Noch muss technisch bewiesen werden, dass die 5G-Wellenform per Satellit übertragen werden kann. Doch es gibt große Pläne für ein weltweites 5G-Netz. (Satelliten, Technologie)
Quelle: Golem
Bis zu 500 US-Dollar günstiger: Seit Wochen fallen die Preise für Grafikkarten, weshalb Nvidia bei seinen Founder’s Editions nun nachzieht. (Nvidia Ampere, Grafikhardware)
Quelle: Golem
Das Start-up Lemo hat uns den Prototyp für eine leichte, preiswerte Kombination aus Fahrrad und Pedelec gezeigt. (E-Bike, Akku)
Quelle: Golem
Eine günstige RISC-V-Platine zeigt, dass damit die Nachfolge von ARM angetreten werden kann. Bis dahin müssen Bastler aber noch Fehler in Kauf nehmen. Von Sebastian Grüner (RISCV, Server)
Quelle: Golem
Ein britischer Gesetzentwurf verlangt eine Chatkontrolle auch bei verschlüsselten Nachrichten – mit drakonischen Strafen bei Nichtbeachtung. (Chatkontrolle, Instant Messenger)
Quelle: Golem
Die animierte Star-Trek-Serie Lower Decks geht in die dritte Runde: Ab dem 25. August startet die neue Staffel mit zehn Folgen. (Star Trek, Amazon)
Quelle: Golem
Anders als AWS mit seinen eigenen Graviton-Chips setzt Google auf die ARM-Server-Chips von Ampere – wie der Rest der Konkurrenz. (Google, Prozessor)
Quelle: Golem
In ice hockey’s earlier days, National Hockey League (NHL) coaches made their most important decisions based on gut instincts. Today, experience and instincts are still vital, but NHL coaches now have another essential tool at their disposal: powerful data analytics. Before and after every game, coaches and even players meticulously pore over game data and review detailed statistics to improve performance and strategy. And while this is a win for the NHL, higher-end data analytics tools have typically been out of reach for youth hockey teams largely because capturing game performance data on the ice is expensive, complicated, and time consuming.We built Drive Hockey Analytics to democratize pro-level analytics and help young players develop their gameplay and build a higher hockey IQ. Coaches and parents can now easily and affordably track 3,000 data points per second from players, sticks, and pucks. Drive Hockey Analytics—which takes 15 minutes to set up at the rink after initial calibration—converts these raw data points into actionable statistics and insights to improve player performance in real time and boost post-game training.Scaling a market-ready stick and puck tracking platform on Google CloudDrive Hockey Analytics began as an engineering project in the MAKE+ prototype lab of the British Columbia Institute of Technology (BCIT). We quickly realized that we couldn’t transform Drive Hockey Analytics into a market-ready stick and puck tracking platform without shifting more resources to R&D. After meeting with the dedicated Google Startup Success Managers from theGoogle for Startups Cloud Program, with this support, we decided to migrate from AWS toGoogle Cloud so our small team could reduce IT costs and accelerate time to market. Google Cloud solutions make everything easier to build, scale, and secure. We immediately took advantage of Google Cloud’s highly secure-by-design infrastructure to implement robust user authentication and institute strict privacy controls to comply with the Children’s Online Privacy Protection Act (COPPA). In just days, we enabled coaches and players to access individual analytics dashboards and more securely share key statistics such as speed, acceleration, agility and edgework, zone time, positioning, among many others with teammates and family.We also separated performance and personalstorage data on Google Cloud, encrypted containers withGoogle Kubernetes Engine (GKE), and wrote third-party applications and pipelines that autoscale withSpark on Google Cloud. These processes could have taken us weeks or even months if we had to manually design and integrate all these security capabilities on our own.To build our interactive player analytics engine, we leveragedTensorFlow,BigQuery, andMongoDB Atlas on Google Cloud. With the simple and flexible architecture offered in Google Cloud, we quickly moved from concept to code, and from code to state-of-the-art predictive models. We now collect and analyze thousands of data points every second to identify key performance metrics, break-out game intelligence, and deliver actionable recommendations. Coaches and players can leverage this data to increase team possession of the puck, optimize player positions, reduce shot attempts, and score more goals.In the future, we plan to explore additional Google products and services such asGoogle Cloud Tensor Processing Units (TPUs),Google Cloud Endpoints for OpenAPI, andGoogle Ads. These solutions will enable us to further expand our ML stack, leverage streaming data from wearables and cameras, and reach new markets.Bringing pro-level sports analytics to youth hockeyThe Startup Success team has been instrumental in helping us rapidly transform Drive Hockey Analytics from a university engineering project into a top shelf player and puck tracking system. Their guidance and responsiveness are amazing, with a human touch that stands out compared to services from other technology providers. We especially want to highlight the Google Cloud research credits that help us affordably explore new solutions to address extremely large dataset challenges. Thanks to these credits, we successfully process thousands