🚀 Excited to announce Elastic Distributed Training is now on Anyscale! 🔍 With Elastic Training, you’ll see up to 60% lower cloud costs using spot instances and faster training with uninterrupted progress, even as computational resources come and go during training. Elastic training adjusts to dynamic computational resources during the training process. Training can recover from spot instances preemptions and hardware failures. Instead of waiting potentially hours for a fixed number of GPUs to be available, training can continue on the resources that are already available. ⚒ You can try this out on Anyscale with minimal code changes. This includes a simple one line code change to specify (min_workers, max_workers) as a tuple instead of a fixed worker group size and adding checkpointing. Read more in our announcement: https://lnkd.in/gK64MEiS
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Another great step here. Cloud costs are the big package when training models - spot instances can greatly decrease these but not all frameworks can handle them. Ray can.
🚀 Excited to announce Elastic Distributed Training is now on Anyscale! 🔍 With Elastic Training, you’ll see up to 60% lower cloud costs using spot instances and faster training with uninterrupted progress, even as computational resources come and go during training. Elastic training adjusts to dynamic computational resources during the training process. Training can recover from spot instances preemptions and hardware failures. Instead of waiting potentially hours for a fixed number of GPUs to be available, training can continue on the resources that are already available. ⚒ You can try this out on Anyscale with minimal code changes. This includes a simple one line code change to specify (min_workers, max_workers) as a tuple instead of a fixed worker group size and adding checkpointing. Read more in our announcement: https://lnkd.in/gK64MEiS
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🚀 Here's A Simple Hack For Reducing AWS Storage Costs by 20% and Boosting Performance . As AWS has so many services and announcements, it's easy to miss out on updates that can make a a significant difference in performance and cost-efficiency. . I recently encountered a throughput throttling issue with an OpenSearch cluster that led me to uncover a simple yet impactful "hack" for AWS users. . . The root of the issue? . The cluster was using gp2 volumes - It was a decent choice years ago but somewhat outdated today. . I was surprised how the cluster was configured with the old generation gp2 instead of gp3, as it was a recently built OpenSearch domain. . Interestingly, despite AWS gp3 volumes being available for nearly 4 years, offering better performance and cost savings, they're not the default choice in Terraform configurations. . If you don't specify volume_type, you likely don't take advantage of these benefits. . Why switch to gp3? . Upon switching to gp3 volumes, I observed: 🔹 An instant reduction in storage costs by 20% 🔹 Significantly improved throughput, eliminating previous bottlenecks . The switch is straightforward but requires explicit action. In your Terraform configuration, ensure you specify the volume_type as gp3 to leverage these advantages. . This minor tweak can lead to noticeable improvements in both cost and performance. . For those using AWS, particularly in combination with Terraform, reviewing and updating your volume types could be a quick win for your projects. #AWSTips #PerformanceOptimization #CostEfficiency #AWScommunity
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front End Developer | HTML | CSS | JavaScript | Bootstrap | Artificial Intelligence Researcher | Student at Lahore Leads University -City Camp
Creating LLMs requires infrastructure/hardware supporting many GPUs (on-prem or Cloud), a big text corpus of at least 5000 GBs, language modeling algorithms, training on datasets, and deploying and managing the models. An ROI analysis must be done before developing and maintaining bespoke LLMs software.
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Hey everyone! Today, I wanted to take a deeper dive into a specific service: Amazon S3 (Simple Storage Service). As someone transitioning from finance, data storage is a crucial concept. S3 offers incredibly scalable and secure object storage, making it perfect for various workloads. From backups and archives to hosting static website content, S3 seems like a powerful tool in any cloud engineer's arsenal. Here's what particularly interests me about S3: Scalability: S3 automatically scales to meet your storage needs, no matter how big or small your data becomes. Durability: Data stored in S3 is replicated across multiple geographically dispersed facilities, ensuring high availability and durability. Cost-Effectiveness: S3 offers a pay-as-you-go pricing model, making it an economical storage solution. I'm still in the learning phase, but I'd love to hear from the community! What are your experiences using S3 for cloud projects? Are there any cool features or functionalities I should explore further? Any recommendations for additional resources on S3? #cloudengineering #aws #solutionsarchitect #learningjourney #cloud #programming #s3
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Another bad-weather weekend is spent on training :) This time it is about the Quantum Computing Service of AWS. You can use Amazon Braket to accelerate scientific discovery with tools for algorithm development and support from the AWS Cloud Credit for Research Program or bring software for quantum computing to market rapidly with Amazon Braket’s SDK. View my verified achievement from Amazon Web Services (AWS). #aws #cloud #quantumcomputing #braket
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🤩 I’m happy to share that I’ve obtained a new badge: Level 3: GenAIus Registries from Google! Google #GoogleCloud #CloudComputing #CloudTechnology #CloudSkills #TechEducation #GoogleCloudPlatform #GCP #CloudCertifications #DigitalTransformation #CloudSolutions #TechSkills #ProfessionalDevelopment #TechTraining #CareerAdvancement
Level 3: GenAIus Registries
cloudskillsboost.google
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mhoye on Mastodon gets it absolutely right 🙃 90's computing: documentation is a waste of time, learn to read code. 2000's computing: we value working software over comprehensive documentation. 2010's computing: SAAS API RPC CLOUD warrgarble 2020's computing: You have more CPU in your lap and maybe your pocket than existed in the world in 1990, an impossibly powerful math furnace at your immediate disposal, at a whim. Learning the details of how to put it to your purposes is a sheer cliff face for some mysterious, indiscernible reason.
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Quantum curious? Check out this FREE quantum computing training session from Amazon's Braket team. #amazonwebservices #amazonbraket #quantumcomputing
🎓 It's our last training session for 2023! Sign up for our *free* quantum computing training session in December. Over 6 hours, you'll get hands-on with QPUs from IonQ, Rigetti Computing, QuEra Computing Inc. and Oxford Quantum Circuits on Amazon Braket via Amazon Web Services (AWS) On the second day, we will be recapping all the quantum announcements and customer stories from re:Invent 2023. There'll be new content even for our customers who have attended these training workshops before 😎 Dates - Tue 12 and Wed 13 December Time - 7am-10am US Pacific Standard Time / 4pm-7pm Central European Time Registration link - https://lnkd.in/g3bq87MV #quantumcomputing #aws #training #certificationcourse #cloudcertification #cloudcertified #quantum
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Just finished the course “Cloud Quantum Computing Essentials” by Lynn Langit! I have taken a lot of online courses on Quantum Computing and this is a great starting point to understand the different players in the Quantum Computing Arena and learn the fundamentals of working with Quantum Hardware. https://lnkd.in/ea9F-3tC #cloudcomputing #quantumcomputing.
Certificate of Completion
linkedin.com
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If you are using AWS RDS databases, see my new article on choosing the most cost-effective volume type. (Hint: It should probably be gp3) #aws #rds #ebs https://lnkd.in/dGHk8P4e
RDS Storage: GP3, GP2 and Provisioned IOPS Cost Comparison
engineering.doit.com
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