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It is sometimes difficult to understand the true value of IBM's Power-based CPUs and associated server platforms. And the company has written a lot about it over the past few years. Even for IT professionals that deploy and manage servers. As an industry, we have become accustomed to using x86 as a baseline for comparison. If an x86 CPU has 64 cores, that becomes what we used to measure relative value in other CPUs.

But this is a flawed way of measuring CPUs and a broken system for measuring server platforms. An x86 core is different than an Arm core which is different than a Power core. While Arm has achieved parity with x86 for some cloud-native workloads, the Power architecture is different. Multi-threading, encryption, AI enablement – many functions are designed into Power that don’t impact performance like other architectures.

I write all this as a set-up for IBM's announced expanded support for its Power10 architecture. In the following paragraphs, I will provide the details of IBM's announcement and give some thoughts on what this could mean for enterprise IT.

What was announced

Before discussing what was announced, it is a good idea to do a quick overview of Power10.

IBM introduced the Power10 CPU architecture at the Hot Chips conference in August 2020. Moor Insights & Strategy chief analyst Patrick Moorhead wrote about it here. Power10 is developed on the opensource Power ISA. Power10 comes in two variants – 15x SMT8 cores and 30x SMT4 cores. For those familiar with x86, SMT8 (8 threads/core seems extreme, as does SMT4. But this is where the Power ISA is fundamentally different from x86. Power is a highly performant ISA, and the Power10 cores are designed for the most demanding workloads.

One last note on Power10. SMT8 is optimized for higher throughput and lower computation. SMT4 attacks the compute-intensive space with lower throughput.

IBM introduced the Power E1080 in September of 2021. Moor Insights & Strategy chief analyst Patrick Moorhead wrote about it here. The E1080 is a system designed for mission and business-critical workloads and has been strongly adopted by IBM's loyal Power customer base.

Because of this success, IBM has expanded the breadth of the Power10 portfolio and how customers consume these resources.

The big reveal in IBM’s accurate announcement is the availability of four new servers built on the Power10 architecture. These servers are designed to address customers' full range of workload needs in the enterprise datacenter.

The Power S1014 is the traditional enterprise workhorse that runs the modern business. For x86 IT folks, think of the S1014 equivalent to the two-socket workhorses that run virtualized infrastructure. One of the things that IBM points out about the S1014 is that this server was designed with lower technical requirements. This statement leads me to believe that the company is perhaps softening the barrier for the S1014 in data centers that are not traditional IBM shops. Or maybe for environments that use Power for higher-end workloads but non-Power for traditional infrastructure needs.

The Power S1022 is IBM's scale-out server. Organizations embracing cloud-native, containerized environments will find the S1022 an ideal match. Again, for the x86 crowd – think of the traditional scale-out servers that are perhaps an AMD single socket or Intel dual-socket – the S1022 would be IBM's equivalent.

Finally, the S1024 targets the data analytics space. With lots of high-performing cores and a big memory footprint – this server plays in the area where IBM has done so well.

In addition, to these platforms, IBM also introduced the Power E1050. The E1050 seems designed for big data and workloads with significant memory throughput requirements.

The E1050 is where I believe the difference in the Power architecture becomes obvious. The E1050 is where midrange starts to bump into high performance, and IBM claims 8-socket performance in this four-socket socket configuration. IBM says it can deliver performance for those running big data environments, larger data warehouses, and high-performance workloads. Maybe, more importantly, the company claims to provide considerable cost savings for workloads that generally require a significant financial investment.

One benchmark that IBM showed was the two-tier SAP Standard app benchmark. In this test, the E1050 beat an x86, 8-socket server handily, showing a 2.6x per-core performance advantage. We at Moor Insights & Strategy didn’t run the benchmark or certify it, but the company has been conservative in its disclosures, and I have no reason to dispute it.

But the performance and cost savings are not just associated with these higher-end workloads with narrow applicability. In another comparison, IBM showed the Power S1022 performs 3.6x better than its x86 equivalent for running a containerized environment in Red Hat OpenShift. When all was added up, the S1022 was shown to lower TCO by 53%.

What makes Power-based servers perform so well in SAP and OpenShift?

The value of Power is derived both from the CPU architecture and the value IBM puts into the system and server design. The company is not afraid to design and deploy enhancements it believes will deliver better performance, higher security, and greater reliability for its customers. In the case of Power10, I believe there are a few design factors that have contributed to the performance and price//performance advantages the company claims, including

  • Use Differential DIMM technology to increase memory bandwidth, allowing for better performance from memory-intensive workloads such as in-memory database environments.
  • Built-in AI inferencing engines that increase performance by up to 5x.
  • Transparent memory encryption performs this function with no performance tax (note: AMD has had this technology for years, and Intel introduced about a year ago).

These seemingly minor differences can add up to deliver significant performance benefits for workloads running in the datacenter. But some of this comes down to a very powerful (pardon the redundancy) core design. While x86 dominates the datacenter in unit share, IBM has maintained a loyal customer base because the Power CPUs are workhorses, and Power servers are performant, secure, and reliable for mission critical applications.

Consumption-based offerings

Like other server vendors, IBM sees the writing on the wall and has opened up its offerings to be consumed in a way that is most beneficial to its customers. Traditional acquisition model? Check. Pay as you go with hardware in your datacenter? Also, check. Cloud-based offerings? One more check.

While there is nothing revolutionary about what IBM is doing with how customers consume its technology, it is important to note that IBM is the only server vendor that also runs a global cloud service (IBM Cloud). This should enable the company to pass on savings to its customers while providing greater security and manageability.

Closing thoughts

I like what IBM is doing to maintain and potentially grow its market presence. The new Power10 lineup is designed to meet customers' entire range of performance and cost requirements without sacrificing any of the differentiated design and development that the company puts into its mission critical platforms.

Will this announcement move x86 IT organizations to transition to IBM? Unlikely. Nor do I believe this is IBM's goal. However, I can see how businesses concerned with performance, security, and TCO of their mission and business-critical workloads can find a strong argument for Power. And this can be the beginning of a more substantial Power presence in the datacenter.

Note: This analysis contains insights from Moor Insights & Strategy Founder and Chief Analyst, Patrick Moorhead.

Moor Insights & Strategy, like all research and tech industry analyst firms, provides or has provided paid services to technology companies. These services include research, analysis, advising, consulting, benchmarking, acquisition matchmaking, and speaking sponsorships. The company has had or currently has paid business relationships with 8×8, Accenture, A10 Networks, Advanced Micro Devices, Amazon, Amazon Web Services, Ambient Scientific, Anuta Networks, Applied Brain Research, Applied Micro, Apstra, Arm, Aruba Networks (now HPE), Atom Computing, AT&T, Aura, Automation Anywhere, AWS, A-10 Strategies, Bitfusion, Blaize, Box, Broadcom, C3.AI, Calix, Campfire, Cisco Systems, Clear Software, Cloudera, Clumio, Cognitive Systems, CompuCom, Cradlepoint, CyberArk, Dell, Dell EMC, Dell Technologies, Diablo Technologies, Dialogue Group, Digital Optics, Dreamium Labs, D-Wave, Echelon, Ericsson, Extreme Networks, Five9, Flex, Foundries.io, Foxconn, Frame (now VMware), Fujitsu, Gen Z Consortium, Glue Networks, GlobalFoundries, Revolve (now Google), Google Cloud, Graphcore, Groq, Hiregenics, Hotwire Global, HP Inc., Hewlett Packard Enterprise, Honeywell, Huawei Technologies, IBM, Infinidat, Infosys, Inseego, IonQ, IonVR, Inseego, Infosys, Infiot, Intel, Interdigital, Jabil Circuit, Keysight, Konica Minolta, Lattice Semiconductor, Lenovo, Linux Foundation, Lightbits Labs, LogicMonitor, Luminar, MapBox, Marvell Technology, Mavenir, Marseille Inc, Mayfair Equity, Meraki (Cisco), Merck KGaA, Mesophere, Micron Technology, Microsoft, MiTEL, Mojo Networks, MongoDB, MulteFire Alliance, National Instruments, Neat, NetApp, Nightwatch, NOKIA (Alcatel-Lucent), Nortek, Novumind, NVIDIA, Nutanix, Nuvia (now Qualcomm), onsemi, ONUG, OpenStack Foundation, Oracle, Palo Alto Networks, Panasas, Peraso, Pexip, Pixelworks, Plume Design, PlusAI, Poly (formerly Plantronics), Portworx, Pure Storage, Qualcomm, Quantinuum, Rackspace, Rambus, Rayvolt E-Bikes, Red Hat, Renesas, Residio, Samsung Electronics, Samsung Semi, SAP, SAS, Scale Computing, Schneider Electric, SiFive, Silver Peak (now Aruba-HPE), SkyWorks, SONY Optical Storage, Splunk, Springpath (now Cisco), Spirent, Splunk, Sprint (now T-Mobile), Stratus Technologies, Symantec, Synaptics, Syniverse, Synopsys, Tanium, Telesign,TE Connectivity, TensTorrent, Tobii Technology, Teradata,T-Mobile, Treasure Data, Twitter, Unity Technologies, UiPath, Verizon Communications, VAST Data, Ventana Micro Systems, Vidyo, VMware, Wave Computing, Wellsmith, Xilinx, Zayo, Zebra, Zededa, Zendesk, Zoho, Zoom, and Zscaler. Moor Insights & Strategy founder, CEO, and Chief Analyst Patrick Moorhead is an investor in dMY Technology Group Inc. VI, Dreamium Labs, Groq, Luminar Technologies, MemryX, and Movandi.

