Alternatives to Eata HPC
Compare Eata HPC alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Eata HPC in 2026. Compare features, ratings, user reviews, pricing, and more from Eata HPC competitors and alternatives in order to make an informed decision for your business.
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1
UberCloud
Simr (formerly UberCloud)
Simr (formerly UberCloud) is a cutting-edge platform for Simulation Operations Automation (SimOps). It streamlines and automates complex simulation workflows, enhancing productivity and collaboration. Leveraging cloud-based infrastructure, Simr offers scalable, cost-effective solutions for industries like automotive, aerospace, and electronics. Trusted by leading global companies, Simr empowers engineers to innovate efficiently and effectively. Simr supports a variety of CFD, FEA and other CAE software including Ansys, COMSOL, Abaqus, CST, STAR-CCM+, MATLAB, Lumerical and more. Simr automates every major cloud including Microsoft Azure, Amazon AWS, and Google GCP. -
2
Kombyne
Kombyne
Kombyne™ is an innovative new SaaS high-performance computing (HPC) workflow tool, initially developed for customers in the defense, automotive, and aerospace industries and academic research. It allows users to subscribe to a range of workflow solutions for HPC CFD jobs, from on-the-fly extract generation and rendering to simulation steering. Interactive monitoring and control are also available, all with minimal simulation disruption and no reliance on VTK. The need for large files is eliminated via extract workflows and real-time visualization. An in-transit workflow uses a separate process that quickly receives data from the solver code and performs visualization and analysis without interfering with the running solver. This process, called an endpoint, can directly output extracts, cutting planes or point samples for data science and can render images as well. The Endpoint can also act as a bridge to popular visualization codes. -
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AWS Parallel Computing Service (AWS PCS) is a managed service that simplifies running and scaling high-performance computing workloads and building scientific and engineering models on AWS using Slurm. It enables the creation of complete, elastic environments that integrate computing, storage, networking, and visualization tools, allowing users to focus on research and innovation without the burden of infrastructure management. AWS PCS offers managed updates and built-in observability features, enhancing cluster operations and maintenance. Users can build and deploy scalable, reliable, and secure HPC clusters through the AWS Management Console, AWS Command Line Interface (AWS CLI), or AWS SDK. The service supports various use cases, including tightly coupled workloads like computer-aided engineering, high-throughput computing such as genomics analysis, accelerated computing with GPUs, and custom silicon like AWS Trainium and AWS Inferentia.Starting Price: $0.5977 per hour
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4
Gemini for Science
Google
Gemini for Science powers scientific discovery with AI tools and resources built to support scientific endeavors. It brings together experimental tools on Google Labs and science workflows in Google Antigravity to accelerate research, sharpen reasoning, and help researchers explore the future of AI-powered scientific discovery. Literature Insights synthesizes scholarly literature to identify new research opportunities, create grounded research artifacts, and extract paper data into queryable tables mapped directly to source evidence. Hypothesis Generation uses a multi-agent system that simulates the scientific method to identify knowledge gaps, generate potential research directions, and propose testable research plans for breakthrough discoveries. Computational Discovery helps researchers discover models and algorithms by using an agentic research engine that generates and scores code variations based on user-defined optimization metrics. -
5
NVIDIA NGC
NVIDIA
NVIDIA GPU Cloud (NGC) is a GPU-accelerated cloud platform optimized for deep learning and scientific computing. NGC manages a catalog of fully integrated and optimized deep learning framework containers that take full advantage of NVIDIA GPUs in both single GPU and multi-GPU configurations. NVIDIA train, adapt, and optimize (TAO) is an AI-model-adaptation platform that simplifies and accelerates the creation of enterprise AI applications and services. By fine-tuning pre-trained models with custom data through a UI-based, guided workflow, enterprises can produce highly accurate models in hours rather than months, eliminating the need for large training runs and deep AI expertise. Looking to get started with containers and models on NGC? This is the place to start. Private Registries from NGC allow you to secure, manage, and deploy your own assets to accelerate your journey to AI. -
6
Ansys HPC
Ansys
With the Ansys HPC software suite, you can use today’s multicore computers to perform more simulations in less time. These simulations can be bigger, more complex and more accurate than ever using high-performance computing (HPC). The various Ansys HPC licensing options let you scale to whatever computational level of simulation you require, from single-user or small user group options for entry-level parallel processing up to virtually unlimited parallel capacity. For large user groups, Ansys facilitates highly scalable, multiple parallel processing simulations for the most challenging projects when needed. Apart from parallel computing, Ansys also offers solutions for parametric computing, which enables you to more fully explore the design parameters (size, weight, shape, materials, mechanical properties, etc.) of your product early in the development process. -
