Sold by: ParaTools Inc.
Deployed on AWS
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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 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. The HPC stack features numerical libraries (PETSc, SuperLU-dist, Trilinos, WRF), visualization tools (ParaView), performance evaluation tools (HPCToolkit, TAU), and HPC applications (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 (arm64) variant of the unified Heidi image. 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 4 -- a proprietary MVAPICH derivative from our partners at X-Scale Solutions. A VNC-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 4 MPI library tuned for EFA and CUDA. HPC applications include 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, NVIDIA BioNeMo, NVIDIA NeMo™, OpenCV, PyTorch, TensorFlow, and vLLM. The Julia language and the VSCodium IDE are 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
- butterflypack
- cabana
- caliper
- chai
- chapel
- charliecloud
- conduit
- cusz
- darshan-runtime
- darshan-util
- datatransferkit
- dyninst
- e4s-alc
- e4s-cl
- exago
- faodel
- fftx
- flecsi
- flit
- fpm
- gasnet
- ginkgo
- globalarrays
- glvis
- 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
- 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
- paraview
- 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
- stc
- strumpack
- sundials
- superlu
- superlu-dist
- swig
- sz
- sz3
- tasmanian
- tau
- trilinos
- turbine
- umap
- umpire
- upcxx
- 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 VNC remote desktop for interactive computing
Details
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Delivery method
Delivery option
64-bit (Arm) Amazon Machine Image (AMI)
Latest version
Operating system
Ubuntu 24.04
Deployed on AWS
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Pricing
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Try this product free for 31 days according to the free trial terms set by the vendor. Usage-based pricing is in effect for usage beyond the free trial terms. Your free trial gets automatically converted to a paid subscription when the trial ends, but may be canceled any time before that.
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Cost/hour |
|---|---|
c7g.4xlarge Recommended | $0.99 |
c6g.4xlarge | $0.99 |
g5g.16xlarge | $0.99 |
c6gd.8xlarge | $0.99 |
c6gd.large | $0.99 |
t4g.micro | $0.99 |
is4gen.medium | $0.99 |
a1.large | $0.99 |
c6g.xlarge | $0.99 |
m6gd.medium | $0.99 |
Dimensions summary
You pay by the hour based on which ARM64 (Graviton) EC2 instance type you run. Each dimension maps to a specific instance type in a family such as general purpose, compute-optimized, memory-optimized, storage-optimized, or GPU-enabled. Within each family, pricing scales with instance size, from small (medium, large) up to larger multi-xlarge and bare-metal options. Larger sizes carry more CPU, memory, or attached storage and bill at a higher hourly rate. You choose the instance type that fits your HPC or AI/ML workload, and the software runs on top with no upfront commitment.
Top-of-mind questions for buyers
You pay per hour for each running ARM64 (Graviton) instance of the type you select. That hour includes the software stack: over 100 HPC tools, a tuned MPI, and AI/ML Python tools. You pick the instance size that matches your workload's CPU, memory, or storage needs.
Hourly software charges apply only while an instance runs. Stopped or powered-off instances do not accrue software charges. Underlying AWS storage fees for attached volumes may still apply separately. Because there is no upfront commitment, you can start and stop instances as your workload requires.
You choose from general purpose, compute-optimized, memory-optimized, storage-optimized, and GPU-enabled families. Sizes range from small (medium, large) to multi-xlarge and bare-metal. Larger sizes add CPU, memory, or attached storage and bill at higher hourly rates. GPU-enabled types suit AI/ML work; storage-optimized types suit data-heavy jobs.
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Any additional refund enquiries can be sent to support@paratools.com and will be considered individually on a case by case basis.
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Delivery details
64-bit (Arm) 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: 25.11
- Default MPI: MVAPICH-4 Plus
- OS: Ubuntu 24.04
*** 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.
*** SECURITY UPDATE NOTICE *** This maintenance release rebuilds the arm64 v2.0 unified image (Ubuntu 24.04 + E4S 25.11) with the latest Ubuntu 24.04 LTS security updates and removes the GNU inetutils telnet client, the telnet transitional package, and the telnetd server to remediate CVE-2026-32746 (pre-auth unauthenticated telnetd RCE on port 23). Default SSH user remains ubuntu.