Wed, 13 Jul 2022 12:00:00 -0500 Matt Kimball en text/html https://www.forbes.com/sites/moorinsights/2022/07/14/ibm-expands-its-power10-portfolio-for-mission-critical-applications/
Killexams : IBM Research Rolls Out A Comprehensive AI And Platform-Based Edge Research Strategy Anchored By Enterprise Partnerships & Use Cases

I recently met with Dr. Nick Fuller, Vice President, Distributed Cloud, at IBM Research for a discussion about IBM’s long-range plans and strategy for artificial intelligence and machine learning at the edge.

Dr. Fuller is responsible for providing AI and platform–based innovation for enterprise digital transformation spanning edge computing and distributed cloud management. He is an IBM Master Inventor with over 75 patents and co-author of 75 technical publications. Dr. Fuller obtained his Bachelor of Science in Physics and Math from Morehouse College and his PhD in Applied Physics from Columbia University.

Edge In, not Cloud Out

In general, Dr. Fuller told me that IBM is focused on developing an "edge in" position versus a "cloud out" position with data, AI, and Kubernetes-based platform technologies to scale hub and spoke deployments of edge applications.

A hub plays the role of a central control plane used for orchestrating the deployment and management of edge applications in a number of connected spoke locations such as a factory floor or a retail branch, where data is generated or locally aggregated for processing.

“Cloud out” refers to the paradigm where cloud service providers are extending their cloud architecture out to edge locations. In contrast, “edge in” refers to a provider-agnostic architecture that is cloud-independent and treats the data-plane as a first-class citizen.

IBM's overall architectural principle is scalability, repeatability, and full stack solution management that allows everything to be managed using a single unified control plane.

IBM’s Red Hat platform and infrastructure strategy anchors the application stack with a unified, scalable, and managed OpenShift-based control plane equipped with a high-performance storage appliance and self-healing system capabilities (inclusive of semi-autonomous operations).

IBM’s strategy also includes several in-progress platform-level technologies for scalable data, AI/ML runtimes, accelerator libraries for Day-2 AI operations, and scalability for the enterprise.

It is an important to mention that IBM is designing its edge platforms with labor cost and technical workforce in mind. Data scientists with PhDs are in high demand, making them difficult to find and expensive to hire once you find them. IBM is designing its edge system capabilities and processes so that domain experts rather than PhDs can deploy new AI models and manage Day-2 operations.

Why edge is important

Advances in computing and storage have made it possible for AI to process mountains of accumulated data to provide solutions. By bringing AI closer to the source of data, edge computing is faster and more efficient than cloud. While Cloud data accounts for 60% of the world’s data today, vast amounts of new data is being created at the edge, including industrial applications, traffic cameras, and order management systems, all of which can be processed at the edge in a fast and timely manner.

Public cloud and edge computing differ in capacity, technology, and management. An advantage of edge is that data is processed and analyzed at / near its collection point at the edge. In the case of cloud, data must be transferred from a local device and into the cloud for analytics and then transferred back to the edge again. Moving data through the network consumes capacity and adds latency to the process. It’s easy to see why executing a transaction at the edge reduces latency and eliminates unnecessary load on the network.

Increased privacy is another benefit of processing data at the edge. Analyzing data where it originates limits the risk of a security breach. Most of the communications between the edge and the cloud is then confined to such things as reporting, data summaries, and AI models, without ever exposing the raw data.

IBM at the Edge

In our discussion, Dr. Fuller provided a few examples to illustrate how IBM plans to provide new and seamless edge solutions for existing enterprise problems.

Example #1 – McDonald’s drive-thru

Dr. Fuller’s first example centered around Quick Service Restaurant’s (QSR) problem of drive-thru order taking. Last year, IBM acquired an automated order-taking system from McDonald's. As part of the acquisition, IBM and McDonald's established a partnership to perfect voice ordering methods using AI. Drive-thru orders are a significant percentage of total QSR orders for McDonald's and other QSR chains.

McDonald's and other QSR restaurants would like every order to be processed as quickly and accurately as possible. For that reason, McDonald's conducted trials at ten Chicago restaurants using an edge-based AI ordering system with NLP (Natural Language Processing) to convert spoken orders into a digital format. It was found that AI had the potential to reduce ordering errors and processing time significantly. Since McDonald's sells almost 7 million hamburgers daily, shaving a minute or two off each order represents a significant opportunity to address labor shortages and increase customer satisfaction.

Example #2 – Boston Dynamics and Spot the agile mobile robot

According to an earlier IBM survey, many manufacturers have already implemented AI-driven robotics with autonomous decision-making capability. The study also indicated that over 80 percent of companies believe AI can help Excellerate future business operations. However, some companies expressed concern about the limited mobility of edge devices and sensors.

To develop a mobile edge solution, IBM teamed up with Boston Dynamics. The partnership created an agile mobile robot using IBM Research and IBM Sustainability Software AI technology. The device can analyze visual sensor readings in hazardous and challenging industrial environments such as manufacturing plants, warehouses, electrical grids, waste treatment plants and other hazardous environments. The value proposition that Boston Dynamics brought to the partnership was Spot the agile mobile robot, a walking, sensing, and actuation platform. Like all edge applications, the robot’s wireless mobility uses self-contained AI/ML that doesn’t require access to cloud data. It uses cameras to read analog devices, visually monitor fire extinguishers, and conduct a visual inspection of human workers to determine if required safety equipment is being worn.

IBM was able to show up to a 10X speedup by automating some manual tasks, such as converting the detection of a problem into an immediate work order in IBM Maximo to correct it. A fast automated response was not only more efficient, but it also improved the safety posture and risk management for these facilities. Similarly, some factories need to thermally monitor equipment to identify any unexpected hot spots that may show up over time, indicative of a potential failure.

IBM is working with National Grid, an energy company, to develop a mobile solution using Spot, the agile mobile robot, for image analysis of transformers and thermal connectors. As shown in the above graphic, Spot also monitored connectors on both flat surfaces and 3D surfaces. IBM was able to show that Spot could detect excessive heat build-up in small connectors, potentially avoiding unsafe conditions or costly outages. This AI/ML edge application can produce faster response times when an issue is detected, which is why IBM believes significant gains are possible by automating the entire process.

