ecpe4s/e4s-cuda repository overview

E4S, an HPSF project, is an HPC-AI software ecosystem for science. It’s a curated, Spack based collection of scientific libraries and tools that form the foundation of some of the world’s most advanced scientific applications. E4S curates the largest single collection of open-source GPU-enabled libraries and tools for scientific applications, including support for equation-based modeling and simulation, and AI for science. All E4s public-domain software is thoroughly tested for interoperability and portability to multiple computing architectures and will continue to be enhanced and expanded to address architectural changes and emerging new architectures. While E4S supports many products and distributions, users can confidently select any subset of functionality. We build and test the whole so you can select what you need. The key features of E4S 25.06 support a timely expansion of the ecosystem’s AI portfolio and include:

● Support for the NVIDIA Blackwell GPU architecture on x86_64 and aarch64 (Grace-Blackwell) with CUDA v12.9.

● NVIDIA NeMoTM Framework v2.5.0, a comprehensive framework for building, customizing, deploying, and maintaining generative AI models. It includes support for large language models (LLMs), video models, vision language models (VLMs), and speech AI.

● NVIDIA BioNeMo Framework v2.7, an open source, AI platform to accelerate drug discovery and biopharmaceutical research providing a comprehensive suite of frameworks, pretrained models, generative AI tools, and microservices for computational biology and chemistry. support for modeling DNA, RNA, and proteins and offers optimized AI models and curated training recipes for biopharma supporting the entire drug discovery process.

● Vllm v0.11.0, an inference engine for efficiently serving LLMs at scale and supporting GPUs.

● Hugging Face Hub and CLI tools, a leading open-source platform for AI/ML often described as the “GitHub of ML”. These tools provide access to a model hub with over a million pre-trained models for text classification, language generation, translation, summarization, and image generation. It features a Transformers Python library simplifying the use of deep learning models for NLP tasks.

● E4S also includes Google ADK, TensorFlow, PyTorch, JAX, Scikit-Learn, Pandas, Lbann, OpenCV, and Torchbraid optimized for GPUs.

Other new features of the E4S release include support for PyTorch and Vllm for Intel GPUs, Intel 25.2 compilers, ROCm 6.4.3 integration for AMD GPUs; the high-order API library, libCEED; and Julia with support for AMD and NVIDIA GPUs with MPI. Chapel has been upgraded with support for NVIDIA and AMD GPUs. Other applications of note in E4S 25.11 include CP2K, DealII, FFTX, GROMACS, LAMMPS, Nek5000, Nekbone, NWChem, OpenFOAM, WarpX, WRF, Quantum Espresso, and Xyce, with support for GPUs where available.

VSCodium provides the integrated development environment, Jupyter and Marimo notebooks provide a web-based Python notebook interface.

3D graphics tools include ParaView, VisIt, and TAU. E4S tools updated in release 25.11 E4S tools updated in release 25.11 include e4s-chain-spack.sh to chain two Spack instances to allow users to install new packages while leveraging pre-installed E4S packages and dependencies, e4s-alc to customize containers from base container images, and e4s-cl to support binary distribution of MPI applications by substituting the MPI library embedded in the containerized application with the system/vendor MPI for near native performance.

E4S 25.11 has separate CPU (x86_64, aarch64, ppc64le) and GPU containers for NVIDIA GPUs optimizing the size of the containers for each GPU architecture. It supports Rocky Linux 9.6 and Ubuntu 24.04 LTS with Python 3.12.11.

Rounding out the expanded capabilities of E4S 25.11, E4S is the availability of ParaTools Pro for E4S(TM) [https://paratoolspro.com⁠] on commercial cloud platforms and their marketplaces on Azure, AWS, Google Cloud, IBM Cloud, and Oracle Cloud Infrastructure with support for NVIDIA GPUs.