I travel frequently to EMC’s global R&D locations to monitor innovation activities. One of the most common questions I receive is: Do you notice cultural differences in a particular region’s approach to innovation?It is difficult to get an accurate feel for any culture unless you live there for an extended period of time. A more appropriate way of asking the question would be: What are your observations about innovation at EMC’s global locations?I’ve thought about my observations in these areas and tried to come up with a word or two that describes what I’ve witnessed firsthand.China: Cutting EdgeI’ve written several articles that chronicle my own personal experience managing EMC Labs China. Over the past few years, as the high-tech industry has evolved, this team (and EMC China employees in general) has prided itself on education, prototyping, and knowledge transfer of the trends and technologies that are on the precipice of exploding in the industry. In 2007 they began researching cloud computing, followed soon after by “trust in the cloud.” Several years later they were among the first in the company to begin researching Big Data and analytics technologies such as Hadoop. They regularly publish papers and attend conferences on emerging technologies. Employees in all countries collaborate with them, and every year their ideas are chosen as some of the best in the world to implement internally.Egypt: Over-achieversIn May of 2011, three months after the Egyptian revolution, I visited our Cairo facility and was asked to help them build a stronger culture of innovation in the region. I let them know that it could take several years to see tangible results. In less than two years, the employees in Egypt have built a local innovation program which is as mature as any that I’ve seen within the company. They submit more ideas per capita than any geography, and increased their employee idea submission ratio by four times year over year. Six employee ideas were chosen as “best in category,” and one of them was chosen as “best in show.” They opened two cloud-computing labs at local universities (the first in the world that I am aware of) and have strong partnerships with local government initiatives.India: EnthusiasmFor several years at EMC I ran the corporate innovation contest (known as the Innovation Roadmap). I have observed that the enthusiasm for this program (and for innovation in general) in India is unbounded. The numbers bear this out: India has regularly been one of the top three countries in ideas submissions for the last three years running. In addition to increased submission rates (up 24% in 2012), the quality of their submissions is amplified by a quality committee; nearly all ideas are “improved” through a local process created exclusively by local employees. Dozens of ideas originating from employees in India have been selected as finalists over the years.Ireland: Customer-centricOur facility in Cork, Ireland, has long welcomed customer visits. As a result, I’ve witnessed a strong emphasis in Ireland on innovating with EMC’s customers. These customers come from all over Europe on a regular basis. I recall a compliance problem that European customers were having trying to return failed disk drives to EMC. Information leakage concerns resulted in a quick response by employees to create an electronic shredding solution that successfully overcame the problem. Employees at the facility are trained to lead idea-generation sessions. One such session focused on improved first impressions and hospitality for customers visiting the facility.Israel: CollaborativeMany people know that Israel is viewed as one of the most innovative countries in the world (e.g., read the book Start-up Nation). I was excited to visit Israel for the first time last year and witness my co-worker’s approach firsthand. What stood out to me is that local EMC employees function as part of a strong local ecosystem, and augment this with consistent and high-quality knowledge transfer to other geographies within EMC. When my Israeli co-workers hosted EMC’s sixth annual Innovation Conference, the entire building (nearly every floor) was filled with exhibits and ideation from external startups, university partners, local corporations and businesses, and government initiatives. It was extremely impressive.Russia: SpeedWhen we opened our Russia Center of Excellence in 2007, we asked our new co-workers to start building some of the newest and most complex high-tech products that EMC had produced to date. They quickly delivered (e.g., the VNXe and Unisphere products). When they set about to build a local university research ecosystem from scratch, they displayed the same sense of urgency and delivery of results, building one of the most advanced set of research partnerships that EMC has in any region around the world. They have also had success converting fantastic research results (e.g., compression) into functional, shipping code that runs inside certain EMC products. Recent efforts also include a push into the Russian startup market.It’s this last point that has led to an investment into a global innovation analytics framework. The company needs an automated way to keep up with the pace of activities. My colleagues from all of these locales designed centralized innovation repository as a way to share and analyze the massive amount of innovation activities occurring worldwide at EMC. A tool was built using the six-step approach and is taught as part of EMC’s Data Science curriculum.This tool, internally known as GINA (Global Innovation Network Analytics), is another example of cutting-edge, over-achieving, enthusiastic, customer-centric, collaborative, and speedy innovation!
