured videos

Events


Find AMD & Supermicro Elsewhere

Related Content

Oil & gas spotlight: Fueling up with AI

Featured content

Oil & gas spotlight: Fueling up with AI

AI is helping industry players that include BP, Chevron and Shell automate a wide range of important use cases. To serve them, AMD and Supermicro offer powerful accelerators and servers.

Learn More about this topic
  • Applications:
  • Featured Technologies:

What’s artificial intelligence good for? For managers in the oil and gas industry, quite a lot.

Industry players that include Shell, BP, ExxonMobil and Chevron are already using machine learning and AI. Use cases include predictive maintenance, seismic data analysis, reservoir management and safety monitoring, says a recent report by Chirag Bharadwaj of consultants Appinventiv.

AI’s potential benefits for oil and gas companies are substantial. Anurag Jain of AI consultants Oyelabs cites estimates of AI lowering oil production costs by up to $5 a barrel with a 25% productivity gain, and increasing oil reserves by as much as 20% with enhanced resource recovery.

Along the same lines is a recent report from market watcher Global Growth Insights. It says adoption of AI in North American oil shale drilling has increased production efficiency by an impressive 20%.

All this has led Jain of Oyelabs to expect a big increase in the oil and gas industry’s AI spend. He predicts the industry’s worldwide spending on AI will rise from $3 billion last year to nearly $5.3 billion in 2028.

Assuming Jain is right, that would put the oil and gas industry’s AI spend at about 15% of its total IT spend. Last year, the industry spent nearly $20 billion on all IT goods and services worldwide, says Global Growth Insights.

Powerful Solutions

All this AI activity in the oil and gas industry hasn’t passed the notice of AMD and Supermicro. They’re on the case.

AMD is offering the industry its AMD Instinct MI300A, an accelerator that combines CPU cores and GPUs to fuel the convergence of high-performance computing (HPC) with AI. And Supermicro is offering rackmount servers driven by this AMD accelerator.

Here are some of the benefits the two companies are offering oil and gas companies:

  • An APU multi-chip architecture that enables dense compute, high-bandwidth memory integration, and chips for both CPU and GPU all in one.
  • Up to 2.6x the HPC performance/watt vs. the older AMD Instinct MI250X.
  • Up to 5.1x the AI-training workload performance with INT8 vs. the AMD Instinct MI250X. (INT8 is a fixed-point representation using 8 bits.)
  • Up to 128GB of unified HBM3 memory dedicated to GPUs. (HBM3 is a high-bandwidth memory chip technology that offers increased bandwidth, memory capacity and power efficiency, all in a smaller form factor.)
  • Double-precision power up to 122.6 TFLOPS with FP64 matrix HPC performance. (FP64 is a double-precision floating point format using 64 bits in memory.)
  • Complete, pre-validated solutions that are ready for rack-scale deployment on day one. These offer the choice of either 2U (liquid cooled) or 4U (air cooled) form factors.
     

If you have customers in oil and gas looking to get into AI, tell them about these Supermicro and AMD solutions.

Do More:

 

Featured videos

Events


Find AMD & Supermicro Elsewhere

Related Content

Tech Explainer: What is Quantum Computing, and How Does It Work?

Featured content

Tech Explainer: What is Quantum Computing, and How Does It Work?

Quantum computing promises to solve problems faster by simultaneously investigating many possible solutions at once. That’s far easier said than done.

Learn More about this topic
  • Applications:

Quantum computing has the potential to alter life as we know it. If, that is, we can figure out how to make the technology work on a massive scale.

This emerging technology is full of promise. At least in theory, it’s powerful enough to help us cure our most insidious diseases, usher in an era of artificial general intelligence (AGI), and enable us to explore neighboring galaxies.

Way, Way Faster

Quantum computing offers a way to solve these kinds of highly complex problems by simultaneously investigating many possible solutions at once.

To understand why this is so important, imagine a robot that’s attempting to find its way through an enormous maze. First, the robot acts as a human might, investigating each possible route, one at a time. Because the maze is so big and has so many possible pathways, this method could take the robot days, weeks or even years to complete.

Now imagine that instead, the robot can instantaneously clone itself, sending each new instance to investigate a potential route. This method would produce results many orders of magnitude faster than the one-at-a-time method.

And that is the promise offered by quantum computing.

Quantum Mechanics

To do all this heavy lifting, quantum computers behave in ways that may seem mysterious.

