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To make room for AI, modernize your data center

A new report finds the latest AMD-powered Supermicro servers can modernize the data center, lowering TCO and making room for AI systems.

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Did you know that dramatic improvements in processor power can enable your corporate customers to lower their total cost of ownership (TCO) by consolidate servers and modernizing their data centers?

Server consolidation is a hot topic in the context of AI. Many data centers are full and running with all the power that’s available. So how can they make room for new AI systems? Also, how can they get the kind of power that today’s AI systems require?

One answer: with consolidation. 

Four in One

All this is especially relevant in light of a new report from Principled Technologies.

The report, prepared for AMD, finds that an organization that upgrades to new Supermicro servers powered by the current 5th generation AMD EPYC processors can consolidate servers on a 4:1 ratio.

In other words, the level of performance that previously required four older servers can now be delivered with just one.

Further, Principled found that organizations that make this upgrade can also free up data-center space; lower operating costs by up to $2.8 million over five years; shrink power-consumption levels; and reduce the maintenance load on sys admins.

Testing Procedures

Here’s how Principled figured all this out. To start, they obtained two systems:

Next, Principled’s researchers compared the transactional database performance of the two servers. They did this with HammerDB TPROC-C, an open-source benchmarking tool for online transaction processing (OLTP) workloads.

To ensure the systems were sufficiently loaded, Principled also measured both servers’ CPU and power utilization rates, pushing both servers to 80% CPU core utilization.

Then Principled calculated a consolidation ratio. That is, how many of the older servers would be needed to do the same level of work done by just 1 new server?

Finally, Principled calculated the expected 5-year costs for software licensing, power, space and maintenance. These calculations were made for both the older and new Supermicro servers, so they could be compared.

The Results

So what did Principled find? Here are the key results:

  • Performance upgrades: The new servers, based on AMD 5th Gen EPYC processors, is much more powerful. To match the database performance of just 1 new server, the testers required 4 of the older servers.
  • Lower operating costs: Consolidating those four older servers onto just one new server could lower an organization’s TCO by over 60%, saving up to an estimated $2.8 million over five years. The estimated 5-year TCO for the legacy server was $4.68 million, compared with $1.78 million for the new system.
  • Lower software license costs: Much of the savings would come from consolidating software licenses. They’re typically charged on a per-core basis, and the new test server needed only about a third as many cores as did the four older systems: 96 cores on the new system, compared with a total of 256 cores on the four older servers.
  • Reduced power consumption: To run the same benchmark, the new system needed only about 40% of the power required by the four older servers.
  • Lower space and cooling requirements: Space savings were calculated by comparing data-center footprint costs, taking into account the 4:1 consolidation and rack space needed. Cooling costs were factored in, too. The savings here were pretty dramatic, even if the figures were relatively low. The new system’s space costs were just $476, or 75% lower than the legacy system’s cost of $1,904.
  • Reduced maintenance costs: This was estimated with the assumption that one full-time sys admin with an annual salary of roughly $100K is responsible for 100 servers. The savings here brought a cost of over $26K for the older setup down to about $6,500 for the new, for a reduction of 75%.

Implicit in the results, though not actually calculated, is the way these reductions could also free up funding, floor space and other resources that organizations can then use for new AI systems.

So if your customers are grappling with finding new resources for AI, tell them about these test results. Upgrading to servers based on the latest processors could be the answer.

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AI across AMD’s entire portfolio? Believe it!

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AI across AMD’s entire portfolio? Believe it!

A little over a year ago, AMD CTO Mark Papermaster said the company’s strategy was to offer AI everywhere. Now learn how AMD, with help from Supermicro, is bringing this strategy to life.

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A year in the fast-moving world of artificial intelligence can seem like a lifetime.