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PowerFLOW
Dassault Systèmes
By leveraging our unique, inherently transient Lattice Boltzmann-based physics PowerFLOW CFD solution performs simulations that accurately predict real world conditions. Using the PowerFLOW suite, engineers evaluate product performance early in the design process prior to any prototype being built — when the impact of change is most significant for design and budgets. PowerFLOW imports fully complex model geometry and accurately and efficiently performs aerodynamic, aeroacoustic and thermal management simulations. Automated domain discretization and turbulence modeling with wall treatment eliminates the need for manual volume meshing and boundary layer meshing. Confidently run PowerFLOW simulations using large number of compute cores on common High Performance Computing (HPC) platforms. -
8
AM PravaH
Paanduv Applications
AM PravaH® is a graphical user interface (GUI)-based high-performance simulation software, specifically designed for additive manufacturing. It is developed by Paanduv R&D and is a combination of parallelized computational modeling with state-of-the-art numerical methods provided by international research leaders and in-house. -
9
Samadii Multiphysics
Metariver Technology Co.,Ltd
Metariver Technology Co., Ltd. is developing innovative and creative computer-aided engineering (CAE) analysis S/W based on the latest HPC technology and S/W technology including CUDA technology. We will change the paradigm of CAE technology by applying particle-based CAE technology and high-speed computation technology using GPUs to CAE analysis software. Here is an introduction to our products. 1. Samadii-DEM (the discrete element method): works with the discrete element method and solid particles. 2. Samadii-SCIV (Statistical Contact In Vacuum): working with high vacuum system gas-flow simulation. Using Monte Carlo simulation. 3. Samadii-EM (Electromagnetics): For full-field interpretation 4. Samadii-Plasma: Plasma simulation for Analysis of ion and electron behavior in an electromagnetic field. 5. Vampire (Virtual Additive Manufacturing System): Specializes in transient heat transfer analysis. additive manufacturing and 3D printing simulation software -
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Amazon EC2 P4 Instances
Amazon
Amazon EC2 P4d instances deliver high performance for machine learning training and high-performance computing applications in the cloud. Powered by NVIDIA A100 Tensor Core GPUs, they offer industry-leading throughput and low-latency networking, supporting 400 Gbps instance networking. P4d instances provide up to 60% lower cost to train ML models, with an average of 2.5x better performance for deep learning models compared to previous-generation P3 and P3dn instances. Deployed in hyperscale clusters called Amazon EC2 UltraClusters, P4d instances combine high-performance computing, networking, and storage, enabling users to scale from a few to thousands of NVIDIA A100 GPUs based on project needs. Researchers, data scientists, and developers can utilize P4d instances to train ML models for use cases such as natural language processing, object detection and classification, and recommendation engines, as well as to run HPC applications like pharmaceutical discovery and more.Starting Price: $11.57 per hour -
11
Microsoft Discovery
Microsoft
Microsoft Discovery is a new agentic platform designed to revolutionize research and development (R&D) by empowering scientists and engineers with AI-driven collaboration and high-performance computing (HPC). Built on Azure, this platform enables researchers to work alongside specialized AI agents that help accelerate the discovery process through advanced knowledge reasoning, hypothesis formulation, and experimental simulations. The platform's graph-based knowledge engine facilitates complex, contextual reasoning over vast amounts of scientific data, promoting transparency and accountability while speeding up the discovery cycle. By automating and enhancing research tasks, Microsoft Discovery offers an extensible, enterprise-ready solution that integrates seamlessly with existing tools and datasets. -
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Claude Science
Anthropic
Claude Science is an AI-powered scientific research application that helps researchers perform data analysis, literature review, computational workflows, and manuscript preparation within a single environment. Built on Claude models, the application integrates scientific databases, research tools, electronic lab notebooks, HPC systems, and domain-specific software to support end-to-end research workflows. It manages computational environments across local machines, Linux systems, and high-performance computing clusters while maintaining reproducible records of every analysis. Researchers can generate publication-quality figures, perform complex analyses, and trace every result back to the underlying code, environment, and conversation. Claude Science also supports specialized fields including genomics, proteomics, single-cell biology, structural biology, and cheminformatics through preconfigured scientific capabilities. -
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Google Cloud GPUs
Google
Speed up compute jobs like machine learning and HPC. A wide selection of GPUs to match a range of performance and price points. Flexible pricing and machine customizations to optimize your workload. High-performance GPUs on Google Cloud for machine learning, scientific computing, and 3D visualization. NVIDIA K80, P100, P4, T4, V100, and A100 GPUs provide a range of compute options to cover your workload for each cost and performance need. Optimally balance the processor, memory, high-performance disk, and up to 8 GPUs per instance for your individual workload. All with the per-second billing, so you only pay only for what you need while you are using it. Run GPU workloads on Google Cloud Platform where you have access to industry-leading storage, networking, and data analytics technologies. Compute Engine provides GPUs that you can add to your virtual machine instances. Learn what you can do with GPUs and what types of GPU hardware are available.Starting Price: $0.160 per GPU -