As you probably know, today’s standard computers operate using bits—binary switches that at any given moment have a value of either 0 or 1. But quantum computers run differently. They employ qubits (short for quantum bits), each of which can represent 0, 1—or both at the same time.

The ability of a particle-based object to be in two states at once? Yes. It’s a fundamental aspect of quantum mechanics known as superimposition.

Leveraging this ability at the bit level enables quantum computers to significantly reduce the time they need to solve problems. Particularly valuable examples of this include defeating encryption, decoding human physiology, even theorizing the mechanics of light-speed travel.

In other words, Star Trek stuff, pure and simple.

Not So Fast?

So why can’t you buy a quantum computer from your local BestBuy? Turns out that many factors have kept the promise of quantum computing just out of reach.

One of the most prevalent is errors at the qubit level. Qubits have a nasty habit of exchanging information with their environment.

By analogy, imagine spinning a basketball on your fingertip, Harlem Globetrotter style. The fast-spinning ball exists in a delicate state. Even tiny disturbances—such as air currents or ambient vibrations—could make the ball wobble and eventually fall.

A similar situation exists for quantum computers. Small environmental inconsistencies can impact qubits on an exponential scale. In fact, the more qubits you use, the more errors you get. Cross a certain threshold, and eventually the number of errors renders a quantum computer no more powerful than today’s standard computers.

Engineers are making progress in their efforts to solve this problem. For example, a French startup with the unlikely name of Alice & Bob was recently funded to the tune of €100 million to develop a new approach to quantum error correction.

Similarly, Google recently announced Willow, a new quantum computing chip the company says can reduce errors exponentially as it scales up. If a recent blog post by Hartmut Neven, lead of Google Quantum AI, is right, then it would seem Google has solved a 30-year-old challenge in quantum error correction.

The Key: R&D

AMD is also attempting to knock down some common quantum computing roadblocks.

The company filed a patent in 2021 titled “Look Ahead Teleportation for Reliable Computation in Multi-SIMD Quantum Processor.” AMD says this breakthrough improves quantum computing system reliability and reduces the number of required qubits. These efforts could revolutionize quantum computing scalability and error correction.

AMD has also created the Zynq UltraScale+ RFSoC, the industry’s only single-chip adaptable radio platform. The Zynq creates high-accuracy, high-speed pulse sequences to control qubits.

Companies like AMD partner Riverlane are using this cutting-edge technology to better control qubits and reduce errors.

When Will We Be There?

Not even a quantum computer can predict the future. But some experts say we could still be 10 to 20 years away from deploying quantum computing on a scale comparable to the ubiquity of the computers we use today.

In the near term, the most powerful tech companies—including AMD and Supermicro—will be working to harness the massive power of qubits.

To achieve their loftiest goals, however, they’ll need to revolutionize scalability and error correction. Only then can we deploy not just hundreds of qubits, but millions.

Once that code is cracked, there’s no telling where we’ll go from there.

 

Featured videos

Events


Find AMD & Supermicro Elsewhere

Related Content

AMD Instinct MI300A blends GPU, CPU for super-speedy AI/HPC

Featured content

AMD Instinct MI300A blends GPU, CPU for super-speedy AI/HPC

CPU or GPU for AI and HPC? You can get the best of both with the AMD Instinct MI300A.

Learn More about this topic
  • Applications:
  • Featured Technologies:

The AMD Instinct MI300A is the world’s first data center accelerated processing unit for high-performance computing and AI. It does this by integrating both CPU and GPU cores on a single package.

That makes the AMD Instinct MI300A highly efficient at running both HPC and AI workloads. It also makes the MI300A powerful enough to accelerate training the latest AI models.

Introduced about a year ago, the AMD Instinct MI300A accelerator is shipping soon. So are two Supermicro servers—one a liquid-cooled 2U system, the other an air-cooled 4U—each powered by four MI300A units.

Under the Hood

The technology of the AMD Instinct MI300A is impressive. Each MI300A integrates 24 AMD ‘Zen 4’ x86 CPU cores with 228 AMD CDNA 3 high-throughput GPU compute units.

You also get 128GB of unified HBM3 memory. This presents a single shared address space to CPU and GPU, all of which are interconnected into the coherent 4th Gen AMD Infinity architecture.

Also, the AMD Instinct MI300A is designed to be used in a multi-unit configuration. This means you can connect up to four of them in a single server.

