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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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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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Red Hat’s OpenShift Runs More Efficiently with Supermicro’s SuperBlade® Servers

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Red Hat’s OpenShift Runs More Efficiently with Supermicro’s SuperBlade® Servers

The Supermicro SuperBlade's advantage for the Red Hat OCP environment is that it supports a higher-density infrastructure and lower-latency network configuration, along with benefits from reduced cabling, power and shared cooling features. SuperBlades feature multiple AMD EPYC™ processors using fast DDR4 3200MHz memory modules.

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Red Hat’s OpenShift Container Platform (OCP) provides enterprise Kubernetes-bundled devops pipelines. It automates builds and container deployments and lets developers focus on application logic while leveraging best-of-class enterprise infrastructure.

 

OpenShift supports a broad range of programming languages, web frameworks, databases, connectors to mobile devices and external back ends. OCP supports cloud-native, stateless applications and traditional applications. Because of its flexibility and utility in running advanced applications, OCP has become one of the go-to places that support high-performance computing.

 

Red Hat’s OCP comes in several deployment packages, including as a managed service running on the major cloud platforms, as virtual machines, and on “bare metal” servers, meaning a user installs all the software needed for the platform and is the sole tenant of the server.

 

It’s that last use case in which Supermicro’s SuperBlade servers are especially useful. Their advantage is that they support a higher-density infrastructure and lower-latency network configuration, along with benefits from reduced cabling, power and shared cooling features.

 

The SuperBlade comes in an 8U chassis with room to accommodate up to 20 hot-pluggable nodes (processor, network and storage) in a variety of more than a dozen models that support serial-attached SCSI, ordinary SATA drives, and GPU processor modules. It sports multiple AMD EPYC™ processors using fast DDR4 3200MHz memory modules.

A chief advantage of the SuperBlade is that it can support a variety of higher-capacity OCP workload configurations and do so within a single server chassis. This is critical because OCP requires a variety of server roles to deliver its overall functionality, and having these roles working inside of a chassis means performance  and latency benefits. For example, you could partition a SuperBlade’s 20 nodes into various OCP components such as administrative, management, storage, worker, infrastructure and load balancer nodes, all operating within a single chassis. For deeper detail about running OCP on the SuperBlade, check out this Supermicro white paper.

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Build an Accelerated Data Center with AMD's Third-Gen EPYC™ CPUs

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Build an Accelerated Data Center with AMD's Third-Gen EPYC™ CPUs

“AMD EPYC™ processors are now a part of the world’s hyperscale data centers,” said Lisa Su, AMD’s CEO. Meta/Facebook is now building its servers with powerful third-generation AMD EPYC™ CPUs.

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If you're making plans to build a high-performance data center, be sure to take a close look at the latest version of AMD's EPYC™ CPU chipsets, which were code-named “Milan X.”

 

Servers that employ AMD’s third-generation EPYC™ CPUs are so powerful that Meta/Facebook is now building its servers with them, using the new single-socket cloud-scale design, which is a part of their Open Compute Project. “AMD EPYC™ processors are now a part of the world’s hyperscale data centers,” said Lisa Su, AMD’s CEO, in the presentation at which she debuted the processors.

 

This latest generation of AMD EPYC™ CPUs uses an innovative packaging option of 3D stacking of chiplets for high-performance computing applications. Higher density cached memory is stacked on top of the processor to deliver more than 200 times the interconnected density of prior chiplet packaging designs. “It is the most flexible active-on-active silicon technology available in the world,” Su said. “It consumes much less energy and fits into existing CPU sockets, too.” AMD's latest chipsets satisfy the higher demands of cloud computing and electronic circuit design applications.

 

Jason Zander, EVP Microsoft Azure, said that Microsoft's partnership with AMD has let the cloud computing company deliver cloud instances that can run up to 12 times the speed of earlier offerings. “That rivals some supercomputers,” he said. Azure has configured some of the most powerful virtual instances, which are running on the latest AMD EPYC™ processors. They are available from 16 cores up to 120 cores and can share 448 GB of memory and 480 MB of L3 cache among the processors. For deeper information, see this Microsoft blog.

 

Circuit design demands the fastest processors. “The next step for AMD is to deliver more differentiation in value with a focus on performance per core,” said Dan McNamara, general manager of AMD’s Server Business Unit. “In our tests comparing Synopsys VCS chip-design simulation software running on older and newer AMD EPYC™ CPUs, engineers were able to complete 66% more jobs in the same elapsed time, thanks to having a larger L3 cache. This means that more data can be kept closer to the processor for better performance.” These faster product design lifecycles mean faster times to market since designers can save time in the testing process.