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VSim
Tech-X
VSim is the Multiphysics Simulation Software used by design engineers and research scientists who require precise solutions for challenging problems. VSim’s unique combination of Finite-Difference Time-Domain (FDTD), Particle-in-Cell (PIC), and Charged Fluid (Finite Volume) methods deliver accurate results for a variety of situations, including plasma modeling. As a parallel software application, VSim can efficiently handle problems at scale, and simulations run quickly using algorithms designed for high-performance computing systems. Trusted by researchers in 30 countries, and used by engineers in industries from aerospace to semiconductor manufacturing, With documented accuracy, VSim provides results that users can trust. Created by a team of computational scientists, Tech-X’s code has been cited thousands of times in the scientific literature, and VSim can be found at many of the world’s top research institutions. -
15
AWS HPC
Amazon
AWS High Performance Computing (HPC) services empower users to execute large-scale simulations and deep learning workloads in the cloud, providing virtually unlimited compute capacity, high-performance file systems, and high-throughput networking. This suite of services accelerates innovation by offering a broad range of cloud-based tools, including machine learning and analytics, enabling rapid design and testing of new products. Operational efficiency is maximized through on-demand access to compute resources, allowing users to focus on complex problem-solving without the constraints of traditional infrastructure. AWS HPC solutions include Elastic Fabric Adapter (EFA) for low-latency, high-bandwidth networking, AWS Batch for scaling computing jobs, AWS ParallelCluster for simplified cluster deployment, and Amazon FSx for high-performance file systems. These services collectively provide a flexible and scalable environment tailored to diverse HPC workloads. -
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NVIDIA Modulus
NVIDIA
NVIDIA Modulus is a neural network framework that blends the power of physics in the form of governing partial differential equations (PDEs) with data to build high-fidelity, parameterized surrogate models with near-real-time latency. Whether you’re looking to get started with AI-driven physics problems or designing digital twin models for complex non-linear, multi-physics systems, NVIDIA Modulus can support your work. Offers building blocks for developing physics machine learning surrogate models that combine both physics and data. The framework is generalizable to different domains and use cases—from engineering simulations to life sciences and from forward simulations to inverse/data assimilation problems. Provides parameterized system representation that solves for multiple scenarios in near real time, letting you train once offline to infer in real time repeatedly. -
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FutureHouse
FutureHouse
FutureHouse is a nonprofit AI research lab focused on automating scientific discovery in biology and other complex sciences. FutureHouse features superintelligent AI agents designed to assist scientists in accelerating research processes. It is optimized for retrieving and summarizing information from scientific literature, achieving state-of-the-art performance on benchmarks like RAG-QA Arena's science benchmark. It employs an agentic approach, allowing for iterative query expansion, LLM re-ranking, contextual summarization, and document citation traversal to enhance retrieval accuracy. FutureHouse also offers a framework for training language agents on challenging scientific tasks, enabling agents to perform tasks such as protein engineering, literature summarization, and molecular cloning. Their LAB-Bench benchmark evaluates language models on biology research tasks, including information extraction, database retrieval, etc. -
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Azure CycleCloud
Microsoft
Create, manage, operate, and optimize HPC and big compute clusters of any scale. Deploy full clusters and other resources, including scheduler, compute VMs, storage, networking, and cache. Customize and optimize clusters through advanced policy and governance features, including cost controls, Active Directory integration, monitoring, and reporting. Use your current job scheduler and applications without modification. Give admins full control over which users can run jobs, as well as where and at what cost. Take advantage of built-in autoscaling and battle-tested reference architectures for a wide range of HPC workloads and industries. CycleCloud supports any job scheduler or software stack—from proprietary in-house to open-source, third-party, and commercial applications. Your resource demands evolve over time, and your cluster should, too. With scheduler-aware autoscaling, you can fit your resources to your workload.Starting Price: $0.01 per hour -
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LeapSpace
Elsevier
