All news with #nvidia tag

🚀 AWS Parallel Computing Service (PCS) now supports Amazon EC2 P6e-GB200 and P6e-GB300 UltraServer instances, enabling large-scale GPU workloads using the NVIDIA Blackwell architecture within Slurm-managed clusters. You can reserve UltraServers via EC2 Capacity Blocks for ML and associate them with a PCS compute node group using an EC2 launch template, while PCS configures Slurm topology automatically. P6e-GB200 offers up to 72 GPUs, 360 petaflops FP8 (no sparsity), and 13.4 TB HBM3e; P6e-GB300 delivers 1.5x GPU memory and FP4 compute versus the GB200. PCS remains a managed Slurm-based service that simplifies building elastic HPC environments with integrated compute, storage, networking, visualization, managed updates, and observability.

🚀Starting today, Amazon EC2 P6-B200 instances accelerated by NVIDIA Blackwell GPUs are available in the Asia Pacific (Mumbai) Region. These instances deliver up to 2x performance versus P5en for AI training and inference and include 8 Blackwell GPUs with 1440 GB of high-bandwidth GPU memory. They offer a 60% increase in GPU memory bandwidth, 5th Gen Intel Xeon processors, and up to 3.2 Tbps of EFAv4 networking, powered by the AWS Nitro System.

🚀 Amazon SageMaker AI now supports serverless customization for Nvidia Nemotron 3 Nano via supervised fine-tuning (SFT) and reinforcement fine-tuning (RFT). This open-weight 30B-parameter model can be deployed and adapted to specific domains and workflows directly within SageMaker. Serverless customization handles infrastructure and training orchestration, enabling teams to focus on data and evaluation while paying only for usage. The feature is available in US East (N. Virginia), US West (Oregon), Asia Pacific (Tokyo), and Europe (Ireland), and can be launched from SageMaker Studio or via the SageMaker Python SDK.

🔒 Google Cloud announces collaboration with Apple to support Apple’s expanded Private Cloud Compute (PCC) systems on Google Cloud, built with Intel and NVIDIA. The effort leverages Google Cloud’s Titanium security architecture and Confidential Computing portfolio, including hardware Trusted Execution Environments, to protect data at rest, in transit, and in use. This layered approach aims to deliver verifiable integrity, no privileged runtime access, and enforceable privacy protections for sensitive AI workloads.

🚀 Amazon EC2 P6-B200 instances powered by NVIDIA Blackwell GPUs are now available in the AWS GovCloud (US-East) Region. These instances deliver up to 2x performance versus P5en for AI training and inference, with 8 GPUs and 1440 GB of high-bandwidth GPU memory. They include 5th Gen Intel Xeon processors, a 60% boost in GPU memory bandwidth, up to 3.2 Tbps EFAv4 networking, and run on the AWS Nitro System for secure scaling.

🔧 AWS Parallel Computing Service (AWS PCS) now offers a PCS‑ready Deep Learning AMI, an AWS‑maintained Amazon Machine Image based on the Deep Learning Base GPU AMI (Ubuntu 24.04). It provides a production‑quality foundation for AI/ML training and HPC with preinstalled, compatibility‑tested infrastructure components such as NVIDIA drivers, CUDA, EFA, Lustre client, PCS Agent, Slurm for PCS, and EFS utilities. Multiple Slurm versions are supported and activate automatically based on cluster configuration, and AWS will regularly update the AMIs for security patches and driver updates. The AMI is available at no additional cost for x86_64 and arm64 in all Regions where AWS PCS is offered.

🔒 At GTC Taipei during COMPUTEX 2026, NVIDIA highlighted its Vera BlueField-4 STX and DOCA innovations designed to secure enterprise AI infrastructure. Modern AI factories combine high-performance compute, distributed storage, Kubernetes, APIs, GPU farms, and sensitive data, creating new security needs. Check Point integrates its AI Factory Firewall with NVIDIA BlueField and DOCA to provide visibility, segmentation, runtime protections, and infrastructure-level policy enforcement across distributed AI environments.

🚀 Amazon announced the general availability of EC2 P6-B200 instances on SageMaker notebook instances in AWS US East (N. Virginia). These instances feature 8 NVIDIA Blackwell GPUs with 1440 GB GPU memory and 5th Gen Intel Xeon processors, offering up to 2x performance versus P5en for AI training. Customers can use them to develop and fine-tune large foundation models interactively in JupyterLab or CodeEditor on SageMaker Studio.

🚀 Amazon SageMaker notebook instances now support EC2 P5.4xl instances powered by NVIDIA H100 Tensor Core GPUs. These instances deliver up to 4x higher performance and up to 40% lower training cost versus prior-generation GPU instances, accelerating development of deep learning and generative AI models. P5.4xl is generally available across multiple AWS regions including US East, US West, Asia Pacific, and South America. Refer to developer guides for setup instructions in JupyterLab and CodeEditor on SageMaker Studio and notebook instances.

🚀 Amazon announces GA of EC2 P5en.48xl instances for SageMaker notebook instances, delivering advanced H200 GPUs paired with 4th Gen Intel Xeon processors. These instances provide increased GPU memory and bandwidth compared to P5, Gen5 PCIe between CPU and GPU, and faster EFA/Nitro networking to boost distributed training and inference. P5en.48xl is available in US East (N. Virginia, Ohio), US West (Oregon), and Asia Pacific (Tokyo) regions. Refer to the developer guides for setup and SageMaker Studio integration.