IBM market opportunities

Drive-thru orders and mobile robots are just a few examples of the millions of potential AI applications that exist at the edge and are driven by several billion connected devices.

Edge computing is an essential part of enterprise digital transformation. Enterprises seek ways to demonstrate the feasibility of solving business problems using AI/ML and analytics at the edge. However, once a proof of concept has been successfully demonstrated, it is a common problem for a company to struggle with scalability, data governance, and full-stack solution management.

Challenges with scaling

“Determining entry points for AI at the edge is not the difficult part,” Dr. Fuller said. “Scale is the real issue.”

Scaling edge models is complicated because there are so many edge locations with large amounts of diverse content and a high device density. Because large amounts of data are required for training, data gravity is a potential problem. Further, in many scenarios, vast amounts of data are generated quickly, leading to potential data storage and orchestration challenges. AI Models are also rarely "finished." Monitoring and retraining of models are necessary to keep up with changes the environment.

Through IBM Research, IBM is addressing the many challenges of building an all-encompassing edge architecture and horizontally scalable data and AI technologies. IBM has a wealth of edge capabilities and an architecture to create the appropriate platform for each application.

IBM AI entry points at the edge

IBM sees Edge Computing as a $200 billion market by 2025. Dr. Fuller and his organization have identified four key market entry points for developing and expanding IBM’s edge compute strategy. In order of size, IBM believes its priority edge markets to be intelligent factories (Industry 4.0), telcos, retail automation, and connected vehicles.

IBM and its Red Hat portfolio already have an established presence in each market segment, particularly in intelligent operations and telco. Red Hat is also active in the connected vehicles space.

Industry 4.0

There have been three prior industrial revolutions, beginning in the 1700s up to our current in-progress fourth revolution, Industry 4.0, that promotes a digital transformation.

Manufacturing is the fastest growing and the largest of IBM’s four entry markets. In this segment, AI at the edge can Excellerate quality control, production optimization, asset management, and supply chain logistics. IBM believes there are opportunities to achieve a 4x speed up in implementing edge-based AI solutions for manufacturing operations.

For its Industry 4.0 use case development, IBM, through product, development, research and consulting teams, is working with a major automotive OEM. The partnership has established the following joint objectives:

  • Increase automation and scalability across dozens of plants using 100s of AI / ML models. This client has already seen value in applying AI/ML models for manufacturing applications. IBM Research is helping with re-training models and implementing new ones in an edge environment to help scale even more efficiently. Edge offers faster inference and low latency, allowing AI to be deployed in a wider variety of manufacturing operations requiring instant solutions.
  • Dramatically reduce the time required to onboard new models. This will allow training and inference to be done faster and allow large models to be deployed much more quickly. The quicker an AI model can be deployed in production; the quicker the time-to-value and the return-on-investment (ROI).
  • Accelerate deployment of new inspections by reducing the labeling effort and iterations needed to produce a production-ready model via data summarization. Selecting small data sets for annotation means manually examining thousands of images, this is a time-consuming process that will result in - labeling of redundant data. Using ML-based automation for data summarization will accelerate the process and produce better model performance.
  • Enable Day-2 AI operations to help with data lifecycle automation and governance, model creation, reduce production errors, and provide detection of out-of-distribution data to help determine if a model’s inference is accurate. IBM believes this will allow models to be created faster without data scientists.

Maximo Application Suite

IBM’s Maximo Application Suite plays an important part in implementing large manufacturers' current and future IBM edge solutions. Maximo is an integrated public or private cloud platform that uses AI, IoT, and analytics to optimize performance, extend asset lifecycles and reduce operational downtime and costs. IBM is working with several large manufacturing clients currently using Maximo to develop edge use cases, and even uses it within its own Manufacturing.

IBM has research underway to develop a more efficient method of handling life cycle management of large models that require immense amounts of data. Day 2 AI operations tasks can sometimes be more complex than initial model training, deployment, and scaling. Retraining at the edge is difficult because resources are typically limited.

Once a model is trained and deployed, it is important to monitor it for drift caused by changes in data distributions or anything that might cause a model to deviate from original requirements. Inaccuracies can adversely affect model ROI.

Day-2 AI Operations (retraining and scaling)

Day-2 AI operations consist of continual updates to AI models and applications to keep up with changes in data distributions, changes in the environment, a drop in model performance, availability of new data, and/or new regulations.

IBM recognizes the advantages of performing Day-2 AI Operations, which includes scaling and retraining at the edge. It appears that IBM is the only company with an architecture equipped to effectively handle Day-2 AI operations. That is a significant competitive advantage for IBM.

A company using an architecture that requires data to be moved from the edge back into the cloud for Day-2 related work will be unable to support many factory AI/ML applications because of the sheer number of AI/ML models to support (100s to 1000s).

“There is a huge proliferation of data at the edge that exists in multiple spokes,” Dr. Fuller said. "However, all that data isn’t needed to retrain a model. It is possible to cluster data into groups and then use sampling techniques to retrain the model. There is much value in federated learning from our point of view.”

Federated learning is a promising training solution being researched by IBM and others. It preserves privacy by using a collaboration of edge devices to train models without sharing the data with other entities. It is a good framework to use when resources are limited.

Dealing with limited resources at the edge is a challenge. IBM’s edge architecture accommodates the need to ensure resource budgets for AI applications are met, especially when deploying multiple applications and multiple models across edge locations. For that reason, IBM developed a method to deploy data and AI applications to scale Day-2 AI operations utilizing hub and spokes.

The graphic above shows the current status quo methods of performing Day-2 operations using centralized applications and a centralized data plane compared to the more efficient managed hub and spoke method with distributed applications and a distributed data plane. The hub allows it all to be managed from a single pane of glass.

Data Fabric Extensions to Hub and Spokes

IBM uses hub and spoke as a model to extend its data fabric. The model should not be thought of in the context of a traditional hub and spoke. IBM’s hub provides centralized capabilities to manage clusters and create multiples hubs that can be aggregated to a higher level. This architecture has four important data management capabilities.

  1. First, models running in unattended environments must be monitored. From an operational standpoint, detecting when a model’s effectiveness has significantly degraded and if corrective action is needed is critical.
  2. Secondly, in a hub and spoke model, data is being generated and collected in many locations creating a need for data life cycle management. Working with large enterprise clients, IBM is building unique capabilities to manage the data plane across the hub and spoke estate - optimized to meet data lifecycle, regulatory & compliance as well as local resource requirements. Automation determines which input data should be selected and labeled for retraining purposes and used to further Excellerate the model. Identification is also made for atypical data that is judged worthy of human attention.
  3. The third issue relates to AI pipeline compression and adaptation. As mentioned earlier, edge resources are limited and highly heterogeneous. While a cloud-based model might have a few hundred million parameters or more, edge models can’t afford such resource extravagance because of resource limitations. To reduce the edge compute footprint, model compression can reduce the number of parameters. As an example, it could be reduced from several hundred million to a few million.
  4. Lastly, suppose a scenario exists where data is produced at multiple spokes but cannot leave those spokes for compliance reasons. In that case, IBM Federated Learning allows learning across heterogeneous data in multiple spokes. Users can discover, curate, categorize and share data assets, data sets, analytical models, and their relationships with other organization members.

In addition to AI deployments, the hub and spoke architecture and the previously mentioned capabilities can be employed more generally to tackle challenges faced by many enterprises in consistently managing an abundance of devices within and across their enterprise locations. Management of the software delivery lifecycle or addressing security vulnerabilities across a vast estate are a case in point.

Multicloud and Edge platform

In the context of its strategy, IBM sees edge and distributed cloud as an extension of its hybrid cloud platform built around Red Hat OpenShift. One of the newer and more useful options created by the Red Hat development team is the Single Node OpenShift (SNO), a compact version of OpenShift that fits on a single server. It is suitable for addressing locations that are still servers but come in a single node, not clustered, deployment type.