of data points in streams and batches, apply ML-driven logic, and run resource-efficient queries. Google Cloud research credits also give us access to dedicated startup experts, managed compute power, vast amounts of secure storage, and potential for joining the Google Cloud Marketplace.Demand for Drive Hockey Analytics continues to grow, and we constantly evolve our platform based on input from youth teams and coaches. We’re looking to go fully to market in 2023. With Drive Hockey Analytics, youth teams are putting on their mitts and taking control of the puck as they improve real-time player performance and help their team count more wins. We can’t wait to see what we accomplish next as we continue transforming dusters into barnburners by democratizing advanced analytics that were once only available to pro-sports teams.If you want to learn more about how Google Cloud can help your startup, visit our pagehere to get more information about our program, andsign up for our communications to get a look at our community activities, digital events, special offers, and more.Related ArticleBlack Kite runs millions of cyber-risk assessments at scale on Google CloudLearn how Black Kite flawlessly runs millions of cyber-risk assessments on Google Cloud.Read Article
Quelle: Google Cloud Platform
Organizations are driving the complete transformation of their business by inventing new ways to accomplish their objectives using the cloud; from making core processes more efficient, to improving how they reach and better serve their customers, to achieving insights through data that fuel innovation. Cloud infrastructure belongs at the center of every organization’s transformation strategy. We see a vast landscape of opportunity to innovate in our cloud’s core capabilities that will have long-standing impact on the speed and simplicity of building solutions on Google Cloud. From data management and machine learning to security and sustainability, we continue to invest deeply in infrastructure innovation that generates value from the foundation upward. We focus on three defining attributes of our infrastructure that help our customers accelerate through innovation:Optimized: Customers want solutions that meet their specific needs. They want to build and run apps where they need them, tailored for popular workloads, industry solutions, and for specific outcomes whether it is high performance, cost savings, or a balance of both. Their workloads should just run better on Google Cloud.Transformative: Transformation is more than “lifting and shifting” infrastructure to the cloud for cost saving and convenience. Transformative infrastructure integrates the best of Google’s AI and ML capabilities to drive faster innovation, while meeting the most stringent security, sovereignty, and compliance needs.Easy: As cloud platforms become more versatile, they can become very complex to adopt and operate. Reducing your operational burden is possible with an easy-to-use cloud platform. Our customers often tell us that Google Cloud makes complex tasks seem simple, and this is a product of intentional engineering. Google’s 20+ years of technology leadership is built on a culture of innovation and focus on our customers. Here are some examples of new innovation we are bringing in these areas. Solutions that are optimized for what matters most to youLet’s start with optimizing for price-performance. Last year, we launched Tau VMs optimized for cost-effective performance of scale-out workloads. Tau T2D leapfrogged every leading public cloud provider in both performance and total cost of ownership delivering up to 42% better price performance versus comparable VMs from any other leading cloud. Today, we are delighted to announce that we are offering more choice to customers, with the addition of Arm-based machines to the Tau VM family. Powered by Ampere® Altra® Arm-based processors, T2A VMs deliver exceptional single-threaded performance at a compelling price, making them ideal for scale-out, cloud-native workloads. Developers now have the option of choosing the optimal architecture to test, develop and run their workloads.Cost optimization is a major goal for many of our customers. Spot VMs enable you to take advantage of our idle machine cycles at deep discounts with a guaranteed 60% off and up to 91% savings off on-demand pricing. These are the perfect choice for batch jobs and fault-tolerant workloads in high performance computing, big data and analytics. Customers told us that they would like to see less variability and more predictability in the pricing of Spot VMs. We have heard you loud and clear. Our Spot VMs offer the least variability (once per month price changes) and more predictability in pricing compared to other leading clouds. Optimizing for global scale is critical to meet the high demands of today’s consumers — especially when it comes to video streaming. Launched in May 2022, Media CDN is optimized to deliver immersive video streaming experience at a global scale. Available in more than 1,300 cities, Media CDN leverages the same infrastructure that YouTube uses to deliver content to over 2 billion users around the world. Customers including U-NEXT and Stan have quickly rolled out Media CDN to deliver a modern, high quality experience to their viewers. Another emerging opportunity is the rise of distributed systems and distributed workers, and