🚀 Amazon Web Services announces general availability of Amazon EC2 P5en.48xl instances on SageMaker notebook instances. These P5en instances feature 8 H200 GPUs with increased GPU memory and bandwidth versus H100, paired with custom 4th Gen Intel Xeon processors and Gen5 PCIe for higher CPU–GPU bandwidth. They also include third-generation EFA via Nitro v5, offering up to 3200 Gbps and latency improvements over prior P5 instances. P5en.48xl is currently available in US East (N. Virginia, Ohio), US West (Oregon), and Asia Pacific (Tokyo).

🚀 Amazon SageMaker notebook instances now support EC2 P5.4xl instances powered by NVIDIA H100 GPUs. These instances boost deep learning and HPC workloads, offering up to 4x faster time-to-solution and up to 40% lower training cost versus prior GPU generations. P5.4xl is available in multiple AWS regions including US East, US West, Asia Pacific, and South America; see AWS developer guides for setup instructions.

🎮 Amazon GameLift Streams has introduced Generation 6e (G6e) stream classes, delivering enhanced GPU performance for streaming graphically demanding games and applications. The G6e classes use EC2 G6e instances with NVIDIA L40S Tensor Core GPUs and 3rd gen AMD EPYC processors, offering 2x GPU memory and up to 2.9x faster GPU memory bandwidth versus standard Gen6 classes. Two variants — gen6e_pro and gen6e_pro_win2022 — provide a full dedicated NVIDIA L40S GPU with 48 GB memory, suited for AAA-quality streaming at high resolutions. G6e stream classes are available in select AWS Regions including US East, US West, Europe, and Asia Pacific.

🔒 On day one of Pwn2Own Berlin 2026 researchers earned $523,000 exploiting 24 unique zero-days, led by Orange Tsai, who collected $175,000 after chaining four logic flaws to escape the Microsoft Edge sandbox. Windows 11 was rooted three times for new privilege-escalation bugs, and Valentina Palmiotti secured payouts for Red Hat Workstations and an NVIDIA Container Toolkit flaw. The event focuses on enterprise and AI-targeted technologies.

🚀 Imgix serves over 8 billion images and videos daily and has migrated its real-time processing stack to G4 VMs on Google Cloud, powered by NVIDIA RTX PRO 6000 Blackwell GPUs. The move delivered a 50% reduction in median latency and a 5–6× increase in throughput per node without rewriting core application code. Imgix combines nvJPEG, NVENC/NVDEC, custom Vulkan compute shaders and CUDA libraries to accelerate decoding, transformation and encoding, while autoscaling, self-healing GPU management and a 2.5PB GCS cache enable fast, reliable global delivery.

🚀 Amazon now offers P5.48xl EC2 instances in SageMaker Studio notebooks across US West (San Francisco), Asia Pacific (Tokyo, Mumbai, Sydney, Jakarta), and Europe (London, Stockholm). These instances are powered by NVIDIA H100 Tensor Core GPUs and deliver up to 4x performance improvements and up to 40% lower training cost versus prior GPU generations. They are suited for training and serving complex LLMs, diffusion models, and other generative AI and HPC workloads. See the developer guides for setup with JupyterLab and CodeEditor and consult regional pricing for details.

🚀 Amazon announces general availability of EC2 P6-B200 instances in AWS US East (N. Virginia) for use with SageMaker Studio notebooks. These instances feature eight NVIDIA Blackwell GPUs, 1440 GB of high-bandwidth GPU memory, and 5th Generation Intel Xeon (Emerald Rapids) processors, offering up to 2x training performance vs P5en. They enable interactive development and fine-tuning of large foundation models directly in JupyterLab or CodeEditor for generative AI workloads.

🚀 Amazon Web Services has announced general availability of Amazon EC2 P5.4xl instances for SageMaker Studio notebooks, powered by NVIDIA H100 Tensor Core GPUs. These instances offer up to 4x faster time-to-solution versus previous-generation GPU instances and claim up to 40% lower training cost for ML models. They are designed to accelerate training and deployment of demanding DL and HPC workloads, including large language models and diffusion models. P5.4xl is available now in select US, Asia Pacific, and South America regions, with developer guides and pricing details provided.

🚀 Amazon Web Services announced general availability of Amazon EC2 G6 instances for SageMaker Studio notebooks in the Middle East (Dubai) and Asia Pacific (Malaysia). G6 instances pair up to eight NVIDIA L4 Tensor Core GPUs (24 GB each) with third-generation AMD EPYC processors, delivering roughly 2× better deep-learning inference performance than G4dn. These instances support interactive model deployment and training for generative AI fine-tuning, NLP, vision, and recommender workloads. Refer to developer guides for JupyterLab and CodeEditor setup and the pricing page for cost details.

🚀 Amazon Web Services announced general availability of EC2 G6e instances on SageMaker Studio notebooks in Dubai, Tokyo, Seoul, Frankfurt, Stockholm and Spain. G6e instances provide up to 8 NVIDIA L40s Tensor Core GPUs with 48 GB per GPU and 3rd‑generation AMD EPYC processors, delivering up to 2.5× performance versus G5. They target interactive model testing, training and generative AI fine‑tuning, and can host LLMs up to 13B parameters as well as diffusion models for image, video and audio generation. Developer guides cover JupyterLab and CodeEditor setup; pricing is available on the AWS pricing page.