IoT / Edge Computing: IoT is driving server-class computing to move closer to end-devices. Companies of all sizes are undergoing digital transformation to automate their operations and better serve their customers. This is resulting in hybrid/multi-cloud deployments closer to their end-users (customer, employees or devices) either on-prem or at a co-location facility. Similar to the network edge, the accelerators (FPGAs, SMART-NICs, GPUs) play a key role here for acceleration of infrastructure services and for accelerating data processing for AI/ML. 5G Access Edge: The evolution of cellular networks to 5G is resulting in the virtualization and disaggregation of Telco Radio Access Network (RAN) architecture. High-frequency 5G wireless spectrum, distance limitations and increasing cell densities require a centralized RAN architecture where radio signals from multiple cell stations are processed at a centralized location. 3GPP and ORAN industry standards group are defining the architecture and specifications to ensure interoperability across RAN vendors. Centralized RAN processing unit uses standard off-the-shelf servers and virtualization techniques along with accelerators to decouple control plane and data plane processing. Control plane runs on a virtualized server called CU (Central Unit) and data plane processing is done on a standard server (called DU or Distributed Unit) with radio packet processing offloaded to an accelerator card. These accelerator cards are typically an FPGA or a custom ASIC with Time-Sensitive Networking (TSN) and other packet processing capabilities. Software companies like Radisys and Altiostar are delivering RAN control plane software that offloads radio frame processing to accelerator cards. Co-Author: Ramesh Radhakrishnan, Distinguished Engineer, Office of the CTO, Server and Infrastructure Systems at Dell EMCOver the past several years, there has been a growing interest in the use of accelerators on standard servers to improve workload performance. It started with GPUs to accelerate AI/ML and now includes FPGAs, SMART-NICs on servers and other low-power embedded accelerators in end-devices for data analytics, inferencing and machine learning. In this blog, we share our perspective on these new classes of emerging accelerators and the role they will play in the growing adoption of IoT and 5G as workloads get distributed from edge to data center to cloud.The Data Decade will see transformation of the compute landscape and proliferation of acceleration technologiesWith the exponential growth of data, an increasing number of IoT devices at the edge, and every industry going through digital transformation, the future of computing is driven by the need to process data cost-effectively, maximize business value and deliver a return on investment. The Data Decade is leading to architectures that process data close to the source of data generation and only send information over long-haul networks that requires storage or higher-level analysis. Emerging use cases around autonomous vehicles (self-driving cars, drones), smart-city projects, and smart factories (robots, mission critical equipment control) require data processing and decision making closer to the point of data generation due to mission critical, low-latency and near-real time requirements of these deployments.Edge computing architectures are emerging with compute infrastructure and applications distributed across edge to cloud. This trend will lead to a range of compute architectures optimized along different vectors – massively parallel floating-point compute capability in the data center to train complex neural network models (where power is not a concern) to highly power-efficient devices that can infer the deployed neural network models at the edge. This leads to a Cambrian explosion of devices that will be used as part of this cloud-to-edge continuum.On the processor front, in the last ten to fifteen years traditional CPU architectures have evolved to an increasing number of cores and memory, but I/O and memory bandwidth hasn’t kept pace. Scaling memory and I/O bandwidth is critical for processing massive datasets in the data center and real-time streaming at the edge. These factors are leading to the evolution of hardware acceleration in both networking and storage devices to optimize dataflow across CPU, memory and IO subsystems at the overall system level. The growth in data processing has led to use of dedicated accelerators for Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL) workloads. These accelerators perform parallel computation and faster execution of AI jobs compared to traditional CPU architectures. They provide dedicated support for efficient execution of matrix math which dominates ML/DL workloads. Multiple numerical precision modes beyond what is available in CPUs (BFLOAT16, Mixed Precision Floating Point) are available to massively speedup a broad spectrum of AI