EUGENE, OR., November 17, 2025— The E4S Project, today announced the immediate availability of E4S Release 25.11. E4S, an HPSF project, is the open-source, community-driven HPC-AI Software Ecosystem for Science. This curated, Spack based collection of scientific libraries and tools forms the foundation of some of the world’s most advanced scientific applications. E4S 25.11 container images […]
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E4S Release 25.11 Offers Container Images, NVIDIA Blackwell Support and 125+ HPC and AI Packages
November 17, 2025 by
NVIDIA: CUDA Available from Additional 3rd-Party Platforms
September 12, 2025 by
NVIDIA announced the CUDA software stack is being deployed across various operating systems and package managers. The company said it is working with its ecosystem of distribution platforms ….
E4S Release 25.06 for AI and HPC Available from High Performance Software Foundation
June 6, 2025 by
EUGENE, OR., June 6, 2025— The E4S Project announced the availability of Release 25.06 that includes new features, including an expanded AI portfolio and support for the NVIDIA Blackwell GPU architecture with CUDA 12.8. E4S, a High Performance Software Foundation project, is an HPC-AI software ecosystem for science. It’s a curated, Spack-based collection of scientific […]
New Update of the Extreme Scale Scientific Software Stack (E4S)
November 18, 2024 by
November 17, 2024, ATLANTA: The PESO Project, a community-driven effort to promote the development and use of scientific software as an ecosystem, and the Extreme Scale Scientific Software (E4S) development and support team, today announced the release of E4S 24.11. Following is a partial list of highlights in this release: E4S includes 132+ HPC-AI packages […]
DOE: E4S for Extreme-Scale Science Now Supports Nvidia Grace and Grace Hopper GPUs
February 27, 2024 by
E4S, the open source Extreme-Scale Scientific Software Stack for HPC-AI scientific applications, now incorporates AI/ML libraries and expands GPU support to include the Nvidia Grace and Grace Hopper architectures. E4S is a community effort to provide open-source….
Emerging Tools and Frameworks in AI: A Comparative Analysis
November 24, 2023 by
In this contributed article, graphic designer and content writer, Erika Ballo delves into some emerging tools and frameworks in AI, comparing their strengths, usability, and ideal use cases.
The Impact of Python: How It Could Rule the AI World?
March 13, 2020 by
In this contributed article, writer, AI researcher, and business strategist Michael Lyman discusses the growth of use of the Python language and how it is playing a significant role in the rise of AI and deep learning. Python’s power and ease of use has catapulted it to become one of the core languages to provide machine learning solutions.
Develop Multiplatform Computer Vision Solutions with Intel® Distribution of OpenVINO™ Toolkit
August 26, 2019 by
Realize your computer vision deployment needs on Intel® platforms—from smart cameras and video surveillance to robotics, transportation, and much more. The Intel® Distribution of OpenVINO™ Toolkit (includes the Intel® Deep Learning Deployment Toolkit) allows for the development of deep learning inference solutions for multiple platforms.
Using Inference Engines to Power AI Apps Audio, Video and more
June 20, 2019 by
With the demand for intelligent solutions like autonomous driving, digital assistants, recommender systems, enterprises of every type are demanding AI powered – applications for surveillance, retail, manufacturing, smart cities and homes, office automation, autonomous driving, and more coming every day. Increasingly, AI applications are powered by smart inference-based inputs. This sponsored post from Intel explores how inference engines can be used to power AI apps, audio, video and highlights the capabilities of Intel’s Distribution of OpenVINO (Open Visual Inference and Neural Network Optimization) toolkit.
Quadric.io to Build “Supercomputer for Edge Devices”
May 14, 2019 by
Today chip startup Quadric.io announced plans to build the world’s first “supercomputer” specifically designed for the real-time needs of autonomous systems. “Instead of building a heterogeneous system with CPUs/GPUs/FPGAs & AI chips and dealing with that complexity of software and hardware integration, Quadric has the technology to handle most of the application in a single unified hardware architecture and software model.”
