Sold by: ParaTools Inc.
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This product has charges associated with it for optional seller support and pre-configured stack (ParaTools Pro for E4S™). ParaTools Pro for E4S™ is the hardened Extreme-scale Scientific Software Stack on Ubuntu, for use with Adaptive Computing's Heidi AI Cloud Supercomputer. It includes over 100 HPC and AI/ML tools, a web-based remote desktop environment, and cluster configuration built using the Spack package manager and a proprietary MVAPICH-Plus 4 MPI tuned for AWS Elastic Fabric Adapter (EFA). Develop AI/ML applications using tools such as JAX, Keras, NIXL, NVIDIA BioNeMo, NVIDIA NeMo™, PyTorch, SGLang, TensorFlow, and vLLM tuned for AWS and Heidi. The HPC stack features numerical libraries (PETSc, SuperLU-dist, Trilinos, WRF), visualization tools (ParaView, VisIt), performance evaluation tools (HPCToolkit, TAU), GPU communication libraries (NCCL, NVSHMEM), and HPC applications (CP2K, GROMACS, LAMMPS, OpenFOAM, Quantum Espresso, WarpX, Xyce).
Overview
ParaTools Pro for E4S™ - the Extreme-scale Scientific Software Stack, E4S™ hardened for commercial clouds and supported by ParaTools, Inc., provides a platform for developing and deploying HPC and AI/ML applications. This product is the Ubuntu variant of the unified Heidi image; a Rocky Linux variant is available as a separate marketplace listing. It is designed for use with Adaptive Computing's Heidi AI Cloud Supercomputer , which provides multi-cloud HPC orchestration with automated infrastructure deployment, scaling, and cluster monitoring. A single unified image auto-detects its cluster role (head node / compute node) at boot time; the image is also usable standalone as a development environment. When run on EFA-capable instance families, cluster nodes are interconnected by a low-latency, high-bandwidth fabric based on AWS Elastic Fabric Adapter (EFA), fully leveraged by MVAPICH-Plus -- a proprietary MVAPICH derivative from our partners at X-Scale Solutions. NVIDIA NCCL and NVSHMEM accelerate multi-GPU communication, and the NVIDIA Inference Xfer Library (NIXL) provides high-throughput data movement for distributed AI inference. A web-based remote desktop is available for interactive GUI work. ParaTools Pro for E4S™ features a suite of over 100 HPC tools built using the Spack package manager and the MVAPICH-Plus MPI library tuned for EFA and CUDA. HPC applications include CP2K, GROMACS, LAMMPS, OpenFOAM, Quantum Espresso, WarpX, Weather Research and Forecasting Model-WRF, and Xyce; the AI/ML Python stack includes Hugging Face Transformers, JAX, JupyterLab, Keras, matplotlib, NIXL, NVIDIA BioNeMo, NVIDIA NeMo™, OpenCV, PyTorch, SGLang, TensorFlow, and vLLM, unified into a single Python environment. The VSCodium IDE is also pre-installed. New packages can be easily added using Spack and pip and are accessible across cluster nodes. It may be used for developing the next generation of generative AI applications using a suite of Python tools and interfaces.
E4S™ has built a unified computing environment for deployment of open-source projects. E4S™ was originally developed to provide a common software environment for the exascale leadership computing systems currently being deployed at DOE National Laboratories across the U.S. Support for ParaTools Pro for E4S™ is available through ParaTools, Inc. This product has additional charges associated with it for optional product support and updates.
This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research (ASCR), under SBIR Award Number DE-SC0022502 ("E4S: Extreme-Scale Scientific Software Stack for Commercial Clouds").
Note: This product contains repackaged and tuned open source software (e.g., E4S™, Spack, and AI/ML tools like NVIDIA NeMo™, BioNeMo, TensorFlow, JAX, vLLM, etc.) which is configured and linked against an MVAPICH MPI implementation specifically developed and tuned for EFA.