Consider:

  • A year ago, ChatGPT had fewer than 200 million weekly active users. Now this Generative AI tool has 400 million weekly users, according to developer OpenAI.
  • A year ago, no one outside of China had heard of DeepSeek. Now its GenAI chatbot is disrupting the AI industry, challenging the way some mainstream tools function.
  • About a year ago, AMD CTO Mark Papermaster said his company’s new strategy called for AI across the entire product portfolio. Now AMD, with help from Supermicro, offers AI power for the data center, cloud and desktop. AMD also offers a robust open AI stack.

‘We’re Thrilled’

AMD’s Papermaster made his comments in Feb. 2024 during a fireside chat hosted by stock research firm Arete Research.

During the interview, CTO Papermaster acknowledged that most early customers for AMD’s AI hardware were mostly big cloud hyperscalers, including AWS, Google Cloud and Microsoft Azure. But he also said new customers are coming, including both enterprises and individual endpoint users.

“We’re thrilled to bring AI across our entire portfolio,” Papermaster said.                                                                          

So how has AMD done? According to the company’s financial results for both the fourth quarter and the full year 2024, pretty good.

Aggressive Investments

During AMD’s recent report on its Q4:24 and full-year ’24 financial results, CFO Jean Hu mentioned that the company is “investing aggressively in AI.” She wasn’t kidding, as the following items show:

  • AMD is accelerating its AI software road map. The company released ROCm 6.3, which includes enhancements for faster AI inferencing on AMD Instinct GPUs. The company also shared an update on its plans for the ROCm software stack.
  • AMD announced a new GPU system in 2024, the AMD Instinct MI325X. Designed for GenAI performance, it’s built on the AMD CDNA3 architecture and offers up to 256GB of HBM3E memory and up to 6TB/sec. of bandwidth.
  • To provide a scalable AI infrastructure, AMD has expanded its partnerships. These partnerships involve companies that include Aleph, IBM, Fujitsu and Vultr. IBM, for one, plans to deploy AMD MI300X GPUs to power GenAI and HPC applications on its cloud offering.
  • AMD is offering AI power for PCs. The company added AI capabilities to its Ryzen line of processors. Dell, among other PC vendors, has agreed to use these AMD CPUs in its Dell Pro notebook and desktop systems.

Supermicro Servers

AMD partner Supermicro is on the AI case, too. The company now offers several AMD-powered servers designed specifically for HPC and AI workloads.

These include an 8U 8-GPU system with AMD Instinct MI300X GPUs. It’s designed to handle some of the largest AI and GenAI models.

There’s also a Supermicro liquid-cooled 2U 4-way server. This system is powered by the AMD Instinct MI300A, which combines CPUs and GPUs, and it’s designed to support workloads that coverge HPC and AI.

Put it all together, and you can see how AMD is implementing AI across its entire portfolio.

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Tech Explainer: What is edge computing — and why does it matter?

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Tech Explainer: What is edge computing — and why does it matter?

Edge computing, once exotic, is now a core aspect of modern IT infrastructures. 

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Edge computing is a vital aspect of our modern IT infrastructure. Its use can reduce latency, minimize bandwidth usage, and shorten response times.

This distributed computing methodology enables organizations to process data closer to its source and make decisions faster. This is referred to as operating at the edge.

For contrast, you can compare this with operating at the core, which refers to data being sent to centralized data centers and cloud environments for processing.

The edge is also a big and fast-growing business. Last year, global spending on edge computing rose by 14%, totaling $228 billion, according to market watcher IDC.

Looking ahead, IDC predicts this spend will increase to $378 billion by 2028, for a five-year compound annual growth rate (CAGR) of nearly 18%. Driving this growth will be high demand for real-time analytics, automation and enhanced customer experiences.

How does edge computing work?

Fundamentally, edge computing operates pretty much the same way that other types of computing do. The big difference is the location of the computing infrastructure relative to devices that collect the data.

For instance, a telecommunications provider like Verizon operates at the edge to better serve its customers. Rather than sending customer data to a central location, a telco can process it closer to the source.

An edge node’s proximity to end users can dramatically reduce the time it takes to transfer information to and from each user. This time is referred to as latency. And moving computing to the edge can reduce it. Edge computing can also lower data-error rates and demand for costly data-center space.