applications.Below, we take a look at five key areas where accelerators will play a pivotal role. Accelerator technologies play a key role in the rollout of 5G technology and associated services (which include AI, AR/VR and content sharing among others) at every stage of the compute spectrum. AI Workloads / Solutions: In addition to the traditional players for machine learning ASICs (namely Nvidia, Intel and Google), startups are emerging with focus on higher performance, lower power and specific application areas. Some examples are Graphcore, Groq, Hailo Technologies, Wave Computing and Quadric. They are driving optimizations for specific areas such as natural language processing, AR/VR, speech recognition and computer vision. Some of these AI ASICs are focusing on inferencing and getting integrated into end-devices such as autonomous vehicles, cameras, robotics and drones to drive real-time data processing and decision making. 5G Network Edge: The high speed, low latency and increased number of device connections supported by 5G networks are leading to a new set of use cases around AR/VR, gaming, content delivery and content sharing. This requires moving third party applications to the network edge along with network slicing capabilities to distinguish between different types of traffic and associated Service Level Agreements (SLAs). This transforms the telco network edge to become a distributed cloud running third party developer and service provider applications. Moving workloads to the network edge also requires the underlying network and storage infrastructure services to ensure secured network and data storage. Telco VNFs (e.g. EPC, BNG) and network services (e.g. firewalls, load balancers, IPSEC) are moving to the network edge to enable hosting of new workloads. In order to free up the server CPU Cores for third party apps and deliver advanced network security functions (e.g. Deep packet inspection, encryption, network slicing, analytics), the underlying network infrastructure services are being offloaded to accelerator cards called SMART-NICs. These SMART-NICs contain standard NIC functionality coupled with low-power CPU Cores and hardware acceleration blocks for network processing. They also provide a programmable data plane interface for Telco VNFs to offload network data-plane processing in hardware. The 3GPP industry standards group is defining architecture and standards for CUPS (Control Plane and User Plane Separation). Many network adapter companies like Intel, Mellanox, Broadcom, Netronome and emerging startups are focusing on these network acceleration adapters. There are also custom accelerator cards emerging to specifically focus on content caching and video analytics (Gaming, AR/VR). Centralized Data Center / Cloud: Most edge deployments consist of a hybrid / multi-cloud environment where processing is done as a combination of near-real-time processing at the edge and backend processing in a centralized data center or public cloud. A centralized data center (or public cloud) hosts the infrastructure for deep learning, storage and data processing. The deep learning infrastructure is making increasing use of higher-end GPUs and emerging high-performance deep learning ASICs. With increasing network speeds (50G/100G and beyond), persistent memory, high-performance NVMe drives and increasing security requirements (encryption, compression, deep packet inspection, network analytics), the network services are using accelerators to offload network data-plane functions in hardware. This enables all these functions at wire-speed and service-chaining of network services. Software-defined storage stacks are also evolving to make use of accelerators for advanced functions like dedup, erasure coding, compression, encryption and to scale to deliver the higher performance with persistent memory, NVMe drives and high-performance networks.In addition to the above opportunities around accelerators, there is an increasing amount of data being stored on the storage systems. In order to provide intelligent access to data, future storage devices are evolving to be programmable, where FPGA and other hardware acceleration techniques are embedded in the drive subsystem to analyze the data in-place and only provide the result to the application. These drives will have capabilities to run third party code and are commonly referred to as computational storage. It optimizes the data transfer over the network, where large videos and images can be analyzed, and database queries can be performed right where data is stored. Large storage systems are also embedding accelerators, virtualization and cloud-native frameworks in the storage system to process data and host third party analytics applications.This use of hardware acceleration for machine learning, network services and storage services is just the beginning of a change in system-level architecture. The next evolution will drive more