LeapSpace is a research-grade, AI-assisted workspace developed by Elsevier, designed to help academic and corporate researchers move from curiosity to discovery faster within a secure, trusted environment. It combines responsible AI with one of the world’s most comprehensive collections of peer-reviewed scientific content, including millions of full-text articles, books, and over 100 million abstracts from thousands of publishers, ensuring that every insight is grounded in verified evidence rather than unfiltered web data. It uses natural-language queries to explore complex research topics, generating structured, cited responses that allow users to review original sources and validate findings directly. LeapSpace supports the full research workflow by enabling users to generate ideas, plan projects, analyze literature, compare studies, and produce in-depth reports that highlight patterns, contradictions, and gaps in existing research. -
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HPCWorks
Siemens
HPCWorks makes high-performance computing fast, efficient, and productive, on-premises and in the cloud. It helps teams expertly manage IT complexity, streamline administration, control costs, and enable the latest AI and mixed workloads with a complete HPC portfolio. Designed to power critical HPC, AI, and high-throughput workloads across applications such as healthcare, weather prediction, chip design, simulation, and analytics, HPCWorks helps organizations optimize computing environments from end to end. It supports GPU acceleration, rapid scaling, flexible scheduling, and workflow design for today’s largest AI workloads. Its agentic AI assistant can estimate job resource requirements, reduce wait times, and improve job throughput by learning from new data over time. HPCWorks also provides optimal job scheduling and workload management, helping teams reduce wait times, minimize downtime, prioritize critical tasks, and manage nodes, CPUs, cloud bursting, licenses, GPUs, etc. -
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Covalent
Agnostiq
Covalent’s serverless HPC architecture allows you to easily scale jobs from your laptop to your HPC/Cloud. Covalent is a Pythonic workflow tool for computational scientists, AI/ML software engineers, and anyone who needs to run experiments on limited or expensive computing resources including quantum computers, HPC clusters, GPU arrays, and cloud services. Covalent enables a researcher to run computation tasks on an advanced hardware platform – such as a quantum computer or serverless HPC cluster – using a single line of code. The latest release of Covalent includes two new feature sets and three major enhancements. True to its modular nature, Covalent now allows users to define custom pre- and post-hooks to electrons to facilitate various use cases from setting up remote environments (using DepsPip) to running custom functions.Starting Price: Free -
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Quartus® Prime Design Software is a powerful, integrated FPGA development environment built to scale with complex designs. It supports the full design flow, from design entry and synthesis to optimization, verification, and simulation. The platform is engineered to deliver advanced performance on devices with millions of logic elements. Quartus Prime includes comprehensive tools for timing, power, and thermal analysis to ensure reliable and efficient designs. Its modular editions allow teams to choose the right level of capability for their project needs. The software streamlines development with automation, debugging, and visualization features. Quartus Prime enables engineers to move from concept to deployment with confidence.
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23
FieldView
Intelligent Light
Over the past two decades, software technologies have advanced greatly and HPC computing has scaled by orders of magnitude. Our human ability to comprehend simulation results has remained the same. Simply making plots and movies in the traditional way does not scale when dealing with multi-billion cell meshes or ten’s of thousands of timesteps. Automated solution assessment is accelerated when features and quantitative properties can be produced directly via eigen analysis or machine learning. Easy-to-use industry standard FieldView desktop coupled to the powerful VisIt Prime backend. -
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NVIDIA HPC SDK
NVIDIA
The NVIDIA HPC Software Development Kit (SDK) includes the proven compilers, libraries and software tools essential to maximizing developer productivity and the performance and portability of HPC applications. The NVIDIA HPC SDK C, C++, and Fortran compilers support GPU acceleration of HPC modeling and simulation applications with standard C++ and Fortran, OpenACC® directives, and CUDA®. GPU-accelerated math libraries maximize performance on common HPC algorithms, and optimized communications libraries enable standards-based multi-GPU and scalable systems programming. Performance profiling and debugging tools simplify porting and optimization of HPC applications, and containerization tools enable easy deployment on-premises or in the cloud. With support for NVIDIA GPUs and Arm, OpenPOWER, or x86-64 CPUs running Linux, the HPC SDK provides the tools you need to build NVIDIA GPU-accelerated HPC applications. -
25
Energy2D
The Concord Consortium
Based on computational physics, Energy2D is an interactive multiphysics simulation program that models all three modes of heat transfer, conduction, convection, and radiation, and their coupling with particle dynamics. Energy2D runs quickly on most computers and eliminates the switches among preprocessors, solvers, and postprocessors typically needed to perform computational fluid dynamics simulations. It allows you to design "computational experiments" to test a scientific hypothesis or solve an engineering problem without resorting to complex mathematics. Work is also underway to incorporate other types of energy transformations and support multiple types of fluids. The conduction part of Energy2D is highly accurate, but the convection and radiation parts are not 100% accurate. Hence, in cases that involve convection and radiation, Energy2D results should be considered qualitative. More than 40 scientific papers have used Energy2D as a research tool.Starting Price: Free -