For a telco application of edge computing, the flow of data would look something like this:

1.   Users working with their smartphones, PCs and other devices create and request data. Because this happens in their homes, offices or anywhere else they happen to be, the data is said to have been created at the edge.

2.   Next, this customer data is processed by what are known as edge nodes. These are edge computing infrastructure devices placed near primary data sources.

3.   Next, the edge nodes filter the user data with algorithms and AI-enabled processing. Then the nodes send to the cloud only the most relevant data. This helps reduce bandwidth usage and costs.

Edge is Everywhere

Many verticals now rely on edge computing to increase efficiency and better serve their customers. These include energy providers, game developers and IoT appliance manufacturers.

One big vertical for the edge is retail, where major brands rely on edge computing to collect data from shoppers in real time. This helps retailers manage their stock, identify new sales opportunities, reduce shrinkage (that is, theft), and offer unique deals to their customers.

Other areas for the edge include “smart roads.” Here, roadside sensors are used to collect and process data locally to assess traffic conditions and maintenance. In addition, the reduced latency and hyper-locality provided by edge computing can speed communications, paring precious seconds when first responders are called to the scene of an accident.

Inner Workings

Like most modern computers, edge nodes rely on a laundry list of digital components. At the top of that list is a processor like the AMD EPYC Embedded 9004 and 8004 series.

AMD’s latest embedded processors are designed to balance performance and efficiency. The company’s ‘Zen 4’ and ‘Zen 4c’ 5-nanometer core architecture is optimized for always-on embedded systems. And with up to 96 cores operating as fast as 4.15 GHz, these processors can handle the AI-heavy workloads increasingly common to edge computing.

Zoom out from the smallest component to the largest, and you’re likely to find a density- and power-optimized edge platform like the Supermicro H13 WIO.

Systems like these are designed specifically for edge operations. Powered by either AC or DC current for maximum flexibility, the H13 WIO can operate at a scant 80 watts TDP. Yet to handle the most resource-intensive applications, it can scale up to 64 cores.

Getting Edgier

The near future of edge computing promises to be fascinating. As more users sign up for new services, enterprises will have to expand their edge networks to keep up with demand.

What tools will they use? To find out, see the latest edge tech from AMD and Supermicro at this year’s MWC, which kicks off in Barcelona, Spain, on March 3.

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

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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.

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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.

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Tech Explainer: CPUs and GPUs for AI training and inferencing

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Tech Explainer: CPUs and GPUs for AI training and inferencing

Which is best for AI – a CPU or a GPU? Like much in life, it depends.

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While central processing units and graphics processing units serve different roles in AI training and inferencing, both roles are vital to AI workloads.

CPUs and GPUs were both invented long before the AI era. But each has found new purpose as the robots conduct more of our day-to-day business.

Each has its tradeoffs. Most CPUs are less expensive than GPUs, and they typically require less electric power. But that doesn’t mean CPUs are always the best choice for AI workloads. Like lots of things in life, it depends.

Two Steps to AI

A typical AI application involves a two-step process. First training. Then inferencing.

Before an AI model can be deployed, it must be trained. That could include suggesting which movie to watch next on Netflix or detecting fake currency in a retail environment.

Once the AI model has been deployed, it can begin the inferencing process. In this stage, the AI application interfaces with users, devices and other models. Then it autonomously makes predictions and decisions based on new input.

For example, Netflix’s recommendation engine is powered by an AI model. The AI was first trained to consider your watching history and stated preferences, as well as to review newly available content. Then the AI employs inferencing—what we might call reasoning—to suggest a new movie or TV show you’re likely to enjoy.

AI Training

GPU architectures like those found in the AMD Instinct MI325X accelerator offers highly parallel processing. In other words, a GPU can perform many calculations simultaneously.

The AMD Instinct MI325X has more than 300 GPU compute units. They make the accelerator faster and more adept at both processing large datasets and handling the repetitious numerical operations common to the training process.