the ability to build and run apps wherever needed. With Google Distributed Cloud, we now extend Google Cloud infrastructure and services to different physical locations (or distributed environments) including on premises or co-location data centers and a variety of edge environments. Anthos powers all Google Distributed Cloud offerings, to deliver a common control plane for building, deploying and running your modern containerized applications at scale, wherever you choose.For greater choice, we have designed Google Distributed Cloud as a portfolio of hardware, software, and services with multiple offerings to address the specific requirements of your workloads and use cases. You can choose from our Edge, Virtual, and Hosted offerings to meet the needs of your business.Driving transformation through AI/ML and securityThe pace of innovation in the field of machine learning continues to accelerate and Google has been a long time pioneer. From Search and YouTube to Play and Maps, ML has helped bring out the best that our products have to offer. We’ve made it a point to make the best of Google available to our customers, and JAX and Cloud TPU v4 are two great examples. JAX is a cutting edge open source ML framework developed by Google researchers. It’s designed to give ML practitioners more flexibility and allow them to more easily scale their models to the largest of scales. We recently made Cloud TPU v4 pods available to all our customers through our new ML hub. This cluster of Cloud TPU v4 pods offers 9 exaflops of peak aggregate performance and runs at 90% carbon-free energy, making it one of the fastest, most efficient, and most sustainable ML infrastructure hubs in the world. Cloud TPU v4 has enabled researchers to train a variety of sophisticated models including natural language processing models and recommender models to name a few. Customers are already seeing the benefits, including Cohere who saw a 70% improvement in training times and LG Research who used Cloud TPU v4 to train their large multi-modal 300 billion parameter model.On the security front, increasing cybersecurity threats has every company rethinking its security posture. Our investments in our planet-scale network that’s secure, performant and reliable is matched with our lead in defining industry wide frameworks and standards to help customers better secure their software supply chain. Google last year introduced SLSA (supply chain levels for software artifacts), an end-to- end framework for ensuring the integrity of artifacts throughout the software supply chain. It is an open-source equivalent of many of the processes we have been implementing internally at Google. We challenge ourselves to enable security without complex configuration or performance degradation. One example of this is our Confidential VMs – where data is stored in the trusted execution environment outside of which it is impossible to view the data or operations performed on it, even with a debugger. Another is Cloud Intrusion Detection System (Cloud IDS), which provides network threat detection built on ML-powered threat analysis which processes over 15 Trillion transactions per day to identify new threats with 4.3M unique security updates made each day. With the highest possible rating of AAA by CyberRatings.org, Cloud IDS has proven efficacy to block virtually all evasions. Developer-first ease of useMaking your transformation journey simpler, with easy-to-use tools to accelerate your innovation is our priority. Today, we are introducing Batch in preview, a fully managed job scheduler to help customers run thousands of batch jobs with just a single command. It’s easy to set up, and supports throughput oriented workloads including those requiring MPI libraries. Jobs run on auto-scalable resources, giving you more time to work on the greatest areas of value. This improves the developer experience for executing HPC, AI/ML, and data processing workloads such as genomics sequencing, media rendering, financial risk modeling, and electronic design automation.Continuing innovation for greater ease, we recently announced the availability of the new HPC toolkit. This is an open source tool from Google Cloud that enables you to easily create repeatable, turnkey HPC clusters based on proven best practices, in minutes. It comes with several blueprints and broad support for third party components such as the Slurm scheduler and Intel DAOS and DDN Lustre storage. System performance and awareness of what infrastructure is doing is closely tied to security, but to do this well, it needs to be easy. We recently introduced Network Analyzer to help customers transform reactive workflows into proactive processes and reduce network and service downtime by automatically monitoring VPC network configurations. Network Analyzer is part of our Network Intelligence Center, providing a single console for Google Cloud network observability, monitoring, and troubleshooting. This is just a sample of what we are doing in Google Cloud to provide infrastructure that gives customers the freedom to securely innovate and scale from on-premises, to edge, to cloud on an easy, transformative, and optimized platform. To learn more about how customers such as Broadcom and Snap are using Google Cloud’s flexible infrastructure to solve their biggest challenges, be sure to watch our Infrastructure Spotlight event, aired today.