For smaller footprints such as industrial PCs or computer vision boards (for example NVidia Jetson Xavier), Red Hat is working on a project which builds an even smaller version of OpenShift, called MicroShift, that provides full application deployment and Kubernetes management capabilities. It is packaged so that it can be used for edge device type deployments.

Overall, IBM and Red Hat have developed a full complement of options to address a large spectrum of deployments across different edge locations and footprints, ranging from containers to management of full-blown Kubernetes applications from MicroShift to OpenShift and IBM Edge Application Manager.

Much is still in the research stage. IBM's objective is to achieve greater consistency in terms of how locations and application lifecycle is managed.

First, Red Hat plans to introduce hierarchical layers of management with Red Hat Advanced Cluster Management (RHACM), to scale by two to three orders of magnitude the number of edge locations managed by this product. Additionally, securing edge locations is a major focus. Red Hat is continuously expanding platform security features, for example by recently including Integrity Measurement Architecture in Red Hat Enterprise Linux, or by adding Integrity Shield to protect policies in Red Hat Advanced Cluster Management (RHACM).

Red Hat is partnering with IBM Research to advance technologies that will permit it to protect platform integrity and the integrity of client workloads through the entire software supply chains. In addition, IBM Research is working with Red Hat on analytic capabilities to identify and remediate vulnerabilities and other security risks in code and configurations.

Telco network intelligence and slice management with AL/ML

Communication service providers (CSPs) such as telcos are key enablers of 5G at the edge. 5G benefits for these providers include:

  • Reduced operating costs
  • Improved efficiency
  • Increased distribution and density
  • Lower latency

The end-to-end 5G network comprises the Radio Access Network (RAN), transport, and core domains. Network slicing in 5G is an architecture that enables multiple virtual and independent end-to-end logical networks with different characteristics such as low latency or high bandwidth, to be supported on the same physical network. This is implemented using cloud-native technology enablers such as software defined networking (SDN), virtualization, and multi-access edge computing. Slicing offers necessary flexibility by allowing the creation of specific applications, unique services, and defined user groups or networks.

An important aspect of enabling AI at the edge requires IBM to provide CSPs with the capability to deploy and manage applications across various enterprise locations, possibly spanning multiple end-to-end network slices, using a single pane of glass.

5G network slicing and slice management

Network slices are an essential part of IBM's edge infrastructure that must be automated, orchestrated and optimized according to 5G standards. IBM’s strategy is to leverage AI/ML to efficiently manage, scale, and optimize the slice quality of service, measured in terms of bandwidth, latency, or other metrics.

5G and AI/ML at the edge also represent a significant opportunity for CSPs to move beyond traditional cellular services and capture new sources of revenue with new services.

Communications service providers need management and control of 5G network slicing enabled with AI-powered automation.

Dr. Fuller sees a variety of opportunities in this area. "When it comes to applying AI and ML on the network, you can detect things like intrusion detection and malicious actors," he said. "You can also determine the best way to route traffic to an end user. Automating 5G functions that run on the network using IBM network automation software also serves as an entry point.”

In IBM’s current telecom trial, IBM Research is spearheading the development of a range of capabilities targeted for the IBM Cloud Pak for Network Automation product using AI and automation to orchestrate, operate and optimize multivendor network functions and services that include:

  • End-to-end 5G network slice management with planning & design, automation & orchestration, and operations & assurance
  • Network Data and AI Function (NWDAF) that collects data for slice monitoring from 5G Core network functions, performs network analytics, and provides insights to authorized data consumers.
  • Improved operational efficiency and reduced cost

Future leverage of these capabilities by existing IBM Clients that use the Cloud Pak for Network Automation (e.g., DISH) can offer further differentiation for CSPs.

5G radio access

Open radio access networks (O-RANs) are expected to significantly impact telco 5G wireless edge applications by allowing a greater variety of units to access the system. The O-RAN concept separates the DU (Distributed Units) and CU (Centralized Unit) from a Baseband Unit in 4G and connects them with open interfaces.

O-RAN system is more flexible. It uses AI to establish connections made via open interfaces that optimize the category of a device by analyzing information about its prior use. Like other edge models, the O-RAN architecture provides an opportunity for continuous monitoring, verification, analysis, and optimization of AI models.

The IBM-telco collaboration is expected to advance O-RAN interfaces and workflows. Areas currently under development are:

  • Multi-modal (RF level + network-level) analytics (AI/ML) for wireless communication with high-speed ingest of 5G data
  • Capability to learn patterns of metric and log data across CUs and DUs in RF analytics
  • Utilization of the antenna control plane to optimize throughput
  • Primitives for forecasting, anomaly detection and root cause analysis using ML
  • Opportunity of value-added functions for O-RAN

IBM Cloud and Infrastructure

The cornerstone for the delivery of IBM's edge solutions as a service is IBM Cloud Satellite. It presents a consistent cloud-ready, cloud-native operational view with OpenShift and IBM Cloud PaaS services at the edge. In addition, IBM integrated hardware and software Edge systems will provide RHACM - based management of the platform when clients or third parties have existing managed as a service models. It is essential to note that in either case this is done within a single control plane for hubs and spokes that helps optimize execution and management from any cloud to the edge in the hub and spoke model.

IBM's focus on “edge in” means it can provide the infrastructure through things like the example shown above for software defined storage for federated namespace data lake that surrounds other hyperscaler clouds. Additionally, IBM is exploring integrated full stack edge storage appliances based on hyperconverged infrastructure (HCI), such as the Spectrum Fusion HCI, for enterprise edge deployments.

As mentioned earlier, data gravity is one of the main driving factors of edge deployments. IBM has designed its infrastructure to meet those data gravity requirements, not just for the existing hub and spoke topology but also for a future spoke-to-spoke topology where peer-to-peer data sharing becomes imperative (as illustrated with the wealth of examples provided in this article).

Wrap up

Edge is a distributed computing model. One of its main advantages is that computing, and data storage and processing is close to where data is created. Without the need to move data to the cloud for processing, real-time application of analytics and AI capabilities provides immediate solutions and drives business value.

IBM’s goal is not to move the entirety of its cloud infrastructure to the edge. That has little value and would simply function as a hub to spoke model operating on actions and configurations dictated by the hub.

IBM’s architecture will provide the edge with autonomy to determine where data should reside and from where the control plane should be exercised.

Equally important, IBM foresees this architecture evolving into a decentralized model capable of edge-to-edge interactions. IBM has no firm designs for this as yet. However, the plan is to make the edge infrastructure and platform a first-class citizen instead of relying on the cloud to drive what happens at the edge.

Developing a complete and comprehensive AI/ML edge architecture - and in fact, an entire ecosystem - is a massive undertaking. IBM faces many known and unknown challenges that must be solved before it can achieve success.

However, IBM is one of the few companies with the necessary partners and the technical and financial resources to undertake and successfully implement a project of this magnitude and complexity.

It is reassuring that IBM has a plan and that its plan is sound.

Paul Smith-Goodson is Vice President and Principal Analyst for quantum computing, artificial intelligence and space at Moor Insights and Strategy. You can follow him on Twitter for more current information on quantum, AI, and space.

Note: Moor Insights & Strategy writers and editors may have contributed to this article.