These capabilities also mean GPUs can accelerate the training process. That’s especially true for large models, such as those that underpin the networks used for deep learning.

CPUs, by contrast, excel at general-purpose tasks. Compared with a GPU, a CPU will be better at completing sequential tasks that require logic or decision-making. For this reason, a CPU’s role in AI training is mostly limited to data preprocessing and coordinating GPU tasks.

AI Inferencing

However, when it comes to AI inferencing, CPUs play a much more significant role. Often, inferencing can be a relatively lightweight workload, because it’s not highly parallel. A good example is the AI capability present in modern edge devices such as the latest iOS and Android smartphones.

As mentioned above, the average CPU also consumes less power than a GPU. That makes a CPU a better choice in situations where heat and battery life are important.

However, not all inferencing applications are lightweight, and such workloads may not be appropriate for CPUs. One example is autonomous vehicles. They will require massive parallel processing in real-time to ensure safety and optimum efficiency.

In these cases, GPUs will play a bigger role in the AI inferencing process, despite their higher cost and power requirements.

Powerful GPUs are already used for AI inferencing at the core. Examples include large-scale cloud services such as AWS, Google Cloud and Microsoft Azure.

Enterprise Grade

Enterprises often conduct AI training and inferencing on a scale so massive, it eclipses those found in edge environments. In these cases, IT engineers must rely on hugely powerful systems.

One example is the Supermicro AS -8125GS-TNMR2 server. This 8U behemoth—weighing in at 225 pounds—can operate up to eight AMD Instinct MI300X accelerators. And it’s equipped with dual AMD EPYC processors, the customer’s choice of either the 9004 or 9005 series.

To handle some of the world’s most demanding AI workloads, Supermicro’s server is packed with an astonishing amount of tech. In addition to its eight GPUs, the server also has room for a pair of AMD EPYC 9005-series processors, 6TB of ECC DDR5 memory, and 18 hot-swap 2.5-inch NVMe and SATA drives.

That makes the Supermicro system one of the most capable and powerful servers now available. And as AI evolves, tech leaders including AMD and Supermicro will undoubtedly produce more powerful CPUs, GPUs and servers to meet the growing demand.

What will the next generation of AI training and inferencing technology look like? To find out, you won’t have to wait long.

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2024: A look back at the year’s best

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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.

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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.

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Faster is better. Supermicro with 5th Gen AMD is faster

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Faster is better. Supermicro with 5th Gen AMD is faster

Supermicro servers powered by the latest AMD processors are up to 9 times faster than a previous generation, according to a recent benchmark.

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When it comes to servers, faster is just about always better.

With faster processors, workloads get completed in less time. End users get their questions answered sooner. Demanding high-performance computing (HPC) and AI applications run more smoothly. And multiple servers get all their jobs done more rapidly.

And if you’ve installed, set up or managed one of these faster systems, you’ll look pretty smart.

That’s why the latest benchmark results from Supermicro are so impressive, and also so important.

The tests show that Supermicro servers powered by the latest AMD processors are up to 9 times faster than a previous generation. These systems can make your customer happy—and make you look good.

SPEC Check

The benchmark in question are those of the Standard Performance Evaluation Corp., better known as SPEC. It’s a nonprofit consortium that sets benchmarks for running complete applications.

Supermicro ran its servers on SPEC’s CPU 2017 benchmark, a suite of 43 benchmarks that measures and compare compute-intensive performance. All of them stress a system’s CPU, memory subsystem and compiler—emphasizing all three of these components working together, not just the processor.

To provide a comparative measure of integer and floating-point compute-intensive performance, the benchmark uses two main metrics. The first is speed, or how much time a server needs to complete a single task. The second is throughput, in which the server runs multiple concurrent copies.

The results are given as comparative scores. In general, higher is better.

Super Server

The server tested was the Supermicro H14 Hyper server, model number AS 2126HS-TN. It’s powered by dual AMD EPYC 9965 processors and loaded with 1.5TB of memory.