The full list of E4S applications installed via Spack is as follows:
- adios
- adios2
- alquimia
- aml
- amrex
- arborx
- argobots
- ascent
- axom
- boost
- bricks
- butterflypack
- cabana
- caliper
- chai
- charliecloud
- conduit
- cp2k
- cusz
- darshan-runtime
- darshan-util
- datatransferkit
- dyninst
- e4s-alc
- e4s-cl
- exaworks
- faodel
- flit
- flux-core
- fpm
- gasnet
- ginkgo
- globalarrays
- gmp
- gotcha
- gptune
- gromacs
- h5bench
- hdf5
- hdf5-vol-async
- hdf5-vol-cache
- hdf5-vol-log
- heffte
- hpctoolkit
- hpx
- hypre
- kokkos
- kokkos-kernels
- laghos
- lammps
- lbann
- legion
- libcatalyst
- libceed
- libnrm
- libpressio
- libquo
- libunwind
- loki
- magma
- mercury
- metall
- mfem
- mgard
- mpark-variant
- mpifileutils
- nccmp
- nco
- nek5000
- nekbone
- netcdf-fortran
- netlib-scalapack
- nrm
- omega-h
- openfoam
- openmpi
- openpmd-api
- papi
- papyrus
- parallel-netcdf
- parsec
- pdt
- petsc
- phist
- plasma
- plumed
- precice
- pruners-ninja
- pumi
- py-cinemasci
- py-h5py
- py-jupyterhub
- py-libensemble
- py-petsc4py
- qthreads
- quantum-espresso
- raja
- rempi
- scr
- slate
- slepc
- strumpack
- sundials
- superlu
- superlu-dist
- swig
- sz
- sz3
- tasmanian
- tau
- trilinos
- turbine
- umap
- umpire
- upcxx
- variorum
- veloc
- vtk-m
- wannier90
- warpx
- wps
- wrf
- xyce
- zfp
Highlights
- ParaTools Pro for E4S™ and Machine Learning stacks, including NVIDIA NeMo™, built and optimized for AWS EFA and Heidi
- A proprietary MVAPICH-Plus 4 MPI implementation that offers lower latency and higher throughput than default OpenMPI implementations for pre-installed applications and user-installed applications
- Over 100 HPC and AI applications managed via the Spack package manager, with a web-based remote desktop for interactive computing
Details
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Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
Ubuntu 26.04
Deployed on AWS
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Dimension | Cost/hour |
|---|---|
c5n.9xlarge Recommended | $0.99 |
t2.micro | $0.99 |
t3.micro | $0.99 |
i3en.metal | $0.99 |
m5n.12xlarge | $0.99 |
m7i.large | $0.99 |
m2.2xlarge | $0.99 |
r6i.xlarge | $0.99 |
m6idn.16xlarge | $0.99 |
i3.16xlarge | $0.99 |
Dimensions summary
You pay by the hour based on the EC2 instance type you run. Each dimension maps to one x86_64 instance type, so your cost scales with the size and family of hardware you choose. Smaller general-purpose instances bill at a lower hourly rate, while memory-optimized, compute-optimized, storage, and GPU or accelerator instances cost more per hour. You only pay for hours the software runs. There are no tiers or upfront commitments. Choose the instance that fits your HPC or AI/ML workload, and billing follows your actual usage.
Top-of-mind questions for buyers
Each hourly unit is one running x86_64 EC2 instance with the software image installed. That image includes over 100 HPC tools, ready-to-use HPC applications, and Python-based AI/ML tools. You pay per hour for each active instance, so running more instances multiplies your hourly charge.
Software charges apply only while an instance runs. Stopped or powered-off instances do not accrue software fees. Underlying AWS storage or other resource charges may still apply while an instance is stopped, but the hourly software meter tracks running time only.
You pay the hourly rate tied to each instance type you run. A head node manages the fleet and can use a smaller general-purpose type. Compute nodes often use larger or accelerator types billed at higher rates. Your total is the sum of each running instance's hourly charge.
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Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
- Adaptive Heidi release: v2.0
- E4S release: 26.06
- Default MPI: MVAPICH-4 Plus
- OS: Ubuntu 26.04
*** UNIFIED IMAGE NOTICE *** Single unified image serves both Heidi Server (head node) and Heidi Node (compute node) roles. Image auto-detects role at boot when deployed with Adaptive Computing's Heidi AI Cloud Supercomputer. Also usable standalone as a development environment.
*** OS VARIANT NOTICE *** Ubuntu 26.04 x86_64 variant. For the Rocky Linux 9 x86_64 variant, see: https://aws.amazon.com/marketplace/pp/prodview-k3nscpq6ipu6c
*** UNIFIED PYTHON NOTICE *** The AI/ML Python stack is a single unified environment (/opt/python/pkgs/python-3.12.13). NeMo, BioNeMo, PyTorch, TensorFlow, JAX, vLLM, and SGLang all share one interpreter; the previously separate NeMo virtual environment has been removed.
