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Manage Your HPC Resources with Supermicro's SuperCloud Composer

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Manage Your HPC Resources with Supermicro's SuperCloud Composer

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  • GigaIO

Today’s data center has numerous challenges: provisioning hardware and cloud workloads, balancing the needs of performance-intensive applications across compute, storage and network resources, and having a consistent monitoring and analytics framework to feed intelligent systems management. Plus, you may have the need to deploy or re-deploy all these resources as needs shift, moment to moment.

Supermicro has created its own tool to assist with these decisions to monitor and manage this broad IT portfolio, called the SuperCloud Composer (SCC). It combines a standardized web-based interface using an Open Distributed Infrastructure Management interface with a unified dashboard based on the RedFish message bus and service agents.

SCC can track the various resources and assign them to different pools with its own predictive analytics and telemetry. It delivers a single intelligent management solution that covers both existing on-premises IT equipment as well as a more software-defined cloud collection. Additional details can be found in this SuperCloud Composer white paper.

SuperCloud Composer makes the use of a cluster-level PCIe network using the FabreX software from GigaIO Networks. It has the capability to flexibly scale up and out storage systems while using the lowest latency paths available.

It also supports Weka.IO cluster members, which can be deployed across multiple systems simultaneously. See our story The Perfect Combination: The Weka Next-Gen File System, Supermicro A+ Servers and AMD EPYC™ CPUs.

SCC can create automated installation playbooks in Ansible, including a software boot image repository that can quickly deploy new images across the server infrastructure. It has a fast-deploy feature that allows a new image to be deployed within seconds.

SuperCloud Composer offers a robust analytics engine that collects historical and up-to-date analytics stored in an indexed database within its framework. This data can produce a variety of charts, graphs and tables so that users can better visualize what is happening with their server resources. Each end-user is provided with analytic capable charting represented by IOPS, network, telemetry, thermal, power, composed node status, storage allocation and system status.

Last but not least, SCC also has both network provisioning and storage fabric provisioning features where build plans are pushed to data or fabric switches either as single-threaded or multithreaded operations, such that multiple switches can be updated simultaneously by shared or unique build plan templates.

For more information, watch this short SCC explainer video. Or schedule an online demo of SCC and request a free 90-day trial of the software.

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Supermicro Debuts New H13 Server Solutions Using AMD’s 4th-Gen EPYC™ CPUs

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Supermicro Debuts New H13 Server Solutions Using AMD’s 4th-Gen EPYC™ CPUs

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Last week, Supermicro announced its new H13 A+ server solutions, featuring the latest fourth-generation AMD EPYC™ processors. The new AMD “Genoa”-class Supermicro A+ configurations will be able to handle up to 96 Zen4 CPU cores running up to 6TB of 12-channel DDR5 memory, using a separate channel for each stick of memory.

The various systems are designed to support the highest performance-intensive computing workloads over a wide range of storage, networking and I/O configuration options. They also feature tool-less chassis and hot-swappable modules for easier access to internal parts as well as I/O drive trays on both front and rear panels. All the new equipment can handle a range of power conditions, including 120 to 480 AC volt operation and 48 DC power attachments.

The new H13 systems have been optimized for AI, machine learning and complex calculation tasks for data analytics and other kinds of HPC applications. Supermicro’s 4th-Gen AMD EPYC™ systems employ the latest PCIe 5.0 connectivity throughout their layouts to speed data flows and provide high network and cluster internetworking performance. At the heart of these systems is the AMD EPYC™ 9004 series CPUs, which were also announced last week.

The Supermicro H13 GrandTwin® systems can handle up to six SATA3 or NVMe drive bays, which are hot-pluggable. The H13 CloudDC systems come in 1U and 2U chassis that are designed for cloud-based workloads and data centers that can handle up to 12 hot-swappable drive bays and support the Open Compute Platform I/O modules. Supermicro has also announced its H13 Hyper configuration for dual-socketed systems. All of the twin-socket server configurations support 160 PCIe 5.0 data lanes.

There are several GPU-intensive configurations for another series of both 4U and 8U sized servers that can support up to 10 GPU PCIe accelerator cards, including the latest graphic processors from AMD and Nvidia. The 4U family of servers support both AMD Infinity Fabric Link and NVIDIA NVLink Bridge technologies so users can choose the right balance of computation, acceleration, I/O and local storage specifications.

To get a deep dive on H13 products, including speeds, feeds and specs, download this whitepaper from the Supermicro site: Supermicro H13 Servers Enable High-Performance Data Centers.