Moor Insights & Strategy, like all research and tech industry analyst firms, provides or has provided paid services to technology companies. These services include research, analysis, advising, consulting, benchmarking, acquisition matchmaking, and speaking sponsorships. The company has had or currently has paid business relationships with 8×8, Accenture, A10 Networks, Advanced Micro Devices, Amazon, Amazon Web Services, Ambient Scientific, Anuta Networks, Applied Brain Research, Applied Micro, Apstra, Arm, Aruba Networks (now HPE), Atom Computing, AT&T, Aura, Automation Anywhere, AWS, A-10 Strategies, Bitfusion, Blaize, Box, Broadcom, C3.AI, Calix, Campfire, Cisco Systems, Clear Software, Cloudera, Clumio, Cognitive Systems, CompuCom, Cradlepoint, CyberArk, Dell, Dell EMC, Dell Technologies, Diablo Technologies, Dialogue Group, Digital Optics, Dreamium Labs, D-Wave, Echelon, Ericsson, Extreme Networks, Five9, Flex, Foundries.io, Foxconn, Frame (now VMware), Fujitsu, Gen Z Consortium, Glue Networks, GlobalFoundries, Revolve (now Google), Google Cloud, Graphcore, Groq, Hiregenics, Hotwire Global, HP Inc., Hewlett Packard Enterprise, Honeywell, Huawei Technologies, IBM, Infinidat, Infosys, Inseego, IonQ, IonVR, Inseego, Infosys, Infiot, Intel, Interdigital, Jabil Circuit, Keysight, Konica Minolta, Lattice Semiconductor, Lenovo, Linux Foundation, Lightbits Labs, LogicMonitor, Luminar, MapBox, Marvell Technology, Mavenir, Marseille Inc, Mayfair Equity, Meraki (Cisco), Merck KGaA, Mesophere, Micron Technology, Microsoft, MiTEL, Mojo Networks, MongoDB, MulteFire Alliance, National Instruments, Neat, NetApp, Nightwatch, NOKIA (Alcatel-Lucent), Nortek, Novumind, NVIDIA, Nutanix, Nuvia (now Qualcomm), onsemi, ONUG, OpenStack Foundation, Oracle, Palo Alto Networks, Panasas, Peraso, Pexip, Pixelworks, Plume Design, PlusAI, Poly (formerly Plantronics), Portworx, Pure Storage, Qualcomm, Quantinuum, Rackspace, Rambus, Rayvolt E-Bikes, Red Hat, Renesas, Residio, Samsung Electronics, Samsung Semi, SAP, SAS, Scale Computing, Schneider Electric, SiFive, Silver Peak (now Aruba-HPE), SkyWorks, SONY Optical Storage, Splunk, Springpath (now Cisco), Spirent, Splunk, Sprint (now T-Mobile), Stratus Technologies, Symantec, Synaptics, Syniverse, Synopsys, Tanium, Telesign,TE Connectivity, TensTorrent, Tobii Technology, Teradata,T-Mobile, Treasure Data, Twitter, Unity Technologies, UiPath, Verizon Communications, VAST Data, Ventana Micro Systems, Vidyo, VMware, Wave Computing, Wellsmith, Xilinx, Zayo, Zebra, Zededa, Zendesk, Zoho, Zoom, and Zscaler. Moor Insights & Strategy founder, CEO, and Chief Analyst Patrick Moorhead is an investor in dMY Technology Group Inc. VI, Dreamium Labs, Groq, Luminar Technologies, MemryX, and Movandi.

Mon, 08 Aug 2022 03:51:00 -0500 Paul Smith-Goodson en text/html https://www.forbes.com/sites/moorinsights/2022/08/08/ibm-research-rolls-out-a-comprehensive-ai-and-ml-edge-research-strategy-anchored-by-enterprise-partnerships-and-use-cases/
Killexams : IBM Uses Power10 CPU As An I/O Switch

Back in early July, we covered the launch of IBM’s entry and midrange Power10 systems and mused about how Big Blue could use these systems to reinvigorate an HPC business rather than just satisfy the needs of the enterprise customers who run transaction processing systems and are looking to add AI inference to their applications through matrix math units on the Power10 chip.

We are still gathering up information on how the midrange Power E1050 stacks up on SAP HANA and other workloads, but in poking around the architecture of the entry single-socket Power S1014 and the dual-socket S1022 and S1024 machines, we found something interesting that we thought we should share with you. We didn’t see it at first, and you will understand immediately why.

Here is the block diagram we got our hands on from IBM’s presentations to its resellers for the Power S1014 machine:

You can clearly see an I/O chip that adds some extra PCI-Express traffic lanes to the Power10 processor complex, right?

Same here with the block diagram of the Power S1022 (2U chassis) machines, which use the same system boards:

There are a pair of I/O switches in there, as you can see, which is not a big deal. Intel has co-packaged PCH chipsets in the same package as the Xeon CPUs with the Xeon D line for years, starting with the “Broadwell-DE” Xeon D processor in May 2015. IBM has used PCI-Express switches in the past to stretch the I/O inside a single machine beyond what comes off natively from the CPUs, such as with the Power IC922 inference engine Big Blue launched in January 2020, which you can see here:

The two PEX blocks in the center are PCI-Express switches, either from Broadcom or MicroChip if we had to guess.

But, that is not what is happening with the Power10 entry machines. Rather, IBM has created a single dual-chip module with two whole Power10 chips inside of it, and in the case of the low-end machines where AIX and IBM i customers don’t need a lot of compute but they do need a lot of I/O, the second Power10 chip has all of its cores turned off and it is acting like an I/O switch for the first Power10 chip that does have cores turned on.

You can see this clearly in this more detailed block diagram of the Power S1014 machine:

And in a more detailed block diagram of the two-socket Power S1022 motherboard:

This is the first time we can recall seeing something like this, but obviously any processor architecture could support the same functions.

In the two-socket Power S1024 and Power L1024 machines

What we find particularly interesting is the idea that those Power10 “switch” chips – the ones with no cores activated – could in theory also have eight OpenCAPI Memory Interface (OMI) ports turned on, doubling the memory capacity of the systems using skinnier and slightly faster 128 GB memory sticks, which run at 3.2 GHz, rather than having to move to denser 256 GB memory sticks that run at a slower 2.67 GHz when they are available next year. And in fact, you could take this all one step further and turn off all of the Power10 cores and turn on all of the 16 OMI memory slots across each DCM and create a fat 8 TB or 16 TB memory server that through the Power10 memory area network – what IBM calls memory inception – could serve as the main memory for a bunch of Power10 nodes with no memory of their own.

We wonder if IBM will do such a thing, and also ponder what such a cluster of memory-less server nodes talking to a centralized memory node might do with SAP HANA, Spark, data analytics, and other memory intensive work like genomics. The Power10 chip has a 2 PB upper memory limit, and that is the only cap on where this might go.

There is another neat thing IBM could do here, too. Imagine if the Power10 compute chip in a DCM had no I/O at all but just lots of memory attached to it and the secondary Power10 chip had only a few cores and all of the I/O of the complex. That would, in effect, make the second Power10 chip a DPU for the first one.

The engineers at IBM are clearly thinking outside of the box; it will be interesting to see if the product managers and marketeers do so.

Tue, 26 Jul 2022 05:54:00 -0500 Timothy Prickett Morgan en-US text/html https://www.nextplatform.com/2022/07/26/ibm-uses-power10-cpu-as-an-i-o-switch/
Killexams : IBM expands Power10 capabilities
IBM Power

(Source – IBM)

  • The Power Systems is a family of server computers from IBM that are based on its Power processor.
  • IBM Power helps customers respond faster to business demands, protect data from core to cloud, and streamline insights and automation while maximizing reliability in a sustainable way.

As businesses continue to increase their reliance on the cloud, having a reliable infrastructure to support their workloads is key. With the hybrid and multi-cloud seemingly the go-to model for most organizations today, having access to an ecosystem of tools that can run essential workloads such as databases and core business applications is a prerogative.

While most tech vendors are able to provide this, having a purpose-built system is ideally the best solution for organizations. And this is where IBM Power systems come in. Known for their performance, scalability, and flexibility, IBM recently announced an expansion to its Power10 server line with the introduction of mid-range and scale-out systems to modernize, protect and automate business applications and IT operations.

The new servers join the popular Power10 E1080 server which was initially introduced in September 2021 to deliver a secured, resilient hybrid cloud experience that can be managed with other x86 and multi-cloud management software across clients’ IT infrastructure. This expansion of the IBM Power10 family with the new midrange and scale-out servers brings high-end server capabilities throughout the product line. Not only do the new systems support critical security features such as transparent memory encryption and advanced processor/system isolation, but also leverage the OpenBMC project from the Linux Foundation for high levels of security for the new scale-out servers.