IMPORTANT:
- Usable standalone as a development environment or shared-memory system. Multi-node SLURM-scheduled jobs and cluster orchestration activate when deployed with Adaptive Computing's Heidi AI Cloud Supercomputer.
- MVAPICH-4 Plus provides optimized multi-node support without strictly requiring EFA-enabled instances; EFA is still recommended for best performance.
Updates in this version: Platform:
- Maintenance and security rebuild of the E4S 26.06 scientific software stack (refreshed package versions; Python 3.12.12 -> 3.12.13)
- NVSHMEM 3.7.0 and NIXL 1.3.1 (NVIDIA Inference Xfer Library) added for accelerated multi-GPU data movement and distributed inference
- MVAPICH-4 Plus -- MPI library tuned for AWS EFA and CUDA (MVAPICH 4.1 core, ch4:ofi device over libfabric/EFA, CUDA-enabled)
- SLURM 23.11.4 workload manager + MUNGE authentication (replaces the TORQUE resource manager used in prior Heidi releases)
- CUDA 12.9.1 system toolkit, cuDNN 9.8.0, NCCL 2.30.7, NVSHMEM 3.7.0, gcc 13.4.0
- Julia 1.12.6
- ParaView 6.1.0, VisIt 3.5.0 (visualization)
- Web-based remote desktop (replaces TurboVNC/noVNC from prior releases)
AI/ML stack (unified Python env, /opt/python/pkgs/python-3.12.13):
- PyTorch 2.11.0 (cu130 wheels) + torchvision 0.26.0 + torchaudio 2.11.0
- TensorFlow 2.21.0
- Keras 3.14.1
- JAX 0.10.1
- vLLM 0.21.0
- SGLang 0.5.12
- NIXL 1.3.1 (NVIDIA Inference Xfer Library)
- OpenCV 4.13.0
- Hugging Face Transformers 5.6.0, HF Hub 1.16.1, Tokenizers 0.22.2
- NVIDIA NeMo (nemo-run 0.9.0rc0, NeMo-Export-Deploy 0.5.0rc0, nemo-evaluator 0.2.6) + Megatron-Core 0.17.0, Megatron-Bridge, Megatron-Energon 6.0.1
- NVIDIA BioNeMo (core 2.4.5 + MoCo, noodles, scDL, size-aware-batching)
- Flash-Attention 2.7.4, Transformer Engine 2.12.0, Mamba-SSM 2.3.1
- Accelerate 1.13.0, PEFT 0.13.2, PyTorch Lightning 2.6.4
- Ray 2.55.1, Gradio 6.14.0, Streamlit 1.57.0, LangChain 1.3.1, OpenAI SDK 2.46.0, Agent Development Kit (ADK) 2.1.0, Weights & Biases 0.27.0
- mpi4py 4.1.2, CuPy 14.1.1, XGBoost 3.3.0, RDKit 2026.3.4
- JupyterLab 4.5.7 + Notebook 7.5.6, Marimo 0.19.2
- NumPy 2.3.5, SciPy 1.17.1, Pandas 2.3.3, Scikit-Learn 1.8.0
- Matplotlib 3.10.9, Seaborn 0.13.2, Plotly 6.7.0, GeoPandas 1.1.3
AI agent tooling:
- Ollama 0.32.1 (local LLM inference)
- AI vendor coding-agent CLIs, OpenClaw, NVIDIA NemoClaw v0.0.68, launch_nemo
Containers + orchestration:
- Docker 29.6.2, Podman 5.7.0, Singularity-CE 4.5.0
- NVIDIA Container Toolkit 1.19.1, Podman-HPC
- k3s v1.36.2 + kubectl
IDE:
- VS Codium 1.121.03429
The full list of E4S applications installed via Spack is as follows:
-- linux-ubuntu26.04-x86_64_v3 / gcc@13.4.0 ----------------
- adios@1.13.1
- adios2@2.12.1
- alquimia@1.1.0
- aml@0.2.1
- amrex@26.06
- arborx@2.1
- argobots@1.2
- ascent@0.9.5
- axom@0.14.0
- boost@1.90.0
- bricks@2023.08.25
- butterflypack@3.2.0
- cabana@0.7.0
- caliper@2.14.0
- chai@2025.12.0
- charliecloud@0.44
- conduit@0.9.7
- cp2k@2026.1
- cusz@0.14.0
- darshan-runtime@3.5.0
- darshan-util@3.5.0