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Gain Business Insights Faster by Building the Right Infrastructure for Performance-Intensive Computing

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Gain Business Insights Faster by Building the Right Infrastructure for Performance-Intensive Computing

A white paper from IDC projects a new role for IT leaders in preparing the infrastructure required to properly power performance-intensive computing (PIC) for enterprise workloads, such as data-driven insights, AI/machine learning, big data, modeling and simulation and more. Get the full white paper to learn best practices and avoid pitfalls when implementing performance-intensive computing infrastructure.

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Organizations use data-driven insights to gain competitive advantage over their rivals. Competitive differentiation is often realized through the delivery of new products and services or enhancements to existing products and services. It can also be achieved by streamlining and optimizing business operations. A data-driven business reduces the time needed to realize business advantage by creating an environment conducive to forming business-differentiating insights.

 

As a result, IDC projects that a new chapter in the relationship between IT and the business is about to begin. The new phase will push IT further in a strategic direction, increasing its influence on business outcomes.

 

The trend is expected by IDC to play out over the next four to five years, thrusting IT into a new role implementing a foundational infrastructure designed to foster timely, data-driven insights, at scale. The new infrastructure will be designed to support Performance-Intensive Computing (PIC). Investments in new performance-intensive workloads will be more significant than those used for corporate IT and other business applications.

 

IDC defines performance-intensive computing as the process of performing large-scale, mathematically intensive computations, commonly used in analytics, machine learning and technical computing — and now increasingly required for artificial intelligence and big data and analytics in the commercial space.

 

Performance-intensive computing workloads have evolved at an accelerated pace. An overwhelming majority of respondents in IDC's 2021 IT Enterprise Infrastructure Survey agreed that PIC workloads are important or even critically important to their business.

 

But a general-purpose infrastructure won’t get the job done. Common pitfalls organizations encounter have to do with people, organizational models, business process and access to the technology required to succeed.

 

  • Learn the five areas that organizations need to evaluate when planning to develop their PIC infrastructures.
  • What are the common reasons why PIC projects fail?
  • Find out about performance-intensive solutions from Supermicro and AMD.

 

Get the full IDC white paper: Gaining Deep and Timely Insights with Performance-Intensive Computing Infrastructure.

 

 

 

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Offering Distinct Advantages: The AMD Instinct™ MI210 and MI250 Series GPU Accelerators and Supermicro SuperBlades

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Offering Distinct Advantages: The AMD Instinct™ MI210 and MI250 Series GPU Accelerators and Supermicro SuperBlades

Using six nanometer processes and the CDNA2 graphics dies, AMD has created the third generation of GPU accelerators, which have more than twice the performance of previous GPU processors and deliver 181 teraflops of mixed precision peak computing power.

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AMD and Supermicro have made it easier to exploit the most advanced combination of GPU and CPU technologies.

Derek Bouius, a senior product manager at AMD, said “Using six nanometer processes and the CDNA2 graphics dies, we created the third generation of GPU chipsets that have more than twice the performance of previous GPU processors. They deliver 181 teraflops of mixed precision peak computing power.” Called the AMD Instinct MI210™ and AMD Instinct MI250™, they have twice the memory (64 GB) to work with and deliver data at the rate of 1.6 TB/sec. Both these accelerators are packaged as fourth generation PCIe expansion cards and come with direct connectors to Infinity Fabric bridges for faster I/O throughput between GPU cards -- without having their traffic go through the standard PCIe bus.

The Instinct accelerators have immediate benefit for improving performance in the most complex computational applications, such as molecular dynamics, computer-aided engineering, weather and oil and gas modeling.

"We provided optimized containerized applications that are pre-built to support the accelerator and run them out of the box," Bouius said. “It is a very easy lift to go from existing solutions to the AMD accelerator,” he added. It’s accomplished by bringing together AMD’s ROCm™ support libraries and tools with its HIP programming language and device drivers – all of which are open source. They can unlock the GPU performance enhancements to make it easier for software developers to take advantage of its latest processors. AMD offers a catalog of dozens of currently available applications.

Supermicro’s SuperBlade product line combines the new AMD Instinct™ GPU accelerators and AMD EPYC™ processors to deliver higher performance with lower latency for its enterprise customers.

One packaging option is to combine six chassis with 20 blades each, delivering 120 servers that provide a total of more than 3,000 teraflops of combined processing power. This equipment delivers more power efficiency in less space with fewer cables, providing a lower cost of ownership. The blade servers are all hot-pluggable and come with two onboard front-mounted 25 gigabit and two 10 gigabit Ethernet connectors.