This server has been designed for applications that include HPC, cloud computing, AI inferencing and machine learning.

In the floating-point measure, the new server, when compared with a SMC server powered by an earlier-gen AMD EPYC 7601, was 8x faster.

In the Integer Rate measure, compared with a circa 2018 SMC server, it’s almost 9x faster.

Impressive results. And remember, when it comes to servers, faster is better.

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Tech Explainer: Why does PCIe 5.0 matter? And what’s coming next?

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Tech Explainer: Why does PCIe 5.0 matter? And what’s coming next?

PCIe 5.0 connects high-speed components to servers and PCs. Versions 6 & 7, coming soon, will deliver even higher speeds for tomorrow’s AI workloads.

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You’ve no doubt heard of PCIe 5.0. But what is it exactly? And why does it matter?

As the name and number imply, PCIe 5.0 is the fifth generation of the Peripheral Component Interconnect Express interface standard. PCIe essentially sets the rules for connecting high-speed components such as GPUs, networking cards and storage devices to servers, desktop PCs and other devices.

To be sure, these components could be connected via a number of other interface standards, such as USB-C and SATA.

But PCIe 5.0 alone offers extremely high bandwidth and low latency. That makes it a better choice for mission-critical enterprise IT operations and resource-intensive AI workloads.

Left in the Dust

The 5th generation of PCIe was released in May 2019, bringing significant improvements over PCIe 4.0. These include:

  • Increased Bandwidth. PCIe 5.0 has a maximum throughput of 32 giga-transfers per second (GT/s)—effectively double the bandwidth of its predecessor. In terms of data transfer, 32 GT/s translates to around 4 GB of data throughput per lane in each direction. That allows for a total of 64 GB/s in a 16-lane PCIe-based GPU. That’s perfect for modern GPU-dependent workflows such as AI-inferencing.
  • Lower Latency. Keeping latency as low as possible is crucial for applications like gaming, high-performance computing (HPC) and AI workloads. High latency can inhibit data retrieval and processing, which in turn hurts both application performance and the user experience. The latency of PCIe 5.0 varies depending on multiple factors, including network connectivity, attached devices and workloads. But it’s safe to assume an average latency of around 100 nanoseconds (ns) — roughly 50% less than PCIe 4.0. And again, with latency, lower is better.
  • Enhanced Data-Center Features. Modern data-center operations are among the most demanding. That’s especially true for IT operations focused on GenAI, machine learning and telecom. So it’s no surprise that PCIe 5.0 includes several features focused on enhanced operations for data centers. Among the most notable is increased bandwidth and faster data access for NVMe storage devices. PCIe 5.0 also includes features that enhance power management and efficiency.

Leveraging PCIe 5

AMD is a front-runner in the race to help enterprises cope with modern AI workloads. And the company has been quick to take advantage of PCIe 5.0’s performance improvements. Take, for example, the AMD Instinct MI325X Accelerator.

This system is a leading-edge accelerator module for generative AI, inference, training and HPC. Each discrete AMD Instinct MI325X offers a 16-lane PCIe Gen 5 host interface and seven AMD Infinity Fabric links for full connectivity between eight GPUs in a ring.

By leveraging a PCIe 5.0 connection, AMD’s accelerator can offer I/O-to-host-CPU and scale-out network bandwidths of 128 GB/sec.

AMD is also using PCIe on its server processors. The new 5th generation AMD EPYC server processors take advantage of PCIe 5.0’s impressive facility. Specifically, the AMD EPYC 9005 Series processors support 128 PCIe 5 I/O lanes in a single-socket server. For dual-socket servers, support increases to 160 lanes.

Supermicro is another powerful force in enterprise IT operations. The company’s behemoth H14 8-GPU system (model number AS-8126GS-TNMR2) leverages AMD EPYC processors and AMD Instinct accelerators to help enterprises deploy the largest AI and large language models (LLMs).