26
ScaleCloud
ScaleMatrix
Data-intensive AI, IoT and HPC workloads requiring multiple parallel processes have always run best on expensive high-end processors or accelerators, such as Graphic Processing Units (GPU). Moreover, when running compute-intensive workloads on cloud-based solutions, businesses and research organizations have had to accept tradeoffs, many of which were problematic. For example, the age of processors and other hardware in cloud environments is often incompatible with the latest applications or high energy expenditure levels that cause concerns related to environmental values. In other cases, certain aspects of cloud solutions have simply been frustrating to deal with. This has limited flexibility for customized cloud environments to support business needs or trouble finding right-size billing models or support. -
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Fuzzball
CIQ
Fuzzball accelerates innovation for researchers and scientists by eliminating the burdens of infrastructure provisioning and management. Fuzzball streamlines and optimizes high-performance computing (HPC) workload design and execution. A user-friendly GUI for designing, editing, and executing HPC jobs. Comprehensive control and automation of all HPC tasks via CLI. Automated data ingress and egress with full compliance logs. Native integration with GPUs and both on-prem and cloud storage on-prem and cloud storage. Human-readable, portable workflow files that execute anywhere. CIQ’s Fuzzball modernizes traditional HPC with an API-first, container-optimized architecture. Operating on Kubernetes, it provides all the security, performance, stability, and convenience found in modern software and infrastructure. Fuzzball not only abstracts the infrastructure layer but also automates the orchestration of complex workflows, driving greater efficiency and collaboration. -
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ESPResSo
ESPResSo
ESPResSo, the Extensible Simulation Package for Research on Soft Matter, is a highly versatile open source simulation package for performing and analyzing scientific molecular dynamics and Monte Carlo many-particle simulations. It is designed as a universal tool for simulating a variety of soft matter systems, especially coarse-grained atomistic or bead-spring models used in physics, chemistry, molecular biology, and process engineering. ESPResSo can be used to simulate polymers, liquid crystals, colloids, polyelectrolytes, ferrofluids, gels, biological systems, DNA, lipid membranes, bacterial motion, and super-capacitors. In coarse-grained models, a group of atoms or molecules is treated as a single bead, allowing researchers to investigate larger time and length scales than would be practical with fully atomistic simulations. ESPResSo supports classical molecular dynamics simulations in different statistical ensembles.Starting Price: Free -
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Amazon Braket
Amazon
Easily work with different types of quantum computers and circuit simulators using a consistent set of development tools. Build quantum projects on a trusted cloud with simple pricing and management controls for both quantum and classical workloads. Run hybrid quantum-classical algorithms faster with priority access to quantum computers and no classical infrastructure to manage. Reserve dedicated device access and engage directly with quantum computing specialists using Braket Direct. Accelerate scientific discovery with tools for algorithm development and support from the AWS Cloud Credit for Research Program. Push the boundaries of quantum hardware research with easy access to superconducting, trapped ion, and neutral atom devices. Bring software for quantum computing to market rapidly with Amazon Braket’s software development kit, simple pricing, and workflow management.Starting Price: $0.08000 per month -
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TrinityX
Cluster Vision
TrinityX is an open source cluster management system developed by ClusterVision, designed to provide 24/7 oversight for High-Performance Computing (HPC) and Artificial Intelligence (AI) environments. It offers a dependable, SLA-compliant support system, allowing users to focus entirely on their research while managing complex technologies such as Linux, SLURM, CUDA, InfiniBand, Lustre, and Open OnDemand. TrinityX streamlines cluster deployment through an intuitive interface, guiding users step-by-step to configure clusters for diverse uses like container orchestration, traditional HPC, and InfiniBand/RDMA architectures. Leveraging the BitTorrent protocol, enables rapid deployment of AI/HPC nodes, accommodating setups in minutes. The platform provides a comprehensive dashboard offering real-time insights into cluster metrics, resource utilization, and workload distribution, facilitating the identification of bottlenecks and optimization of resource allocation.Starting Price: Free -
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NVIDIA GPU-Optimized AMI
Amazon
The NVIDIA GPU-Optimized AMI is a virtual machine image for accelerating your GPU accelerated Machine Learning, Deep Learning, Data Science and HPC workloads. Using this AMI, you can spin up a GPU-accelerated EC2 VM instance in minutes with a pre-installed Ubuntu OS, GPU driver, Docker and NVIDIA container toolkit. This AMI provides easy access to NVIDIA's NGC Catalog, a hub for GPU-optimized software, for pulling & running performance-tuned, tested, and NVIDIA certified docker containers. The NGC catalog provides free access to containerized AI, Data Science, and HPC applications, pre-trained models, AI SDKs and other resources to enable data scientists, developers, and researchers to focus on building and deploying solutions. This GPU-optimized AMI is free with an option to purchase enterprise support offered through NVIDIA AI Enterprise. For how to get support for this AMI, scroll down to 'Support Information'Starting Price: $3.06 per hour -