IMPORTANT:
- Usable standalone as a development environment or shared-memory system. Multi-node TORQUE-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:
- Security (Important): removed the GNU inetutils telnet client, the telnet transitional package, and the telnetd server to remediate CVE-2026-32746; applied the latest Ubuntu 24.04 LTS security updates
- Hugging Face Transformers updated to 4.57.6
- Julia 1.12.6 added (CUDA + MPI integration)
Platform:
- E4S 25.11 scientific software stack
- Ubuntu 24.04
- MVAPICH-4 Plus -- MPI library tuned for AWS EFA and CUDA (MVAPICH 4.1 core, Hydra 4.3.0 process manager)
- CUDA 12.9, gcc 13.3.0
- Julia 1.12.6 (CUDA + MPI integration)
- ParaView 5.13.3 (visualization)
- TurboVNC 3.2.1 + noVNC 1.4.0 (VNC-based web remote desktop)
AI/ML stack (system Python env, /opt/python/pkgs/python-3.12.12):
- PyTorch 2.10.0 + torchvision
- TensorFlow 2.20.0
- Keras 3.14.0
- JAX 0.10.0
- vLLM 0.19.0
- OpenCV 4.13.0
- Hugging Face Transformers 4.57.6, HF Hub
- Triton 3.6.0, mpi4py 4.1.1
- Gradio, LangChain, OpenAI SDK
- Ollama (local LLM inference)
- JupyterLab + Notebook, Marimo
- NumPy, SciPy, Pandas, Matplotlib, Seaborn, Plotly, GeoPandas
NeMo / BioNeMo stack (segregated venv, activate via . /usr/local/py-env/nemo/bin/activate):
- NVIDIA NeMo Toolkit 2.5.3
- NVIDIA BioNeMo suite (core 2.4.5, fw 2.7.1, ESM-2, Evo2, AMPLIFY, Geneformer, MoCo, scDL)
- PyTorch 2.9.1
- Megatron-Core 0.14 + Megatron-Bridge, Megatron-FSDP, Megatron-Energon
- Flash-Attention 2.7.4
- PyTorch Lightning 2.4.0, Accelerate 1.13.0
- Diffusers 0.37.1, PEFT 0.19.1
Containers + orchestration:
- Docker, Podman, Singularity-CE 4.4.1
IDE:
- VS Codium
Packages installed via Spack:
- adios@1.13.1
- adios2@2.10.2
- adios2@2.11.0
- alquimia@1.1.0
- aml@0.2.1
- amrex@25.10
- arborx@1.5
- arborx@2.0.1
- argobots@1.2
- ascent@0.9.5
- axom@0.10.1
- boost@1.88.0
- butterflypack@3.2.0
- cabana@0.7.0
- caliper@2.12.1
- chai@2025.03.0
- chapel@2.6.0
- charliecloud@0.40
- conduit@0.9.5
- cusz@0.14.0
- darshan-runtime@3.4.7
- darshan-util@3.4.7
- datatransferkit@3.1.1
- dyninst@13.0.0
- e4s-alc@1.0.3
- e4s-cl@1.0.5
- exago@1.6.0
- faodel@1.2108.1
- fftx@1.2.0
- flecsi@2.4.1
- flit@2.1.0
- fpm@0.10.0
- gasnet@2025.8.0
- ginkgo@1.10.0
- globalarrays@5.8.2
- glvis@4.4
- gmp@6.3.0
- gotcha@1.0.8
- gptune@4.0.0
- gromacs@2025.3
- 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@2025.1.0
- hpx@1.11.0
- hypre@2.33.0
- kokkos@4.7.01
- kokkos-kernels@4.7.01
- laghos@3.1
- lammps@20250722
- lbann@0.104
- legion@25.03.0
- libcatalyst@2.0.0
- libceed@0.12.0
- libnrm@0.1.0
- libpressio@0.99.4
- libquo@1.4
- libunwind@1.7.2
- loki@0.1.7
- magma@2.9.0
- metall@0.30
- mfem@4.8.0
- mgard@compat-2023-12-09
- mpark-variant@1.4.0
- mpifileutils@0.12
- nccmp@1.9.1.0
- nco@5.3.4
- nek5000@19.0
- nekbone@17.0
- netcdf-fortran@4.6.2
- netlib-scalapack@2.2.2
- nrm@0.1.0
- omega-h@10.8.6-scorec
- openfoam@2412
- openmpi@5.0.8
- openpmd-api@0.16.1
- papi@7.2.0
- papyrus@1.0.2
- parallel-netcdf@1.14.1
- paraview@5.13.3
- parsec@4.0.2411
- pdt@3.25.2
- petsc@3.24.0
- phist@1.12.1
- plasma@24.8.7
- plumed@2.9.2
- precice@3.3.0
- pruners-ninja@1.0.1
- pumi@2.2.9
- py-cinemasci@1.7.0
- py-h5py@3.14.0
- py-jupyterhub@1.4.1
- py-libensemble@1.5.0
- py-petsc4py@3.24.0
- qthreads@1.18
- quantum-espresso@7.5
- raja@2025.03.0
- rempi@1.1.0
- scr@3.1.0
- slate@2025.05.28
- slepc@3.24.0
- stc@0.9.0
- strumpack@8.0.0
- sundials@7.5.0
- superlu@7.0.0
- superlu-dist@9.1.0
- swig@4.0.2-fortran
- sz@2.1.12.5
- sz3@3.2.0
- tasmanian@8.1
- tau@2.35.1
- trilinos@16.1.0
- turbine@1.3.0
- umap@2.1.1
- umpire@2025.03.0
- upcxx@2023.9.0
- veloc@1.7
- vtk-m@2.3.0
- wannier90@3.1.0
- warpx@25.04
- wps@4.5
- wrf@4.6.1
- 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.
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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, 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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