“Everything is faster now for running enterprise workloads,” says Shanthi Adloori, senior director of product management for Supermicro. “This is why our Supermicro servers have won the world record in performance from the Standard Performance Evaluation Corp. three years in row.” Another popular design for the SuperBlade is to provide an entire “private cloud in a box” that combines administration and worker nodes and handles deploying a Red Hat Openshift platform to run Kubernetes-based deployments with minimal provisioning.

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AMD and Supermicro Work Together to Produce the Latest High-Performance Computers

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AMD and Supermicro Work Together to Produce the Latest High-Performance Computers

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Solving some of business’ bigger computing challenges requires a solid partnership between CPU vendor, system builders and channel partners. That is what AMD and Supermicro have brought to the market with the third generation of AMD's EPYC™ processors with AMD 3D V-Cache™ and AMD Instinct™ MI200 series GPU accelerators wrapped up in SuperBlade servers built by Supermicro.

 

“This has immediate benefits for particular fields such as crash and digital circuit simulations and electronic design automation,” said David Weber, Senior Manager for AMD. “It means we can create virtual chips and track workflows and performance before we design and build the silicon." The same situation holds for computational fluid dynamics, he added, "in which we can determine the virtual air and water flows across wings and through water pumps and save a lot of time and money, and the AMD 3D V-Cache™ makes this process a lot faster.” Without any software coding changes, these applications are seeing 50% to 80% performance improvement, Weber said.

 

The chips are not just fast, they come with several built-in security features, including support for Zen 3 and Shadow Stack. Zen 3 is the overall name for a series of improvements to the AMD higher-end CPU line that have shown a 19% improvement in instructions per clock, lower latency for doubled cache delivery when compared to the earlier Zen 2 architecture chips.

 

These processors also support Microsoft’s Hardware-enforced Stack Protection to help detect and thwart control-flow attacks by checking the normal program stack against a secured hardware-stored copy. This helps to boot securely, protect the computer from firmware vulnerabilities, shield the operating system from attacks, and prevent unauthorized access to devices and data with advanced access controls and authentication systems.

 

Supermicro offers its SuperBlade servers that take advantage of all these performance and security improvements. For more information, see this webcast.

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Lawrence Livermore Labs Advances Scientific Research with AMD GPU Accelerators

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Lawrence Livermore Labs Advances Scientific Research with AMD GPU Accelerators

The Lawrence Livermore National Lababoratory chose to use a cluster of 120 servers running AMD EPYC™ processors with nearly 1,000 AMD Instinct™ GPU accelerators. The hardware, facilitated by Supermicro, was an excellent match for the molecular dynamics simulations required for the Lab's cutting-edge research, which combines machine learning with structural biology concepts.

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Lawrence Livermore National Laboratory is one of the centers of high-performance computing (HPC) in the world and it is constantly upgrading its equipment to meet increasing computational demands. It houses one of the world's largest computing environments. Among its more pressing research goals derives from the COVID-19 crisis.

Lawrence Livermore researches and supports proposals from the COVID-19 HPC Consortium, which is composed of more than a dozen research organizations across government, academia and private industry. It aims to accelerate disease detection and treatment efforts, as well as to screen antibody candidates virtually and run several disease-related mathematical simulations.

"By leveraging the massive compute capabilities of the world’s [more] powerful supercomputers, we can help accelerate critical modeling and research to help fight the virus," said Forrest Norrod, senior vice president and general manager, AMD Datacenter and Embedded Systems Group.

The lab chose to use a cluster of 120 servers running AMD EPYC™ processors with nearly 1,000 AMD Instinct™ GPU accelerators. The servers were connected by Mellanox switches. The product choices had two benefits: First, the hardware, facilitated by Supermicro, was an excellent match for the molecular dynamics simulations required for this research. The lab is performing cutting-edge research that combines machine learning with structural biology concepts. Second, the gear was tested and packaged together, so it could become operational when it was delivered to the lab.

AMD software engineers and application specialists were able to modify components to run GPU-based applications. This is top-of-the-line gear. The AMD accelerators deliver up to 13.3 teraFLOPS of single-precision peak floating-point performance combined with 32GB of high-bandwidth memory. The scientists were able to reduce their simulation run-times from seven hours to just 40 minutes, allowing  them to test multiple modeling iterations efficiently.

For more information, see the Supermicro case study and Lawrence Livermore report.

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