Tag: GPU

Video encoding and transcoding are critical workloads for media and entertainment companies. Delivering high-quality video content to viewers across devices and networks needs efficient and scalable encoding infrastructure. As video resolutions continue to increase to 4K and 8K, GPU acceleration is essential to real-time encoding workflows where parallel encoding tasks are necessary. Although encoding on […]

Introduction In recent years, there’s been a remarkable surge in the adoption of Kubernetes for data analytics and machine learning (ML) workloads in the tech industry. This increase is underpinned by a growing recognition that Kubernetes offers a reliable and scalable infrastructure to handle these demanding computational workloads. Furthermore, a recent wave of Generative AI […]

In today’s fast-paced technological landscape, the demand for accelerated computing is skyrocketing, particularly in areas like artificial intelligence (AI) and machine learning (ML). One of the primary challenges the enterprises face is the efficient utilization of computational resources, particularly when it comes to GPU acceleration, which is crucial for ML tasks and general AI workloads. […]

With the Generative Artificial intelligence (GenAI) and machine learning (ML) surge, GPU-intensive tasks such as machine learning, graphics rendering, and high-performance computing are becoming increasingly prevalent. However, many of these tasks do not always require the full performance and resources of a high-end GPU. This underutilization of GPU resources leads to inefficiencies, increased costs, and […]

Introduction Apache Spark revolutionized big data processing with its distributed computing capabilities, which enabled efficient data processing at scale. It offers the flexibility to run on traditional Central Processing Unit (CPUs) as well as specialized Graphic Processing Units (GPUs), which provides distinct advantages for various workloads. As the demand for faster and more efficient machine […]

Last year, we announced the general availability of the Amazon Elastic Container Service (Amazon ECS)-optimized Bottlerocket AMI. Bottlerocket is an open source project that focuses on security and maintainability, providing a reliable and consistent Linux distribution for hosting container-based workloads. Now, we are happy to announce that you can now run ECS NVIDIA GPU-accelerated workloads […]

Today, we are happy to announce that Bottlerocket, a Linux-based, open-source, container-optimized operating system, now supports NVIDIA GPUs for accelerated computing workloads. You can now use NVIDIA-based Amazon Elastic Compute Cloud (EC2) instance types with Bottlerocket to accelerate your machine learning (ML), artificial intelligence (AI), and similar workloads that require GPU compute devices. This release […]