Quelle: Google Cloud Platform
Organizations that are developing ever larger, scale-out applications will leave no stone unturned in their search for a compute platform that meets their needs. For some, that means looking to the Arm® architecture. Known for delivering excellent performance per watt efficiency, Arm-based chips are already ubiquitous in mobile devices, and have proven themselves for supercomputing workloads. At Google Cloud, we’re also excited about using Arm chips for the next generation of scale-out, cloud-native workloads.Last year, we added Tau VMs to Compute Engine, offering a new family of VMs optimized for cost-effective performance for scale-out workloads. Today we are thrilled to announce the Preview release of our first VM family based on the Arm architecture, Tau T2A. Powered by Ampere® Altra® Arm-based processors, T2A VMs deliver exceptional single-threaded performance at a compelling price. Tau T2A VMs come in multiple predefined VM shapes, with up to 48 vCPUs per VM, and 4GB of memory per vCPU. They offer up to 32 Gbps networking bandwidth and a wide range of network attached storage options, making Tau T2A VMs suitable for scale-out workloads including web servers, containerized microservices, data-logging processing, media transcoding, and Java applications.Google Cloud customers and developers now have the option of choosing an Arm-based Google Cloud VM to test, develop and run their workloads on the optimal architecture for their workload. Several of our customers have had private preview access to T2A VMs for the last few months and have had a great experience with these new VMs. Below is what few of them have to say about T2A VMs.“Our drug discovery research at Harvard includes several compute-intensive workloads that run on SLURM using VirtualFlow1. The ability to run our workloads on tens of thousands of VMs in parallel is critical to optimize compute time. We ported our workload to the new T2A VM family from Google and were up and running with minimal effort. The improved price-performance of the T2A will help us screen more compounds and therefore discover more promising drug candidates.” – Christoph Gorgulla, Research Associate, Harvard University“In recent years, we have come to rely on Arm-based servers to power our engineering activity at lower cost and higher performance compared to legacy environments. The introduction of the Arm Neoverse N1-based T2A instance allows us to diversify our use of cloud compute on Arm-based hardware and leverage the Google Compute Engine to build the exact virtual machine types we need, with the convenience of Google Kubernetes Engine for containerized workloads.” – Mark Galbraith, Vice President, Productivity Engineering, Arm.Ampere Computing has been a key partner for Google Cloud and delivering this VM. “Ampere® Altra® Cloud Native Processors were designed from the ground up to meet the demands of modern cloud applications,” said Jeff Wittich, Chief Product Officer, Ampere Computing. “Our close collaboration with Google Cloud has resulted in the launch of the new price-performance optimized Tau T2A instances, which enable demanding scale-out applications to be deployed rapidly and efficiently.”Integration with Google Cloud services Google Cloud is ramping up its support for Arm. T2A VMs support most popular Linux operating systems such as RHEL, CentOS, Ubuntu, and Rocky Linux. In addition, T2A VMs also support Container-optimized OS to bring up Docker containers quickly, efficiently and securely. Further, developers building applications on Google Cloud can already use several Google Cloud services with T2A VMs — with more coming later this year: Google Kubernetes Engine – Google Kubernetes Engine (GKE) is the leading platform for organizations looking for advanced container orchestration. Starting today, GKE customers can run their containerized workloads using the Arm architecture on T2A. Arm nodes come packed with key GKE features, including the ability to run in GKE Autopilot mode for a hands-off experience. Read more about running your Arm workloads with GKE here. Batch – Our newly launched Batch service supports