- datatransferkit@3.1.1
- dyninst@13.0.1
- e4s-alc@1.0.3
- e4s-cl@1.0.9
- exaworks@0.1.0
- faodel@1.2108.1
- flit@2.1.0
- flux-core@0.81.0
- fpm@0.13.0
- gasnet@2025.8.0
- ginkgo@1.11.0
- globalarrays@5.8.2
- gmp@6.3.0
- gotcha@1.0.8
- gptune@5.0.0
- gromacs@2026.1
- h5bench@1.4
- hdf5@1.14.6
- hdf5-vol-async@1.7
- hdf5-vol-cache@v1.1
- hdf5-vol-log@1.4.0
- heffte@2.4.1
- hpctoolkit@2026.0.1
- hpx@1.11.0
- hypre@3.1.0
- kokkos@5.1.1
- kokkos-kernels@5.1.1
- laghos@3.1
- lammps@20250722.3
- lbann@0.104
- legion@26.03.0
- libcatalyst@2.1.0
- libceed@0.12.0
- libnrm@0.1.0
- libpressio@0.99.4
- libquo@1.4
- libunwind@1.8.3
- loki@0.1.7
- magma@2.10.0
- mercury@2.4.1
- metall@0.30
- mfem@4.9.0
- mgard@1.6.0
- mpark-variant@1.4.0
- mpifileutils@0.12
- nccmp@1.11.0.0
- nco@5.3.9
- nek5000@19.0
- nekbone@17.0
- netcdf-fortran@4.6.2
- netlib-scalapack@2.2.3
- nrm@0.1.0
- omega-h@11.0.0-scorec
- openfoam@2512
- openmpi@5.0.10
- openpmd-api@0.17.0
- papi@7.2.0
- papyrus@1.0.2
- parallel-netcdf@1.14.1
- parsec@4.0.2411
- pdt@3.25.2
- petsc@3.25.2
- phist@1.12.1
- plasma@24.8.7
- plumed@2.10.0
- precice@3.4.0
- pruners-ninja@1.0.2
- pumi@2.2.9
- py-cinemasci@1.7.9
- py-h5py@3.16.0
- py-jupyterhub@1.4.1
- py-libensemble@1.5.0
- py-petsc4py@3.25.2
- qthreads@1.18
- quantum-espresso@7.5
- raja@2025.12.2
- rempi@1.1.0
- scr@3.1.0
- slate@2025.05.28
- slepc@3.25.1
- strumpack@8.0.0
- sundials@7.7.0
- superlu@7.0.1
- superlu-dist@9.2.1
- swig@4.0.2-fortran
- sz@2.1.12.5
- sz3@3.2.0
- tasmanian@8.1
- tau@2.35.2
- trilinos@14.4.0
- trilinos@17.1.1
- turbine@1.3.0
- umap@2.1.1
- umpire@2025.12.0
- upcxx@2025.10.0
- variorum@0.8.0
- veloc@1.7
- vtk-m@2.3.0
- wannier90@3.1.0
- warpx@26.05
- wps@4.5
- wrf@4.7.1
- xyce@7.10.0
- zfp@1.0.1
Additional details
Usage instructions
The 1-Click Security Group opens port 22 only so that you can access your instance via SSH using login 'ubuntu', you may change this later.
For software development and basic usage:
- Launch the ParaTools Pro for E4S (TM) AMI via 1-Click
- On the 'EC2 Launch an Instance' page pick the key pair you will use to login
- On the 'EC2 Launch an Instance' page optionally edit the network settings by pressing the edit button. Adjust the firewall rules if needed to ensure ssh access and enable Auto-assign public IP if you plan to access the instance remotely from a non-AWS IP address.
- Click 'Launch Instance'
- Find your running instance in the EC2 Instances section of the EC2 dashboard, and connect to the instance via SSH using the key pair you previously selected by picking the instance and pressing the connect button.
For more advanced usage, including launching a ParaTools Pro for E4S (TM) cluster with the Heidi AI Cloud Supercomputer, and submitting multi-node jobs please see:
Support
Vendor support
For general support questions, please email support@paratools.com
Paid support contracts, custom AMIs, and computing environments are available. Please see https://paratoolspro.com/ for additional details.