To make this work, each APU has 1 TB/sec. of bidirectional connectivity through eight 128 GB/sec. AMD Infinity Fabric interfaces. Four of the interfaces are dedicated Infinity Fabric links. The other four can be flexibly assigned to deliver either Infinity Fabric or PCIe Gen 5 connectivity.

In a typical four-APU configuration, six interfaces are dedicated to inter-GPU Infinity Fabric connectivity. That supplies a total of 384 GB/sec. of peer-to-peer connectivity per APU. One interface is assigned to support x16 PCIe Gen 5 connectivity to external I/O devices. In addition, each MI300A includes two x4 interfaces to storage, such as M.2 boot drives, plus two USB Gen 2 or 3 interfaces.

Converged Computing

There’s more. The AMD Instinct MI300A was designed to handle today’s convergence of HPC and AI applications at scale.

To meet the increasing demands of AI applications, the APU is optimized for widely used data types. These include FP64, FP32, FP16, BF16, TF32, FP8 and INT8.

The MI300A also supports native hardware sparsity for efficiently gathering data from sparse matrices. This saves power and compute cycles, and it also lowers memory use.

Another element of the design aims at high efficiency by eliminating time-consuming data copy operations. The MI300A can easily offload tasks easily between the CPU and GPU. And it’s all supported by AMD’s ROCm 6 open software platform, built for HPC, AI and machine learning workloads.

Finally, virtualized environments are supported on the MI300A through SR-IOV to share resources with up to three partitions per APU. SR-IOV—short for single-root, input/output virtualization—is an extension of the PCIe spec. It allows a device to separate access to its resources among various PCIe functions. The goal: improved manageability and performance.

Fun fact: The AMD Instinct MI300A is a key design component of the El Capitan supercomputer recently dedicated by Lawrence Livermore Labs. This system can process over two quintillion (1018) calculations per second.

Supermicro Servers

As mentioned above, Supermicro now offers two server systems based on the AMD Instinct MI300A APU. They’re 2U and 4U systems.

These servers both take advantage of AMD’s integration features by combining four MI300A units in a single system. That gives you a total of 912 GPUs, 96 CPUs, and 512GB of HBM3 memory.

Supermicro says these systems can push HPC processing to Exascale levels, meaning they’re very, very fast. “Flop” is short for floating point operations per second, and “exa” indicates a 1 with 18 zeros after it. That’s fast.

Supermicro’s 2U server (model number AS -2145GH-TNMR-LCC) is liquid-cooled and aimed at HPC workloads. Supermicro says direct-to-chip liquid-cooling technology enables a nice TCO with over 51% data center energy cost savings. The company also cites a 70% reduction in fan power usage, compared with air-cooled solutions.

If you’re looking for big HPC horsepower, Supermicro’s got your back with this 2U system. The company’s rack-scale integration is optimized with dual AIOM (advanced I/O modules) and 400G networking. This means you can create a high-density supercomputing cluster with as many as 21 of Supermicro’s 2U systems in a 48U rack. With each system combining four MI300A units, that would give you a total of 84 APUs.

The other Supermicro server (model number AS -4145GH-TNMR) is an air-cooled 4U system, also equipped with four AMD Instinct MI300A accelerators, and it’s intended for converged HPC-AI workloads. The system’s mechanical airflow design keeps thermal throttling at bay; if that’s not enough, the system also has 10 heavy-duty 80mm fans.

Do More:

 

Featured videos

Events


Find AMD & Supermicro Elsewhere

Related Content

AMD’s new ROCm 6.3 makes GPU programming even better

Featured content

AMD’s new ROCm 6.3 makes GPU programming even better

AMD recently introduced version 6.3 of ROCm, its open software stack for GPU programming. New features included expanded OS support and other optimizations.

Learn More about this topic
  • Applications:
  • Featured Technologies:

There’s a new version of AMD ROCm, the open software stack designed to enable GPU programming from low-level kernel all the way up to end-user applications.  

The latest version, ROCm 6.3, adds features that include expanded operating system support, an open-source toolkit and more.

Rock On

AMD ROCm provides the tools for HIP (the heterogeneous-computing interface for portability), OpenCL and OpenMP. These include compilers, APIs, libraries for high-level functions, debuggers, profilers and runtimes.

ROCm is optimized for Generative AI and HPC applications, and it’s easy to migrate existing code into. Developers can use ROCm to fine-tune workloads, while partners and OEMs can integrate seamlessly with AMD to create innovative solutions.