optimized data-flows across various accelerators so that data can flow between network, storage and GPUs directly without involving the host x86 CPUs and host memory. This will become increasingly important in future dis-aggregated and composable server architectures wherein a logical server is composed from independent pools of CPUs, memory, network adapters, disk drives, and GPUs connected with a high-performance fabric.Research is underway to enhance machine learning accelerators for capabilities like reinforcement learning and explainable AI. Future ML accelerators will support capabilities to enable localized training at the edge to further improve decision making for localized data sets. Accelerators at the edge also need to account for environmental conditions at the deployment location. Many edge deployments need ruggedized infrastructure as it is either deployed in outside environment (street side, parking lot or outside a building) or in a warehouse environment (e.g. retail, factory). The power, thermal and form factor requirements need to be considered to build the ruggedized infrastructure containing accelerators for edge deployments.The companies that innovate in this system-level architecture for next generation workloads will win in driving customers towards digital transformation, edge and 5G. At Dell EMC, we are heavily focused on this evolving use of accelerators, ruggedized IT infrastructure and system level optimizations. Please see the recent Dell Technologies announcement around PowerEdge XE2420 ruggedized compute platform, Dell EMC Modular Data Center Micro 415 and Dell EMC Streaming Data Platform.To learn more about PowerEdge servers, visit the PowerEdge Servers page, Dell EMC Accelerator Solutions page, Dell EMC Edge Computing Solutions page or join the conversation on Twitter.
Dell Technologies continues to innovate and deliver new solutions for customers as we fully accelerate to meet the Cloud era. With new partnerships with Google Cloud and new Dell Technologies Cloud Platform capabilities, Dell Technologies is helping to unify the application experience across products and technologies. That Cloud-based innovation extends to the Edge with SD-WAN.Dell EMC SD-WAN Solution powered by VMware delivers a set of software-defined tools that can boost application performance and maintain quality of service for mission-critical applications like voice, video conferencing, and VDI. With Cloud-based centralized management, a Cloud network of virtualized gateways, and zero touch deployments, SD-WAN Solution delivers turnkey networking modernization and gives the WAN a much needed boost for supporting today’s Cloud applications. And with many businesses seeing traditional branch workloads now move into home offices for their critical workers, SD-WAN provides quality of service to keep business applications in service while sharing bandwidth with video streaming, social media, and other home traffic.SD-WAN Solution powered by VMware modernizes networking with:Simplicity & Agility – Appliances and software combined in an all-in-one solution, saving you time and money and enabling the rapid deployment of SD-WANPerformance & Efficiency – Boost application performance with software-defined features and Cloud-based management, and gain efficiency to reduce WAN costs up 75%*Scale & Trust – Back your transformation at scale with enterprise-class support, services, and global supply chain from a single vendor- Dell TechnologiesWe’re pleased to announce that SD-WAN Solution has expanded to offer even more choice and flexibility for turnkey WAN modernization. Take a look at our recent updates:Expanding the EdgeNew Dell EMC Edge 620, 640, and 680 models join the successful Edge 600 appliance portfolio, adding even more configuration and bandwidth options for modernization. These appliances feature Intel processors, fast DDR memory, onboard flash storage, and are built specifically for virtualized networking workloads. And like all Dell EMC SD-WAN Solution appliances, they are factory-integrated with VMware Velocloud software, delivering a turnkey solution for transforming networking with SD-WAN. A closer look at the new appliances:Dell EMC Edge 620 – up to 500mbps of performance, for a single virtualized networking function and typical bandwidth usageDell EMC Edge 640 – up to 1gps of performance with extra bandwidth capacity for demanding applications and resourcesDell EMC Edge 680 – up to 2gps of performance, for multiple virtualized networking workloads and high bandwidth utilizationThe expanded Edge portfolio brings even more throughput and performance to branch locations, all delivered in a sleek and compact form factor. End users simply plug the appliances in and IT handles the rest remotely via Cloud-based Centralized Management. No serial number tracking, no on-site visits, no sensitive network information pre-loaded on devices- a true game change!More Software-Defined InnovationsVMware has expanded the software-defined features and capabilities of the Velocloud SD-WAN software.The latest release, 3.4.1, introduces the following:Support for Private SegmentsSyslog Firewall Logging EnhancementMPLS CoS EnhancementThis new update expands upon the impressive list of features introduced in update 3.4, including:Conditional BackhaulStateful FirewallConfigure DSL OptionsEdge ClusteringWi-Fi ImprovementsEnterprise ReportingVMware continues to push forward with SD-WAN, delivering an unmatched set of virtualized functionality to an already impressive set of software-defined innovations. It’s no wonder they’ve been named a leader by Gartner in the Magic Quadrant for Edge Infrastructure two years in a row.