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
Similar products
This product has charges associated with it for optional seller support and pre-configured stack (ParaTools Pro for E4S™). ParaTools Pro for E4S™ is the hardened Extreme-scale Scientific Software Stack on Rocky Linux, for use with Adaptive Computing's Heidi AI Cloud Supercomputer. It includes over 100 HPC and AI/ML tools, a VNC-based remote desktop environment, and cluster configuration built using the Spack package manager and a proprietary MVAPICH-Plus 4 MPI tuned for AWS Elastic Fabric Adapter (EFA). Develop AI/ML applications using tools such as JAX, Keras, NVIDIA BioNeMo, NVIDIA NeMo™, PyTorch, TensorFlow, and vLLM tuned for AWS and Heidi, along with Julia. The HPC stack features numerical libraries (PETSc, SuperLU-dist, Trilinos, WRF), visualization tools (ParaView, VisIt), performance evaluation tools (HPCToolkit, TAU), and HPC applications (CP2K, deal.II, GROMACS, LAMMPS, OpenFOAM, Quantum Espresso, WarpX, Xyce). Default SSH user on this image is `rocky`.
This product has charges associated with it for optional seller support and pre-configured stack (ParaTools Pro for E4S™). ParaTools Pro for E4S™ is the hardened Extreme-scale Scientific Software Stack on Ubuntu and Rocky Linux, using AWS ParallelCluster, with over 100 HPC and AI/ML tools, an optional Amazon DCV remote desktop on the cluster head node, and cluster configuration built using the Spack package manager and a proprietary MVAPICH-Plus 4 MPI tuned for AWS Elastic Fabric Adapter (EFA). Develop AI/ML applications using tools such as JAX, Keras, NVIDIA BioNeMo, NVIDIA NeMo™, PyTorch, SGLang, TensorFlow, and vLLM tuned for AWS ParallelCluster, with a complete HPC software stack including numerical libraries (PETSc, SuperLU-dist, Trilinos, WRF), visualization tools (ParaView, VisIt), performance evaluation tools (HPCToolkit, TAU), HPC applications (CP2K, GROMACS, LAMMPS, OpenFOAM, Quantum Espresso, WarpX, Xyce).
This product has charges associated with it for optional seller support and pre-configured stack (ParaTools Pro for E4S™). ParaTools Pro for E4S™ is the hardened Extreme-scale Scientific Software Stack on Ubuntu, using AWS Parallel Computing Service (AWS PCS), with over 100 HPC and AI/ML tools, a remote desktop environment (Amazon DCV), and cluster configuration built using the Spack package manager and a proprietary MVAPICH-Plus 4 MPI tuned for AWS Elastic Fabric Adapter (EFA). Develop AI/ML applications using tools such as JAX, Keras, NVIDIA BioNeMo, NVIDIA NeMo™, PyTorch, TensorFlow, and vLLM tuned for AWS Parallel Computing Service, with a complete HPC software stack including numerical libraries (PETSc, SuperLU-dist, Trilinos, WRF), performance evaluation tools (HPCToolkit, TAU), HPC applications (GROMACS, LAMMPS, OpenFOAM, Quantum Espresso, WarpX, Xyce).
This product has charges associated with it for optional seller support and pre-configured stack (ParaTools Pro for E4S™). ParaTools Pro for E4S™ is the hardened Extreme-scale Scientific Software Stack on Ubuntu, using AWS ParallelCluster, with over 100 HPC and AI/ML tools, an optional Amazon DCV remote desktop on the cluster head node, and cluster configuration built using the Spack package manager and a proprietary MVAPICH-Plus 4 MPI tuned for AWS Elastic Fabric Adapter (EFA). Develop AI/ML applications using tools such as JAX, Keras, NVIDIA BioNeMo, NVIDIA NeMo™, PyTorch, TensorFlow, and vLLM tuned for AWS ParallelCluster, with a complete HPC software stack including numerical libraries (PETSc, SuperLU-dist, Trilinos, WRF), visualization tools (Ascent, VTK-m), performance evaluation tools (HPCToolkit, TAU), HPC applications (GROMACS, LAMMPS, OpenFOAM, Quantum Espresso, WarpX, Xyce).
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