The H14’s standard configuration includes eight PCIe 5.0 x16 low-profile slots and two full-height slots. Users can also opt for a PCIe expansion kit, which adds two additional PCIe 5.0 slots. That brings the grand total to an impressive 12 PCIe 5.0 16-lane expansion slots.

PCIe 6.0 and Beyond

PCIe 5.0 is now entering its sixth year of service. That’s not a long time in the grand scheme of things. But the current version might feel ancient to IT staff who need to eke out every shred of bandwidth to support modern AI workloads.

Fortunately, a new PCIe generation is in the works. The PCIe 6.0 specification, currently undergoing testing and development, will offer still more performance gains over its predecessor.

PCI-SIG, an organization committed to developing and enhancing the PCI standard, says the 6.0 platform’s upgrades will include:

  • A data rate of up to 64 GT/sec., double the current rate and providing a maximum bidirectional bandwidth of up to 256 GB/sec for x16 lanes
  • Pulse Amplitude Modulation with 4 levels (PAM4)
  • Lightweight Forward Error Correct (FEC) and Cyclic Redundancy Check (CRC) to mitigate the bit error rate increase associated with PAM4 signaling
  • Backwards compatibility with all previous generations of PCIe technology

There’s even a next generation after that, PCIe 7.0. This version could be released as soon as 2027, according to the PCI-SIG. That kind of speed makes sense considering the feverish rate at which new technology is being developed to enable and expand AI operations.

It’s not yet clear how accurate those release dates are. But one thing’s for sure: You won’t have to wait long to find out.

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

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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.

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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.

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Supermicro FlexTwin now supports 5th gen AMD EPYC CPUs

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Supermicro FlexTwin now supports 5th gen AMD EPYC CPUs

FlexTwin, part of Supermicro’s H14 server line, now supports the latest AMD EPYC processors — and keeps things chill with liquid cooling.

 

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Wondering about the server of the future? It’s available for order now from Supermicro.

The company recently added support for the latest 5th Gen AMD EPYC 9005 Series processors on its 2U 4-node FlexTwin server with liquid cooling.

This server is part of Supermicro’s H14 line and bears the model number AS -2126FT-HE-LCC. It’s a high-performance, hot-swappable and high-density compute system.

Intended users include oil & gas companies, climate and weather modelers, manufacturers, scientific researchers and research labs. In short, anyone who requires high-performance computing (HPC).

Each 2U system comprises four nodes. And each node, in turn, is powered by a pair of 5th Gen AMD EPYC 9005 processors. (The previous-gen AMD EPYC 9004 processors are supported, too.)

Memory on this Supermicro FlexTwin maxes out at 9TB of DDR5, courtesy of up to 24 DIMM slots. Expansions connect via PCIe 5.0, with one slot per node the standard and more available as an option.

The 5th Gen AMD EPYC processors, introduced last month, are designed for data center, AI and cloud customers. The series launched with over 25 SKUs offering up to 192 cores and all using AMD’s new “Zen 5” or “Zen 5c” architectures.

Keeping Cool

To keep things chill, the Supermicro FlexTwin server is available with liquid cooling only. This allows the server to be used for HPC, electronic design automation (EDA) and other demanding workloads.

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

The server’s liquid cooling also covers the 5th gen AMD processors’ more demanding cooling requirements; they’re rated at up to 500W of thermal design power (TDP). By comparison, some members of the previous, 4th gen AMD EPYC processors have a default TDP as low as 200W.

Build & Recycle

The Supermicro FlexTwin server also adheres to the company’s “Building Block Solutions” approach. Essentially, this means end users purchase these servers by the rack.

Supermicro says its Building Blocks let users optimize for their exact workload. Users also gain efficient upgrading and scaling.

Looking even further into the future, once these servers are ready for an upgrade, they can be recycled through the Supermicro recycling program.

In Europe, Supermicro follows the EU’s Waste Electrical and Electronic Equipment (WEEE) Directive. In the U.S., recycling is free in California; users in other states may have to pay a shipping charge.

Put it all together, and you’ve got a server of the future, available to order today.

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