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Lustre
OpenSFS and EOFS
The Lustre file system is an open-source, parallel file system that supports many requirements of leadership class HPC simulation environments. Whether you’re a member of our diverse development community or considering the Lustre file system as a parallel file system solution, these pages offer a wealth of resources and support to meet your needs. The Lustre file system provides a POSIX-compliant file system interface, which can scale to thousands of clients, petabytes of storage, and hundreds of gigabytes per second of I/O bandwidth. The key components of the Lustre file system are the Metadata Servers (MDS), the Metadata Targets (MDT), Object Storage Servers (OSS), Object Server Targets (OST), and the Lustre clients. Lustre is purpose-built to provide a coherent, global POSIX-compliant namespace for very large-scale computer infrastructure, including the world's largest supercomputer platforms. It can support hundreds of petabytes of data storage.Starting Price: Free -
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Amazon EC2 P5 Instances
Amazon
Amazon Elastic Compute Cloud (Amazon EC2) P5 instances, powered by NVIDIA H100 Tensor Core GPUs, and P5e and P5en instances powered by NVIDIA H200 Tensor Core GPUs deliver the highest performance in Amazon EC2 for deep learning and high-performance computing applications. They help you accelerate your time to solution by up to 4x compared to previous-generation GPU-based EC2 instances, and reduce the cost to train ML models by up to 40%. These instances help you iterate on your solutions at a faster pace and get to market more quickly. You can use P5, P5e, and P5en instances for training and deploying increasingly complex large language models and diffusion models powering the most demanding generative artificial intelligence applications. These applications include question-answering, code generation, video and image generation, and speech recognition. You can also use these instances to deploy demanding HPC applications at scale for pharmaceutical discovery. -
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Azure HPC
Microsoft
Azure high-performance computing (HPC). Power breakthrough innovations, solve complex problems, and optimize your compute-intensive workloads. Build and run your most demanding workloads in the cloud with a full stack solution purpose-built for HPC. Deliver supercomputing power, interoperability, and near-infinite scalability for compute-intensive workloads with Azure Virtual Machines. Empower decision-making and deliver next-generation AI with industry-leading Azure AI and analytics services. Help secure your data and applications and streamline compliance with multilayered, built-in security and confidential computing. -
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MPI for Python (mpi4py)
MPI for Python
Over the last years, high performance computing has become an affordable resource to many more researchers in the scientific community than ever before. The conjunction of quality open source software and commodity hardware strongly influenced the now widespread popularity of Beowulf class clusters and cluster of workstations. Among many parallel computational models, message-passing has proven to be an effective one. This paradigm is specially suited for (but not limited to) distributed memory architectures and is used in today’s most demanding scientific and engineering application related to modeling, simulation, design, and signal processing. However, portable message-passing parallel programming used to be a nightmare in the past because of the many incompatible options developers were faced to. Fortunately, this situation definitely changed after the MPI Forum released its standard specification.Starting Price: Free -
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Bright Cluster Manager
NVIDIA
NVIDIA Bright Cluster Manager offers fast deployment and end-to-end management for heterogeneous high-performance computing (HPC) and AI server clusters at the edge, in the data center, and in multi/hybrid-cloud environments. It automates provisioning and administration for clusters ranging in size from a couple of nodes to hundreds of thousands, supports CPU-based and NVIDIA GPU-accelerated systems, and enables orchestration with Kubernetes. Heterogeneous high-performance Linux clusters can be quickly built and managed with NVIDIA Bright Cluster Manager, supporting HPC, machine learning, and analytics applications that span from core to edge to cloud. NVIDIA Bright Cluster Manager is ideal for heterogeneous environments, supporting Arm® and x86-based CPU nodes, and is fully optimized for accelerated computing with NVIDIA GPUs and NVIDIA DGX™ systems. -
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Runway
Runway AI
Runway is an AI research and product company focused on building systems that simulate the world through generative models. The platform develops advanced video, world, and robotics models that can understand, generate, and interact with reality. Runway’s technology powers state-of-the-art generative video models like Gen-4.5 with cinematic motion and visual fidelity. It also pioneers General World Models (GWM) capable of simulating environments, agents, and physical interactions. Runway bridges art and science to transform media, entertainment, robotics, and real-time interaction. Its models enable creators, researchers, and organizations to explore new forms of storytelling and simulation. Runway is used by leading enterprises, studios, and academic institutions worldwide.Starting Price: $15 per user per month -