The latest release builds on ROCm 6, which AMD introduced last year. Version 6 added expanded support for AMD Instinct MI300A and MI300X accelerators, key AI support features, optimized performance, and an expanded support ecosystem.

The senior VP of AMD’s AI group, Vamsi Boppana, wrote in a recent blog post: “Our vision is for AMD ROCm to be the industry’s premier open AI stack, enabling choice and rapid innovation.”

New Features

Here’s some of what’s new in AMD ROCm 6.3:

  • rocJPEG: A high-performance JPEG decode SDK for AMD GPUs.
  • ROCm compute profiler and system profiler: Previously known as Omniperf and Omnitrace, these have been renamed to reflect their new direction as part of the ROCm software stack.
  • Shark AI toolkit: This open-source toolkit is for high-performance serving of GenAI and  LLMs. Initial release includes support for the AMD Instinct MI300.
  • PyTorch 2.4 support: PyTorch is a machine learning library used for applications such as computer vision and natural language processing. Originally developed by Meta AI, it’s now part of the Linux Foundation umbrella.
  • Expanded OS support: This includes added support for Ubuntu 24.04.2 and 22.04.5; RHEL 9.5; and Oracle Linux 8.10. In addition, ROCm 6.3.1 includes support for both Debian 12 and the AMD Instinct MI325X accelerator.
  • Documentation updates: ROCm 6.3 offers clearer, more comprehensive guidance for a wider variety of use cases and user needs.

Super for Supermicro

Developers can use ROCm 6.3 to create tune workloads and create solutions for Supermicro GPU systems based on AMD Instinct MI300 accelerators.

Supermicro offers three such systems:

Are your customers building AI and HPC systems? Then tell them about the new features offered by AMD ROCm 6.3.

Do More:

 

 

Featured videos

Events


Find AMD & Supermicro Elsewhere

Related Content

2024: A look back at the year’s best

Featured content

2024: A look back at the year’s best

Let's look back at 2024, a year when AI was everywhere, AMD introduced its 5th Gen EPYC processors, and Supermicro led with liquid cooling.

Learn More about this topic
  • Applications:
  • Featured Technologies:

You couldn't call 2024 boring.

If anything, the year was almost too exciting, too packed with important events, and moving much too fast.

Looking back, a handful of 2024’s technology events stand out. Here are a few of our favorite things.

AI Everywhere

In March AMD’s chief technology officer, Mark Papermaster, made some startling predictions that turned out to be absolutely true.

Speaking at an investors’ event sponsored by Arete Research, Papermaster said, “We’re thrilled to bring AI across our entire product portfolio.” AMD has indeed done that, offering AI capabilities from PCs to servers to high-performance GPU accelerators.

Papermaster also said the buildout of AI is an event as big as the launch of the internet. That certainly sounds right.

He also said AMD believes the total addressable market for AI through 2027 to be $400 billion. If anything, that was too conservative. More recently, consultants Bain & Co. predicted that figure will reach $780 billion to $990 billion.

Back in March, Papermaster said AMD had increased its projection for full-year AI sales from $2 billion to $3.5 billion. That’s probably too low, too.

AMD recently reported revenue of $3.5 billion for its data-center group for just the third quarter alone. The company attributed at least some of the group’s 122% year-on-year increase to the strong ramp of AMD Instinct GPU shipments.

5th Gen AMD EPYC Processors

October saw AMD introduce the fifth generation of its powerful line of EPYC server processors.

The 5th Gen AMD EPYC processors use the company’s new ‘Zen 5’ core architecture. It includes over 25 SKUs offering anywhere from 8 to 192 cores. And the line includes a model—the AMD EPYC 9575F—designed specifically to work with GPU-powered AI solutions.

The market has taken notice. During the October event, AMD CEO Lisa Su told the audience that nearly one in three servers worldwide (34%) are now powered by AMD EPYC processors. And Supermicro launched its new H14 line of servers that will use the new EPYC processors.

Supermicro Liquid Cooling

As servers gain power to add AI and other compute-intensive capabilities, they also run hotter. For data-center operators, that presents multiple challenges. One big one is cost: air conditioning is expensive. What’s more, AC may be unable to cool the new generation of servers.

Supermicro has a solution: liquid cooling. For some time, the company has offered liquid cooling as a data-center option.