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How the New EPYC CPUs Deliver System-on-Chip Electronics

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How the New EPYC CPUs Deliver System-on-Chip Electronics

CPU chipsets are not normally considered systems-on-chip (SoC) but the fourth generation of AMD EPYC processors incorporate numerous I/O functionality at a high level of integration.

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Typically, CPU chipsets are not normally considered systems-on-chip (SoC) but the fourth generation of AMD EPYC processors incorporate numerous I/O functionality at a high level of integration. Previous generations have delivered this functionality on external chipsets. The SoC design helps reduce power consumption, packaging costs and improve data throughput by reducing interconnection latencies.
 
The new EPYC processors have 12 DDR5 memory controllers – 50 percent more controllers than any other x86 CPU, which keeps up the higher memory demands of performance-intensive computing applications. As we mentioned in an earlier blog, these controllers also include inline encryption engines for supporting AMD’s Infinity Guard features, including support for an integrated security processor that establishes a secure root of trust and other security tasks.
 
They also include 128 or 160 lanes of PCIe Gen5 controllers, which also helps with higher I/O throughput of these more demanding applications. These support the same physical interfaces for Infinity fabric connectors and provide more remote memory access among CPUs at up to 36 GBps between servers. The new Zen 4 CPU cores can make use of one or two interfaces.
 
The PCIe Gen 5 I/O is supported in the I/O die with eight serializer/deserializer silicon controllers with one independent set of traces to support each port of 16 PCIe lanes.
 
 

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AMD’s Infinity Guard Selected by Google Cloud for Confidential Computing

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AMD’s Infinity Guard Selected by Google Cloud for Confidential Computing

Google Cloud has been working over the past several years with AMD on developing new on-chip security protocols. More on the release of the AMD EPYC™ 9004 series processors in this part three of a four-part series..

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Google Cloud has been working over the past several years with AMD on developing new on-chip security protocols that have seen further innovation with the release of the AMD EPYC™ 9004 series processors. These have a direct benefit for performance-intensive computing applications, particularly for supporting higher-density virtual machines (VMs) and using technologies that can protect data flows from leaving the confines of what Google calls confidential VMs as well as further isolating VM hypervisors. They offer a collection of N2D and C2D instances that support these confidential VMs.
 
“Product security is always our top focus,” said AMD CTO Mark Papermaster. “We are continuously investing and collaborating in the security of these technologies.” 
 
Royal Hansen, VP of engineering for Google Cloud said: “Our customers expect the most trustworthy computing experience on the planet. Google and AMD have a long history and a variety of relationships with the deepest experts on security and chip development. This was at the core of our going to market with AMD’s security solutions for datacenters.”
 
The two companies also worked together on this security analysis.
 
Called Infinity Guard collectively, the security technologies theyv'e been working on involve four initiatives:
 
1. Secure encrypted virtualization provides each VM with its own unique encryption key known only to the processor.
 
2. Secure nested paging complements this virtualization to protect each VM from any malicious hypervisor attacks and provide for an isolated and trusted environment.
 
3. AMD’s secure boot along with the Trusted Platform Module attestation of the confidential VMs happen every time a VM boots, ensuring its integrity and to mitigate any persistent threats.
 
4. AMD’s secure memory encryption and integration into the memory channels speed performance.
 
These technologies are combined and communicate using the AMD Infinity Fabric pathways to deliver breakthrough performance along with better secure communications.
 

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Understanding the New Core Architecture of the AMD EPYC 9004 Series Processors

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Understanding the New Core Architecture of the AMD EPYC 9004 Series Processors

AMD’s announcement of its fourth generation EPYC 9004 Series processors includes major advances in how these chipsets are designed and produced. Part 2 of 4.

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AMD’s announcement of its fourth generation EPYC 9004 Series processors includes major advances in how these chipsets are designed and produced for delivering the highest performance levels. These advances involve using a hybrid multi-die architecture.
 
This architecture makes use of two different production processes for cores and I/O pathways. The former makes use of five nanometer dies, while the latter uses six nanometer dies. Each processor package can have up to 12 CPU dies, each with eight 8 cores for a total of 96 cores in the maximum configuration. Each eight-core assembly has its own set of eight 8 dedicated 1 MB L2 caches, and the overall assembly can access a shared 32 MB L3 cache, as shown in the diagram below.
 