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HPE Pointnext
Hewlett Packard
This confluence put new demands on HPC storage as the input/output patterns of both workloads could not be more different. And it is happening right now. A recent study of the independent analyst firm Intersect360 found out that 63% of the HPC users today already are running machine learning programs. Hyperion Research forecasts that, at current course and speed, HPC storage spending in public sector organizations and enterprises will grow 57% faster than spending for HPC compute for the next three years. Seymour Cray once said, "Anyone can build a fast CPU. The trick is to build a fast system.” When it comes to HPC and AI, anyone can build fast file storage. The trick is to build a fast, but also cost-effective and scalable file storage system. We achieve this by embedding the leading parallel file systems into parallel storage products from HPE with cost effectiveness built in. -
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BIOVIA COSMO-RS
Dassault Systèmes
BIOVIA COSMO-RS is a comprehensive toolbox for modeling and predicting fluid phase properties, enabling chemical engineers, chemists, formulation engineers, and materials scientists to research and develop new solutions faster and more efficiently than with test and experimentation alone, thus accelerating innovation and reducing costs. COSMO-RS simulations are based on a sound scientific theory, which ensures robust and reliable predictions over the whole range of chemistry in the liquid state. The first-principle approach allows for predictions of new, not yet synthesized compounds, reaching beyond the known chemical space. BIOVIA’s COSMO team consists of the original inventors of COSMO-RS, assuring timely support and prime expertise to help solve even the most challenging problems in solution thermodynamics. Key benefits include a robust scientific foundation combining quantum chemistry and thermodynamics to ensure accuracy and reliability. -
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Sciscoper
Sciscoper
Sciscoper is an AI powered research assistant that is used to streamline and accelerate the literature review process for STEM researchers, academics, and R&D teams. Researchers often deal with hundreds or thousands of scientific papers scattered across different sources, making it difficult to extract meaningful insights efficiently. Sciscoper solves this by using AI and natural language processing to automatically: Summarize scientific papers and research findings. Extract key insights, concepts, and relationships across documents. Generate literature reviews with citations in multiple reference styles. Organize and index papers into a structured, searchable knowledge base for easy discovery. This allows users to focus less on manual reading and note-taking, and more on analyzing results, identifying research gaps, and producing new scientific knowledge.Starting Price: $20/user/month -
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Amazon S3 Express One Zone
Amazon
Amazon S3 Express One Zone is a high-performance, single-Availability Zone storage class purpose-built to deliver consistent single-digit millisecond data access for your most frequently accessed data and latency-sensitive applications. It offers data access speeds up to 10 times faster and requests costs up to 50% lower than S3 Standard. With S3 Express One Zone, you can select a specific AWS Availability Zone within an AWS Region to store your data, allowing you to co-locate your storage and compute resources in the same Availability Zone to further optimize performance, which helps lower compute costs and run workloads faster. Data is stored in a different bucket type, an S3 directory bucket, which supports hundreds of thousands of requests per second. Additionally, you can use S3 Express One Zone with services such as Amazon SageMaker Model Training, Amazon Athena, Amazon EMR, and AWS Glue Data Catalog to accelerate your machine learning and analytics workloads. -
42
Constructor Research
Constructor Tech
A powerful solution for accelerating computational experiments, enabling non-developers and non-ML researchers to obtain results quickly and efficiently. It streamlines scientific experiment orchestration and optimizes resource consumption for maximum efficiency. With an intuitive low-code interface, it facilitates computational modeling, team collaboration, and instant results sharing. The platform's optimized resource management ensures seamless hybrid infrastructure orchestration, integrating on-prem servers and HPC hardware for scientific use. Additionally, it enhances experiment reproducibility and enables interactive result sharing for improved research transparency and collaboration. -
43
Alchemite
Intellegens
Alchemite provides AI-augmented physical modeling and solutions that help organizations extract actionable insights from experimental and simulation data by combining machine learning with physics-informed models to improve prediction accuracy, reduce experimental costs, and optimize product and process development. Its solutions span materials discovery and design, predictive modelling of performance and reliability, multiscale modelling that connects atomistic to macroscopic behaviour, and automation of workflow tasks such as data integration, surrogate modelling, and model validation. It supports physics-aware neural networks and hybrid modelling approaches that respect underlying scientific laws while learning from data to enable faster and more accurate simulations, reduced reliance on expensive physical testing, and improved decision-making. Intellegens’ tools are applied in areas such as battery performance prediction, chemical process optimization, etc. -