In a accurate media briefing, Francis Ong, ASEANZK POWER Business Unit Executive commented that the expanded IBM Power10 portfolio is built around the next-generation IBM Power10 processor with two times more cores and more than two times memory bandwidth than previous Power generations.

What makes it more interesting is the new flexible consumption choices. As organizations continue to expand based on their business requirements, IBM’s new flexible consumption offerings enable pay-as-you-go options and by-the-minute metering for IBM Power Private Cloud. This enables more opportunities to help lower the cost of running OpenShift solutions on Power when compared to alternative platforms.

Ong explained that these new consumption models build on options already available with IBM Power Virtual Server to enable greater flexibility in clients’ hybrid journeys. Additionally, the highly anticipated IBM subscription delivers a comprehensive platform solution with the hardware, software, and support/services included in the subscription service.

At the same time, the expansion of the IBM Power10 family has been engineered to establish one of the industry’s most flexible and broadest range of servers for data-intensive workloads such as SAP S/4HANA – from on-premises workloads to hybrid cloud. The new systems with IBM Power Virtual Server also help clients operate a secured hybrid cloud experience that delivers high performance and architectural consistency across their IT infrastructure. The systems are uniquely designed so as to protect sensitive data from core to cloud and enable virtual machines and containerized workloads to run simultaneously on the same systems.

For critical business workloads that have traditionally needed to reside on-premises, they can now be moved into the cloud as workloads and needs demand. This flexibility can help clients mitigate the risk and time associated with rewriting applications for a different platform.

To maximize the capabilities of the IBM Power10, businesses would need the support of a robust ecosystem. In Malaysia, the banking system has been relying on such an ecosystem through Silverlake Axis. An IBM partner, Silverlake Axis collaborates with clients to build hybrid environments, connecting essential workloads to the cloud to maximize the value of their existing infrastructure investments.

In Malaysia, the Silverlake Axis Integrated Banking Solution (SIBS) for example is highly valued as a matured feature-rich, scalable, and robust Banking Platform with compelling modernization strategies and technology renewal, enabling an organization to be a market leader.

Catherine Lian, Managing Director and Technology Leader of IBM Malaysia also commented that the major banks in the country are using IBM Power servers for their processes with several recipients of the digital banking license in Malaysia also working with Silverlake Axis on this.






Wed, 03 Aug 2022 16:00:00 -0500 en-US text/html https://techwireasia.com/2022/08/ibm-expands-power-10-capabilities/
Killexams : IBM Expands the Power10 Server Family

IBM is expanding its Power10 server line with the introduction of mid-range and scale-out systems to modernize, protect, and automate business applications and IT operations.

The new Power10 servers combine performance, scalability, and flexibility with new pay-as-you-go consumption offerings for clients looking to deploy new services quickly across multiple environments.

The new servers join the popular Power10 E1080 server introduced in September 2021 to deliver a secured, resilient hybrid cloud experience that can be managed with other x86 and multi-cloud management software across clients' IT infrastructure.

This expansion of the IBM Power10 family with the new midrange and scale-out servers brings high-end server capabilities throughout the product line.

Not only do the new systems support critical security features such as transparent memory encryption and advanced processor/system isolation but also leverage the OpenBMC project from the Linux Foundation for high levels of security for the new scale-out servers. 

Highlights of the announcements include:

  • New systems: The expanded IBM Power10 portfolio, built around the next-generation IBM Power10 processor with 2x more cores and more than 2x memory bandwidth than previous Power generations, now includes the Power10 Midrange E1050, delivering record-setting 4-socket compute1, Java2, and ERP3 performance capabilities. New scale-out servers include the entry-level Power S1014, as well as S1022, and S1024 options, bringing enterprise capabilities to SMBs and remote-office/branch office environments, such as Capacity Upgrade on Demand (CuOD).
  • Cloud on premises with new flexible consumption choices: IBM has recently announced new flexible consumption offerings with pay-as-you-go options and by-the-minute metering for IBM Power Private Cloud, bringing more opportunities to help lower the cost of running OpenShift solutions on Power when compared against alternative platforms. These new consumption models build on options already available with IBM Power Virtual Server to enable greater flexibility in clients' hybrid journeys. Additionally, the highly anticipated IBM i subscription delivers a comprehensive platform solution with the hardware, software and support/services included in the subscription service.
  • Business transformation with SAP: IBM continues its innovations for SAP solutions. The new midrange E1050 delivers scale (up to 16 TB) and performance for a 4-socket system for clients who run BREAKTHROUGH with IBM for RISE with SAP. In addition, an expansion of the premium provider option is now available to provide more flexibility and computing power with an additional choice to run workloads on IBM Power on Red Hat Enterprise Linux on IBM Cloud.

"Today's highly dynamic environment has created volatility, from materials to people and skills, all of which impact short-term operations and long-term sustainability of the business," said Steve Sibley, vice president, IBM Power product management. "The right IT investments are critical to business and operational resilience. Our new Power10 models offer clients a variety of flexible hybrid cloud choices with the agility and automation to best fit their needs, without sacrificing performance, security or resilience."

The expansion of the IBM Power10 family has been engineered to establish one of the industry's most flexible and broadest range of servers for data-intensive workloads such as SAP S/4HANA—from on-premises workloads to hybrid cloud.

IBM now offers more ways to implement dynamic capacity—with metering across all operating environments including IBM i, AIX, Linux and OpenShift supporting modern and traditional applications on the same platforms—as well as integrated infrastructure automation software for improved visibility and management.

The new systems with IBM Power Virtual Server also help clients operate a secured hybrid cloud experience that delivers high performance and architectural consistency across their IT infrastructure. The systems are uniquely designed so as to protect sensitive data from core to cloud, and enable virtual machines and containerized workloads to run simultaneously on the same systems. For critical business workloads that have traditionally needed to reside on-premises, they can now be moved into the cloud as workloads and needs demand. This flexibility can help clients mitigate risk and time associated with rewriting applications for a different platform.

For more information about this news, visit  www.ibm.com.


Mon, 25 Jul 2022 01:01:00 -0500 en text/html https://www.dbta.com/Editorial/News-Flashes/IBM-Expands-the-Power10-Server-Family-154055.aspx
Killexams : Astadia Publishes Mainframe to Cloud Reference Architecture Series

The guides leverage Astadia’s 25+ years of expertise in partnering with organizations to reduce costs, risks and timeframes when migrating their IBM mainframe applications to cloud platforms

BOSTON, August 03, 2022--(BUSINESS WIRE)--Astadia is pleased to announce the release of a new series of Mainframe-to-Cloud reference architecture guides. The documents cover how to refactor IBM mainframes applications to Microsoft Azure, Amazon Web Services (AWS), Google Cloud, and Oracle Cloud Infrastructure (OCI). The documents offer a deep dive into the migration process to all major target cloud platforms using Astadia’s FastTrack software platform and methodology.

As enterprises and government agencies are under pressure to modernize their IT environments and make them more agile, scalable and cost-efficient, refactoring mainframe applications in the cloud is recognized as one of the most efficient and fastest modernization solutions. By making the guides available, Astadia equips business and IT professionals with a step-by-step approach on how to refactor mission-critical business systems and benefit from highly automated code transformation, data conversion and testing to reduce costs, risks and timeframes in mainframe migration projects.

"Understanding all aspects of legacy application modernization and having access to the most performant solutions is crucial to accelerating digital transformation," said Scott G. Silk, Chairman and CEO. "More and more organizations are choosing to refactor mainframe applications to the cloud. These guides are meant to assist their teams in transitioning fast and safely by benefiting from Astadia’s expertise, software tools, partnerships, and technology coverage in mainframe-to-cloud migrations," said Mr. Silk.

The new guides are part of Astadia’s free Mainframe-to-Cloud Modernization series, an ample collection of guides covering various mainframe migration options, technologies, and cloud platforms. The series covers IBM (NYSE:IBM) Mainframes.