T2A. As of today users will be able to run batch jobs on T2A instances to optimize their cost of running workloads.Dataflow – Dataflow is a fully managed streaming analytics service that minimizes latency, processing time, and cost through autoscaling and batch processing. You can now use T2A VMs with your Dataflow workloads.Extensive ISV partner ecosystemWhile Arm chips are relative newcomers to data center workloads, there’s already a robust ecosystem of ISV support for Tau T2A VMs. In fact, Ampere lists more than 100 applications, databases, cloud-native software and programming languages that are already running on Ampere-based T2A VMs, with more being added all the time. Further, ISV partners that have validated their solutions on T2A VMs have been impressed by the ease with which they were able to port their software to Tau T2A VMs. “Momento’s serverless cache enables developers to accelerate database and application performance at scale. Over the past few months, we have become intimately familiar with Google Cloud’s new T2A VMs. We were pleasantly surprised with the ease of portability to Arm instance from day one. The maturity of the T2A platform gives us the confidence to start using these VMs in production. Innovations like T2A VMs in Google Cloud help us continuously innovate on behalf of our customers.” – Khawaja Shams, CEO, Momento. Learn more about Momento’s T2A experience.“SchedMD’s Slurm open-source workload manager is designed specifically to satisfy the demanding needs of compute-intensive workloads. We are thrilled with the introduction of the T2A VMs on Compute Engine. The introduction of T2A will give our customers more choice of virtual machines for their demanding workload management needs using Slurm.” – Nick Ihli, Director of cloud and Solutions Engineering, SchedMD.”At Rescale, we help our customers deliver innovations faster with high performance computing built for the cloud. We are excited to now offer T2A VMs to our customers, with compelling price-performance to further drive engineering and scientific breakthroughs. With Arm-based VMs on Google Cloud, we are able to offer our customers a larger portfolio of solutions for computational discovery.” – Joris Poort, CEO, Rescale“Canonical Ubuntu is a popular choice for developers seeking a third party server operating system running on Google Cloud, and we are very happy to provide Ubuntu as the guest OS for users of Compute Engine on Google Cloud’s new Arm-based VMs, which supports our most recent long-term supported versions. Once migrated, users will find a completely familiar environment with all the packages and libraries they know and rely on to manage their workloads.” – Alexander Gallagher, VP of Cloud Sales at CanonicalTo help you get started, we’re providing customers, ISV and ecosystem partners access to T2A VMs at no charge for a trial period, to help jumpstart development on Ampere Arm-based processors. When Tau T2A reaches General Availability later this year, we’ll continue to offer a generous trial program that offers up to 8 vCPUs and 32 GB of RAM at no cost.Pricing and availabilityTau T2A VMs are price-performance optimized for your cloud-native applications. A 32vCPU VM with 128GB RAM will be priced at $1.232 per hour for on-demand usage in us-central1. T2A VMs are currently in preview in several Google Cloud regions: us-central (Iowa – Zone A,B,F), europe-west4 (Netherlands – Zone A,B,C) and asia-southeast1 (Singapore – Zone B,C) and will be in General Availability in the coming months. We look forward to working with you as you explore using Ampere Arm-based T2A VMs for your next scale-out workload in the cloud.To learn more about Tau T2A VMs or other Compute Engine VM options, check out our machine types and pricing pages. To get started, go to the Google Cloud Console and select T2A for your VMs.1. https://www.nature.com/articles/s41586-020-2117-zRelated ArticleRun your Arm workloads on Google Kubernetes Engine with Tau T2A VMsWith Google Kubernetes Engine’s (GKE) support for the new Tau VM T2A, you can run your containerized workloads on the Arm architecture.Read Article
Quelle: Google Cloud Platform