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Intel Tiber AI Cloud
Intel
Intel® Tiber™ AI Cloud is a powerful platform designed to scale AI workloads with advanced computing resources. It offers specialized AI processors, such as the Intel Gaudi AI Processor and Max Series GPUs, to accelerate model training, inference, and deployment. Optimized for enterprise-level AI use cases, this cloud solution enables developers to build and fine-tune models with support for popular libraries like PyTorch. With flexible deployment options, secure private cloud solutions, and expert support, Intel Tiber™ ensures seamless integration, fast deployment, and enhanced model performance.Starting Price: Free -
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CAESIM
Adaptive Research
Adaptive Research is pleased to announce the immediate release of the CAESIM 2024 simulation platform, providing advanced computational fluid dynamics modeling with multi-physics capabilities. The new software release provides new tools and capabilities that optimize the modeling process and provide the CFD engineer with fast simulation solutions.Starting Price: $1295/annual standard -
46
Arm Forge
Arm
Build reliable and optimized code for the right results on multiple Server and HPC architectures, from the latest compilers and C++ standards to Intel, 64-bit Arm, AMD, OpenPOWER, and Nvidia GPU hardware. Arm Forge combines Arm DDT, the leading debugger for time-saving high-performance application debugging, Arm MAP, the trusted performance profiler for invaluable optimization advice across native and Python HPC codes, and Arm Performance Reports for advanced reporting capabilities. Arm DDT and Arm MAP are also available as standalone products. Efficient application development for Linux Server and HPC with Full technical support from Arm experts. Arm DDT is the debugger of choice for developing of C++, C, or Fortran parallel, and threaded applications on CPUs, and GPUs. Its powerful intuitive graphical interface helps you easily detect memory bugs and divergent behavior at all scales, making Arm DDT the number one debugger in research, industry, and academia. -
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The Nimbix Supercomputing Suite is a set of flexible and secure as-a-service high-performance computing (HPC) solutions. This as-a-service model for HPC, AI, and Quantum in the cloud provides customers with access to one of the broadest HPC and supercomputing portfolios, from hardware to bare metal-as-a-service to the democratization of advanced computing in the cloud across public and private data centers. Nimbix Supercomputing Suite allows you access to HyperHub Application Marketplace, our high-performance marketplace with over 1,000 applications and workflows. Leverage powerful dedicated BullSequana HPC servers as bare metal-as-a-service for the best of infrastructure and on-demand scalability, convenience, and agility. Federated supercomputing-as-a-service offers a unified service console to manage all compute zones and regions in a public or private HPC, AI, and supercomputing federation.
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Vensim
Ventana Systems
Vensim® is the software of choice for thousands of analysts, consultants, and researchers worldwide for building high-quality simulation models in business, scientific, environmental, and social systems. Vensim integrates into one environment a powerful suite of tools for developing, testing, interpreting, and distributing models. These tools include cause-and-effect diagramming, graphical and textual model construction, easy reproduction of model structure using subscripts (arrays), Monte Carlo sensitivity analysis, optimization, data handling, and application interfaces. Further features enable advanced model resolution and fidelity. Vensim includes patented techniques to aid error detection, error prevention, and rapid comprehension of complex results.Starting Price: $50 per month -
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Amazon EC2 G4 Instances
Amazon
Amazon EC2 G4 instances are optimized for machine learning inference and graphics-intensive applications. It offers a choice between NVIDIA T4 GPUs (G4dn) and AMD Radeon Pro V520 GPUs (G4ad). G4dn instances combine NVIDIA T4 GPUs with custom Intel Cascade Lake CPUs, providing a balance of compute, memory, and networking resources. These instances are ideal for deploying machine learning models, video transcoding, game streaming, and graphics rendering. G4ad instances, featuring AMD Radeon Pro V520 GPUs and 2nd-generation AMD EPYC processors, deliver cost-effective solutions for graphics workloads. Both G4dn and G4ad instances support Amazon Elastic Inference, allowing users to attach low-cost GPU-powered inference acceleration to Amazon EC2 and reduce deep learning inference costs. They are available in various sizes to accommodate different performance needs and are integrated with AWS services such as Amazon SageMaker, Amazon ECS, and Amazon EKS. -
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oneAPI
Intel
Intel oneAPI is an open, unified programming model designed to simplify development across CPUs, GPUs, and other accelerators. It provides developers with a highly productive software stack for AI, HPC, and accelerated computing workloads. oneAPI supports scalable hybrid parallelism, enabling performance portability across different hardware architectures. The platform includes optimized libraries, SYCL-based C++ extensions, and powerful developer tools for profiling, debugging, and optimization. Developers can build, optimize, and deploy applications with confidence across data centers, edge systems, and PCs. oneAPI is built on open standards to avoid vendor lock-in while maximizing performance. It empowers developers to write code once and run it efficiently everywhere.