In addition to the reference architecture diagrams, these comprehensive guides include various techniques and methodologies that may be used in forming a complete and effective Legacy Modernization plan. The documents analyze the important role of the mainframe platform, and how to preserve previous investments in information systems when transitioning to the cloud.

In each of the IBM Mainframe Reference Architecture white papers, readers will explore:

  • Benefits, approaches, and challenges of mainframe modernization

  • Understanding typical IBM Mainframe Architecture

  • An overview of Azure/AWS/Google Cloud/Oracle Cloud

  • Detailed diagrams of IBM mappings to Azure/AWS/ Google Cloud/Oracle Cloud

  • How to ensure project success in mainframe modernization

The guides are available for download here:

To access more mainframe modernization resources, visit the Astadia learning center on www.astadia.com.

About Astadia

Astadia is the market-leading software-enabled mainframe migration company, specializing in moving IBM and Unisys mainframe applications and databases to distributed and cloud platforms in unprecedented timeframes. With more than 30 years of experience, and over 300 mainframe migrations completed, enterprises and government organizations choose Astadia for its deep expertise, range of technologies, and the ability to automate complex migrations, as well as testing at scale. Learn more on www.astadia.com.

View source version on businesswire.com: https://www.businesswire.com/news/home/20220803005031/en/

Contacts

Wilson Rains, Chief Revenue Officer
Wilson.Rains@astadia.com
+1.877.727.8234

Wed, 03 Aug 2022 02:00:00 -0500 en-US text/html https://finance.yahoo.com/news/astadia-publishes-mainframe-cloud-reference-140000599.html
Killexams : International Business Machines Co. (NYSE:IBM) Shares Sold by Great Lakes Advisors LLC

Great Lakes Advisors LLC lowered its holdings in shares of International Business Machines Co. (NYSE:IBMGet Rating) by 2.1% in the first quarter, according to the company in its most accurate Form 13F filing with the Securities and Exchange Commission. The fund owned 13,651 shares of the technology company’s stock after selling 296 shares during the period. Great Lakes Advisors LLC’s holdings in International Business Machines were worth $1,776,000 at the end of the most accurate reporting period.

Other hedge funds and other institutional investors also recently added to or reduced their stakes in the company. IFS Advisors LLC acquired a new position in shares of International Business Machines in the fourth quarter valued at approximately $28,000. Parkside Investments LLC acquired a new position in shares of International Business Machines in the first quarter valued at approximately $31,000. Total Clarity Wealth Management Inc. raised its position in shares of International Business Machines by 537.5% in the fourth quarter. Total Clarity Wealth Management Inc. now owns 255 shares of the technology company’s stock valued at $34,000 after buying an additional 215 shares during the last quarter. SJS Investment Consulting Inc. raised its position in shares of International Business Machines by 39.9% in the first quarter. SJS Investment Consulting Inc. now owns 270 shares of the technology company’s stock valued at $35,000 after buying an additional 77 shares during the last quarter. Finally, Mitsubishi UFJ Morgan Stanley Securities Co. Ltd. acquired a new position in shares of International Business Machines in the fourth quarter valued at approximately $37,000. Institutional investors and hedge funds own 55.22% of the company’s stock.

Analysts Set New Price Targets

IBM has been the subject of a number of accurate analyst reports. StockNews.com upgraded shares of International Business Machines from a “hold” rating to a “buy” rating in a report on Thursday, July 21st. Morgan Stanley lowered their target price on shares of International Business Machines from $157.00 to $155.00 and set an “overweight” rating for the company in a report on Tuesday, July 19th. BMO Capital Markets lowered their target price on shares of International Business Machines from $152.00 to $148.00 in a report on Tuesday, July 19th. Credit Suisse Group decreased their price objective on shares of International Business Machines from $166.00 to $156.00 and set an “outperform” rating for the company in a research note on Wednesday, July 20th. Finally, Bank of America boosted their price objective on shares of International Business Machines from $162.00 to $165.00 and gave the stock a “buy” rating in a research note on Wednesday, April 20th. One equities research analyst has rated the stock with a sell rating, three have given a hold rating and seven have assigned a buy rating to the stock. Based on data from MarketBeat.com, the stock presently has a consensus rating of “Moderate Buy” and an average target price of $146.10.

International Business Machines Price Performance

Shares of IBM stock opened at $132.48 on Monday. The company has a market capitalization of $119.65 billion, a PE ratio of 21.51, a price-to-earnings-growth ratio of 2.00 and a beta of 0.85. The firm has a fifty day simple moving average of $136.61 and a 200-day simple moving average of $132.78. The company has a current ratio of 0.88, a quick ratio of 0.82 and a debt-to-equity ratio of 2.28. International Business Machines Co. has a twelve month low of $114.56 and a twelve month high of $146.00.

International Business Machines (NYSE:IBMGet Rating) last announced its earnings results on Monday, July 18th. The technology company reported $2.31 earnings per share for the quarter, beating the consensus estimate of $2.29 by $0.02. The business had revenue of $15.54 billion during the quarter, compared to the consensus estimate of $15.18 billion. International Business Machines had a net margin of 8.72% and a return on equity of 43.52%. The business’s quarterly revenue was up 9.3% compared to the same quarter last year. During the same period in the prior year, the firm earned $2.33 earnings per share. Equities research analysts anticipate that International Business Machines Co. will post 9.47 earnings per share for the current fiscal year.

International Business Machines Dividend Announcement

The company also recently announced a quarterly dividend, which will be paid on Saturday, September 10th. Stockholders of record on Wednesday, August 10th will be paid a $1.65 dividend. The ex-dividend date is Tuesday, August 9th. This represents a $6.60 annualized dividend and a dividend yield of 4.98%. International Business Machines’s dividend payout ratio (DPR) is presently 107.14%.

Insider Activity

In related news, major shareholder Business Machine International sold 22,301,536 shares of the company’s stock in a transaction on Thursday, May 19th. The shares were sold at an average price of $13.95, for a total value of $311,106,427.20. Following the sale, the insider now directly owns 22,301,536 shares of the company’s stock, valued at $311,106,427.20. The transaction was disclosed in a filing with the Securities & Exchange Commission, which is available at this hyperlink. Insiders own 0.04% of the company’s stock.

International Business Machines Profile

(Get Rating)

International Business Machines Corporation provides integrated solutions and services worldwide. The company operates through four business segments: Software, Consulting, Infrastructure, and Financing. The Software segment offers hybrid cloud platform and software solutions, such as Red Hat, an enterprise open-source solutions; software for business automation, AIOps and management, integration, and application servers; data and artificial intelligence solutions; and security software and services for threat, data, and identity.

Recommended Stories

Want to see what other hedge funds are holding IBM? Visit HoldingsChannel.com to get the latest 13F filings and insider trades for International Business Machines Co. (NYSE:IBMGet Rating).

Institutional Ownership by Quarter for International Business Machines (NYSE:IBM)

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Sun, 07 Aug 2022 23:06:00 -0500 admin en text/html https://www.defenseworld.net/2022/08/08/international-business-machines-co-nyseibm-shares-sold-by-great-lakes-advisors-llc.html
Killexams : IBM Expands Power10 Server Family to Help Clients Respond Faster to Rapidly Changing Business Demands

New Power10 scale-out and midrange models extend IBM's capabilities to deliver flexible and secured infrastructure for hybrid cloud environments

ARMONK, N.Y., July 12, 2022 /PRNewswire/ -- IBM (NYSE: IBM) today announced a significant expansion of its Power10 server line with the introduction of mid-range and scale-out systems to modernize, protect and automate business applications and IT operations. The new Power10 servers combine performance, scalability, and flexibility with new pay-as-you-go consumption offerings for clients looking to deploy new services quickly across multiple environments.

IBM Corporation logo. (PRNewsfoto/IBM)

IBM announced an expansion of its Power10 server line with mid-range and scale-out systems.