In November the company took a new step in this direction. It announced a server that comes with liquid cooling only.

The server in question is the Supermicro 2U 4-node FlexTwin, model number AS -2126FT-HE-LCC. It’s a high-performance, hot-swappable, high-density compute system designed for HPC workloads.

Each 2U system comprises 4 nodes, and each node is powered by dual AMD EPYC 9005 processors. (The previous-gen AMD EPYC 9004s are supported, too.)

To keep cool, the FlexTwin server uses a direct-to-chip (D2C) cold plate liquid cooling setup. Each system also runs 16 counter-rotating fans. Supermicro says this cooling arrangement can remove up to 90% of server-generated heat.

AMD Instinct MI325X Accelerator

A big piece of AMD’s product portfolio for AI is its Instinct line of accelerators. This year the company promised to maintain a yearly cadence of new Instinct models.

Sure enough, in October the company introduced the AMD Instinct MI325X Accelerator. It’s designed for Generative AI performance and working with large language models (LLMs). The system offers 256GB of HBM3E memory and up to 6TB/sec. of memory bandwidth.

Looking ahead, AMD expects to formally introduce the line’s next member, the AMD Instinct MI350, in the second half of next year. AMD has said the new accelerator will be powered by a new AMD CDNA 4 architecture, and will improve AI inferencing performance by up to 35x compared with the older Instinct MI300.

Supermicro Edge Server

A lot of computing now happens at the edge, far beyond either the office or corporate data center.

Even more edge computing is on tap. Market watcher IDC predicts double-digit growth in edge-computing spending through 2028, when it believes worldwide sales will hit $378 billion.

Supermicro is on it. At the 2024 MWC, held in February in Barcelona, the company introduced an edge server designed for the kind of edge data centers run by telcos.

Known officially as the Supermicro A+ Server AS -1115SV-WTNRT, it’s a 1U short-depth server powered by a single AMD EPYC 8004 processor with up to 64 cores. That’s edgy.

Happy Holidays from all of us at Performance Intensive Computing. We look forward to serving you in 2025.

Check out these related blog posts:

 

Featured videos

Events


Find AMD & Supermicro Elsewhere

Related Content

Supermicro JumpStart remote test site adds latest 5th Gen AMD EPYC processors

Featured content

Supermicro JumpStart remote test site adds latest 5th Gen AMD EPYC processors

Register now to test the Supermicro H14 2U Hyper with dual AMD EPYC 9965 processors from the comfort and convenience of your office.

Learn More about this topic
  • Applications:
  • Featured Technologies:

Supermicro’s JumpStart remote test site will soon let you try out a server powered by the new 5th Gen AMD EPYC processors from any location you choose.

The server is the Supermicro H14 2U Hyper with dual AMD EPYC 9965 processors. It will be available for remote testing on the Supermicro JumpStart site starting on Dec. 2. Registration is open now.

The JumpStart site lets you use a Supermicro server solution online to validate, test and benchmark your own workloads, or those of your customers. And using JumpStart is free.

All test systems on JumpStart are fully configured with SSH (the Secure Socket Shell network protocol); VNC (Virtual Network Computing remote-access software); and Web IPMI (the Intelligent Platform Management Interface). During your test, you can open one session of each.

Using the Supermicro JumpStart remote testing site is simple:

Step 1: Select the system you want to test, and the time slot when you want to test it.

Step 2: At the scheduled time, login to the JumpStart site using your Supermicro single sign-on (SSO) account. If you don’t have an account yet, create one and then use it to login to JumpStart. (Creating an account is free.)

Step 3: Use the JumpStart site to validate, test and benchmark your workloads!

Rest assured, Supermicro will protect your privacy. Once you’re done testing a system on JumpStart, Supermicro will manually erase the server, reflash the BIOS and firmware, and re-install the OS with new credentials.

Hyper power

The AMD-powered server recently added to JumpStart is the Supermicro H14 2U Hyper, model number AS -2126HS-TN. It’s powered by dual AMD EPYC 9965 processors. Each of these CPUs offers 192 cores and a maximum boost clock of 3.7 GHz.

This Supermicro server also features 3.8TB of storage and 1.5TB of memory. The system is built in the 2U rackmount form factor.

Are you eager to test this Supermicro server powered by the latest AMD EPYC CPUs? JumpStart is here to help you.

Do More:

 

Featured videos

Events


Find AMD & Supermicro Elsewhere

Related Content

Pages