32 MB L3 cache image
 
 
 
 
 
 
 
 
 
 
 
In addition to these changes, AMD announced improvements called Zen 4 that involve boosting instructions-per-clock counts and overall clock- speed increases. AMD promises roughly 29 percent faster single-core CPU performance in Zen 4 relative to Zen 3, which were affirmed with Ars Technica’s tests earlier this fall. (Zen 3 chips used the older seven 7 nanometer dies.)
 
 
This configuration provides a great deal of flexibility in how the CPU, memory channels, and I/O paths are arranged. The multi-die setup can reduce fabrication waste and offer better parallel processing support. In addition, AMD EPYC processors are produced in single and dual socket configurations, with the latter offering more I/O pathways and dedicated PCIe generation 5 I/O connections.
 

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AMD Announces Fourth-Generation EPYC™ CPUs with the 9004 Series Processors

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AMD Announces Fourth-Generation EPYC™ CPUs with the 9004 Series Processors

AMD announces its fourth-generation EPYC™ CPUs. The new EPYC 9004 Series processors demonstrate advances in hybrid, multi-die architecture by decoupling core and I/O processes. Part 1 of 4.

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AMD very recently announced its fourth-generation EPYC™ CPUs.This generation will provide innovative solutions that can satisfy the most demanding performance-intensive computing requirements for cloud computing, AI and highly parallelized data analytic applications. The design decisions AMD made on this processor generation strirke a good balance among specificaitons, including higher CPU power and I/O performance, latency reductions and improvements in overall data throughput. This lets a single CPU socket address an increasingly larger world of complex workloads. 
 
The new AMD EPYC™ 9004 Series processors demonstrate advances in hybrid, multi-die architecture by decoupling core and I/O processes. The new chip dies support 12 DDR5 memory channels, doubling the I/O throughput of previous generations. The new CPUs also increase core counts from 64 cores in the previous EPYC 7003 chips to 96 cores in the new chips using 5-nanometer processes. The new generation of chips also increases the maximum memory capacity from 4TB of DDR4-3200 to 6TB of DDR5-4800 memory.
 
 
 
There are three major innovations evident in the AMD EPYC™ 9004 processor series:
  1. A  new hybrid multi-die chip architecture coupled with multi-processor server innovations and a new and more advanced Zen 4 instruction set along with support for an increase in dedicated L2 and shared L3 cache storage
  2. Security enhancements to AMD’s Infinity Guard
  3. Advances to system-on-chip designs that extend and enhance AMD Infinity switching fabric technology,
Taken together, the new AMD EPYC™ 9004 series processors can offer plenty of innovation and performance advantage. The new processors offer better performance per watt of power consumed and better per core performance, too.
 

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

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

Join Supermicro online Nov. 10th to watch the unveiling of the company’s new A+ systems -- featuring next-generation AMD EPYC™ processors. They can't tell us any more right now. But you can register for a link to the event by scrolling down and signing-up on this page.
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The Perfect Combination: The Weka Next-Gen File System, Supermicro A+ Servers and AMD EPYC™ CPUs

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

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

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

 

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

 

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

 

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

 

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

 

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

 

 

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

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

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

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

 

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

 

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


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

 

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


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

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Fast Supermicro A+ Servers with Dual AMD EPYC™ CPUs Support Scientific Research in Hungary

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Fast Supermicro A+ Servers with Dual AMD EPYC™ CPUs Support Scientific Research in Hungary

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The Budapest Institute for Computer Science and Control (known as SZTAKI) conducts a wide range of scientific research spanning the fields of physics, computer science, industrial controls and intelligent systems. The work involves medical image processing, autonomous vehicles, robotics and natural language processing, all areas that place heavy demands on computing equipment and a natural use case for performance-intensive computing.


SZTAKI has been in operation since 1964 and has more than 300 full-time staff, with more than 70 of them holding science-related degrees. It works with both government and other academic institutions jointly on research projects as well as contract research and development of custom computer-based applications.

The institute also coordinates similar types of work done at Hungary’s AI national lab. For example, there are several projects underway to develop AI-based solutions to process the Hungarian language and build computational-based models that can be more effective and not require as much training as earlier models. They are also working on creating more transparent and explainable machine learning models to make them more reliable and more resilient in preserving data privacy.

SZTAKI has been using Supermicro’s A+ 4124GO-NART servers with GPUs that are configured with two AMD EPYC™ 7F72 CPUs. “Our researchers are now able to advance our use of AI and focus on more advanced research," said Andras Benczur, scientific director at the AI lab. One challenges they face is keeping up with the advanced algorithms that its researchers have developed. Having the Supermicro servers, which operate at 20x the speed of previous servers, means that researchers can execute coding and modeling decisions far more quickly.

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