**The Dell Technologies AdvantageWith the full backing of Dell’s global supply chain, ProSupport, and PreDeploy services options, SD-WAN Solution makes the adoption and deployment of SD-WAN easy and low risk, no matter how complex the network or location. Select the Edge appliance that best fits your need – from the newly expanded 600 series to 3000 series options for data center and HQ locations – and ship directly to the site.Network Engineers can then access the remote hardware via Centralized Management, and perform all network configuration tasks from there. No flights, no trips, no tracking of serial numbers or the risk of pre-loading devices with sensitive networking information. Deploying Dell EMC SD-WAN Solution powered by VMware is simple, fast, and low risk.Purpose-built appliances from Dell Technologies and leading software from VMware combined in one innovative solution- a truly better together story to power modernization and accelerate networks to meet the challenges of the Cloud era.To learn more about Dell EMC SD-WAN Solution powered by VMware, visit here.Availability and terms vary by region. Contact your sales representative for details.*75% cost saving based on internal VMware calculation of private MPLS at $1,800/month converted to a SD-WAN dual broadband configuration cost of ~$200 per month. Actual savings will vary depending on specific configurations and broadband rates.**Gartner, Magic Quadrant for WAN Edge Infrastructure, 26 November 2019, Jonathan Forest, Mike Toussaint, Neil Rickard. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, express or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
President Joe Biden has ordered the Department of Justice to end its reliance on private prisons and acknowledge the central role the government has played implementing discriminatory housing policies. Biden signed a series of orders and memorandums Tuesday to spotlight the new administration’s effort to make combating racial injustice a central focus of his presidency. The new orders will recommit the federal government to respect tribal sovereignty and disavow discrimination against the Asian American and Pacific Islander community over COVID-19. President Donald Trump frequently used xenophobic language in public comments when referring to the coronavirus.
WASHINGTON (AP) — Former President Donald Trump is rejecting a request by House Democrats to testify under oath for his Senate impeachment trial. Democrats are challenging the former president to explain why he and his lawyers have disputed key factual allegations related to their charge that he incited a violent mob to storm the Capitol. Trump adviser Jason Miller responded Thursday that “the president will not testify in an unconstitutional proceeding.” Trump’s lawyers dismissed the request as a “public relations stunt.” The request from House impeachment managers doesn’t require Trump to appear, but it does warn that any refusal to testify could be used at trial to support arguments for a conviction.
The human loss from the pandemic will not be reflected in the U.S. population count used for divvying up congressional seats among the states. That could save a congressional seat for New York but cost Alabama one. The pandemic’s start and the April 1 reference date used for the nation’s head count were just weeks apart. Because of that, the loss of life from the virus won’t show up in the 2020 census numbers. New York is slotted to get the last of 435 congressional seats, based on population estimates. If the reference date were just a few months later, Alabama would get that last seat.
SOFIA, Bulgaria (AP) — A Bulgarian mountain climber has been found dead during his attempt to reach the peak of the world’s second-tallest mountain, K2. Bulgaria’s Foreign ministry said in a statement that a Pakistani army helicopter crew confirmed the death of 42-year-old Atanas Skatov on Friday. Bulgarian national radio cited the Nepalese organizer of the expedition as saying that Skatov is believed to have fallen while changing ropes during a descent to base camp. Skatov in 2017 became the world’s first vegan to scale the highest mountains on every continent, known as the Seven Summits.