 Digital transformation is driving organizations to modernize both their applications and IT infrastructures. IBM Power systems are purpose-built for today's demanding and dynamic business environments, and these new systems are optimized to run essential workloads such as databases and core business applications, as well as maximize the efficiency of containerized applications. An ecosystem of solutions with Red Hat OpenShift also enables IBM to collaborate with clients, connecting critical workloads to new, cloud-native services designed to maximize the value of their existing infrastructure investments.

The new servers join the popular Power10 E1080 server introduced in September 2021 to deliver a secured, resilient hybrid cloud experience that can be managed with other x86 and multi-cloud management software across clients' IT infrastructure. This expansion of the IBM Power10 family with the new midrange and scale-out servers brings high-end server capabilities throughout the product line. Not only do the new systems support critical security features such as transparent memory encryption and advanced processor/system isolation, but also leverage the OpenBMC project from the Linux Foundation for high levels of security for the new scale-out servers.  

Highlights of the announcements include:

  • New systems: The expanded IBM Power10 portfolio, built around the next-generation IBM Power10 processor with 2x more cores and more than 2x memory bandwidth than previous Power generations, now includes the Power10 Midrange E1050, delivering record-setting 4-socket compute1, Java2, and ERP3 performance capabilities. New scale-out servers include the entry-level Power S1014, as well as S1022, and S1024 options, bringing enterprise capabilities to SMBs and remote-office/branch office environments, such as Capacity Upgrade on Demand (CuOD).
  • Cloud on premises with new flexible consumption choices: IBM has recently announced new flexible consumption offerings with pay-as-you-go options and by-the-minute metering for IBM Power Private Cloud, bringing more opportunities to help lower the cost of running OpenShift solutions on Power when compared against alternative platforms. These new consumption models build on options already available with IBM Power Virtual Server to enable greater flexibility in clients' hybrid journeys. Additionally, the highly anticipated IBM i subscription delivers a comprehensive platform solution with the hardware, software and support/services included in the subscription service.
  • Business transformation with SAP®: IBM continues its innovations for SAP solutions. The new midrange E1050 delivers scale (up to 16 TB) and performance for a 4-socket system for clients who run BREAKTHROUGH with IBM for RISE with SAP. In addition, an expansion of the premium provider option is now available to provide more flexibility and computing power with an additional choice to run workloads on IBM Power on Red Hat Enterprise Linux on IBM Cloud.

"Today's highly dynamic environment has created volatility, from materials to people and skills, all of which impact short-term operations and long-term sustainability of the business," said Steve Sibley, Vice President, IBM Power Product Management. "The right IT investments are critical to business and operational resilience. Our new Power10 models offer clients a variety of flexible hybrid cloud choices with the agility and automation to best fit their needs, without sacrificing performance, security or resilience."

The expansion of the IBM Power10 family has been engineered to establish one of the industry's most flexible and broadest range of servers for data-intensive workloads such as SAP S/4HANA – from on-premises workloads to hybrid cloud. IBM now offers more ways to implement dynamic capacity – with metering across all operating environments including IBM i, AIX, Linux and OpenShift supporting modern and traditional applications on the same platforms – as well as integrated infrastructure automation software for improved visibility and management.

The new systems with IBM Power Virtual Server also help clients operate a secured hybrid cloud experience that delivers high performance and architectural consistency across their IT infrastructure. The systems are uniquely designed so as to protect sensitive data from core to cloud, and enable virtual machines and containerized workloads to run simultaneously on the same systems. For critical business workloads that have traditionally needed to reside on-premises, they can now be moved into the cloud as workloads and needs demand. This flexibility can help clients mitigate risk and time associated with rewriting applications for a different platform.

"As organizations around the world continue to adapt to unpredictable changes in consumer behaviors and needs, they need a platform that can deliver their applications and insights securely where and when they need them," said Peter Rutten, IDC Worldwide Infrastructure Research Vice President. "IBM Power continues its laser focus on helping clients respond faster to dynamically changing environments and business demands, while protecting information security and distilling new insights from data, all with high reliability and availability."

Ecosystem of ISVs and Channel Partners Enhance Capabilities for IBM Power10

Critical in the launch of the expanded Power10 family is a robust ecosystem of ISVs, Business Partners, and lifecycle services. Ecosystem partners such as SVA and Solutions II provide examples of how the IBM Ecosystem collaborates with clients to build hybrid environments, connecting essential workloads to the cloud to maximize the value of their existing infrastructure investments:

"SVA customers have appreciated the enormous flexibility of IBM Power systems through Capacity Upgrade On-Demand in the high-end systems for many years," said Udo Sachs, Head of Competence Center Power Systems at SVA. "The flexible consumption models using prepaid capacity credits have been well-received by SVA customers, and now the monthly pay-as-you-go option for the scale-out models makes the platform even more attractive. When it comes to automation, IBM helps us to roll out complex workloads such as entire SAP landscapes at the push of a button by supporting Ansible on all OS derivatives, including AIX, IBM i and Linux, as well as ready-to-use modules for deploying the complete Power infrastructure."

"Solutions II provides technology design, deployment, and managed services to hospitality organizations that leverage mission critical IT infrastructure to execute their mission, often requiring 24/7 operation," said Dan Goggiano, Director of Gaming, Solutions II. "System availability is essential to maintaining our clients' revenue streams, and in our experience, they rely on the stability and resilience of IBM Power systems to help solidify their uptime. Our clients are excited that the expansion of the Power10 family further extends these capabilities and bolsters their ability to run applications securely, rapidly, and efficiently." 

For more information on IBM Power and the new servers and consumption models announced today, visit: https://www.ibm.com/it-infrastructure/power

About IBM

IBM is a leading global hybrid cloud and AI, and business services provider, helping clients in more than 175 countries capitalize on insights from their data, streamline business processes, reduce costs and gain the competitive edge in their industries. Nearly 3,800 government and corporate entities in critical infrastructure areas such as financial services, telecommunications and healthcare rely on IBM's hybrid cloud platform and Red Hat OpenShift to affect their digital transformations quickly, efficiently, and securely. IBM's breakthrough innovations in AI, quantum computing, industry-specific cloud solutions and business services deliver open and flexible options to our clients. All of this is backed by IBM's legendary commitment to trust, transparency, responsibility, inclusivity, and service. For more information, visit www.ibm.com.

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1Comparison based on best performing 4-socket systems (IBM Power E1050 3.15-3.9 GHz, 96 core and Inspur NF8480M6 2.90 GHz, Intel Xeon Platinum 8380H) using published results at https://www.spec.org/cpu2017/results/rint2017.html as of 22 June 2022. For more information about SPEC CPU 2017, see https://www.spec.org/cpu2017/.

2Comparison based on best performing 4-socket systems (IBM Power E1050 3.15-3.9 GHz, 96 core; and Inspur NF8480M6 2.90 GHz, Intel Xeon Platinum 8380H) using published results at https://www.spec.org/cpu2017/results/rint2017.html as of 22 June 2022. For more information about SPEC CPU 2017, see www. http:/spec.org/cpu2017

3Comparison based on best performing 4-socket systems (1) IBM Power E1050; two-tier SAP SD standard application benchmark running SAP ERP 6.0 EHP5; Power10 2.95 GHz processor, 4,096 GB memory, 4p/96c/768t, 134,016 SD benchmark users, 736,420 SAPS, AIX 7.3, DB2 11.5,  Certification # 2022018  and (2) Dell EMC PowerEdge 840; two-tier SAP SD standard application benchmark running SAP ERP 6.0 EHP5; Intel Xeon Platinum 8280 2.7 GHz, 4p/112c/224t, 69,500 SD benchmark users (380,280 SAPS), SUSE Linux Enterprise Server 12 and SAP ASE 16, Certification # 2019045. All results can be found at sap.com/benchmark Valid as of 7 July 2022. 

Contact:
Ben Stricker
ben.stricker@ibm.com

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SOURCE IBM

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