Alternatives to oneAPI
Compare oneAPI alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to oneAPI in 2026. Compare features, ratings, user reviews, pricing, and more from oneAPI competitors and alternatives in order to make an informed decision for your business.
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Retool
Retool
Retool is an application development platform that enables developers to combine the benefits of traditional software development with a drag-and-drop UI editor and AI to build internal tools radically faster. Building in Retool fits with how you develop software today—deploy it anywhere, connect to any internal service, import your libraries, debug with your toolchain, and share it securely to users—ensuring good and well-governed software by default. Retool is used by industry leaders such as Amazon, American Express, DoorDash, OpenAI, and Mercedes Benz for mission critical custom software across operations, billing, and customer support.Starting Price: $10 per user per month -
2
Rocky Linux
Ctrl IQ, Inc.
CIQ empowers people to do amazing things by providing innovative and stable software infrastructure solutions for all computing needs. From the base operating system, through containers, orchestration, provisioning, computing, and cloud applications, CIQ works with every part of the technology stack to drive solutions for customers and communities with stable, scalable, secure production environments. CIQ is the founding support and services partner of Rocky Linux, and the creator of the next generation federated computing stack. - Rocky Linux, open, Secure Enterprise Linux - Apptainer, application Containers for High Performance Computing - Warewulf, cluster Management and Operating System Provisioning - HPC2.0, the Next Generation of High Performance Computing, a Cloud Native Federated Computing Platform - Traditional HPC, turnkey computing stack for traditional HPC -
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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. -
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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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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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OpenVINO
Intel
The Intel® Distribution of OpenVINO™ toolkit is an open-source AI development toolkit that accelerates inference across Intel hardware platforms. Designed to streamline AI workflows, it allows developers to deploy optimized deep learning models for computer vision, generative AI, and large language models (LLMs). With built-in tools for model optimization, the platform ensures high throughput and lower latency, reducing model footprint without compromising accuracy. OpenVINO™ is perfect for developers looking to deploy AI across a range of environments, from edge devices to cloud servers, ensuring scalability and performance across Intel architectures.Starting Price: Free -
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Arm Allinea Studio is a suite of tools for developing server and HPC applications on Arm-based platforms. It contains Arm-specific compilers and libraries, and debug and optimization tools. Arm Performance Libraries provide optimized standard core math libraries for high-performance computing applications on Arm processors. The library routines, which are available through both Fortran and C interfaces. Arm Performance Libraries are built with OpenMP across many BLAS, LAPACK, FFT, and sparse routines in order to maximize your performance in multi-processor environments.
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8
TotalView
Perforce
TotalView debugging software provides the specialized tools you need to quickly debug, analyze, and scale high-performance computing (HPC) applications. This includes highly dynamic, parallel, and multicore applications that run on diverse hardware — from desktops to supercomputers. Improve HPC development efficiency, code quality, and time-to-market with TotalView’s powerful tools for faster fault isolation, improved memory optimization, and dynamic visualization. Simultaneously debug thousands of threads and processes. Purpose-built for multicore and parallel computing, TotalView delivers a set of tools providing unprecedented control over processes and thread execution, along with deep visibility into program states and data. -
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Modular
Modular
The future of AI development starts here. Modular is an integrated, composable suite of tools that simplifies your AI infrastructure so your team can develop, deploy, and innovate faster. Modular’s inference engine unifies AI industry frameworks and hardware, enabling you to deploy to any cloud or on-prem environment with minimal code changes – unlocking unmatched usability, performance, and portability. Seamlessly move your workloads to the best hardware for the job without rewriting or recompiling your models. Avoid lock-in and take advantage of cloud price efficiencies and performance improvements without migration costs. -
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Arm MAP
Arm
No need to change your code or the way you build it. Profiling for applications running on more than one server and multiple processes. Clear views of bottlenecks in I/O, in computing, in a thread, or in multi-process activity. Deep insight into actual processor instruction types that affect your performance. View memory usage over time to discover high watermarks and changes across the complete memory footprint. Arm MAP is a unique scalable low-overhead profiler, available standalone or as part of the Arm Forge debug and profile suite. It helps server and HPC code developers to accelerate their software by revealing the causes of slow performance. It is used from multicore Linux workstations through to supercomputers. You can profile realistic test cases that you care most about with typically under 5% runtime overhead. The interactive user interface is clear and intuitive, designed for developers and computational scientists. -
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Amazon EC2 UltraClusters
Amazon
Amazon EC2 UltraClusters enable you to scale to thousands of GPUs or purpose-built machine learning accelerators, such as AWS Trainium, providing on-demand access to supercomputing-class performance. They democratize supercomputing for ML, generative AI, and high-performance computing developers through a simple pay-as-you-go model without setup or maintenance costs. UltraClusters consist of thousands of accelerated EC2 instances co-located in a given AWS Availability Zone, interconnected using Elastic Fabric Adapter (EFA) networking in a petabit-scale nonblocking network. This architecture offers high-performance networking and access to Amazon FSx for Lustre, a fully managed shared storage built on a high-performance parallel file system, enabling rapid processing of massive datasets with sub-millisecond latencies. EC2 UltraClusters provide scale-out capabilities for distributed ML training and tightly coupled HPC workloads, reducing training times. -
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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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Intel Open Edge Platform
Intel
The Intel Open Edge Platform simplifies the development, deployment, and scaling of AI and edge computing solutions on standard hardware with cloud-like efficiency. It provides a curated set of components and workflows that accelerate AI model creation, optimization, and application development. From vision models to generative AI and large language models (LLM), the platform offers tools to streamline model training and inference. By integrating Intel’s OpenVINO toolkit, it ensures enhanced performance on Intel CPUs, GPUs, and VPUs, allowing organizations to bring AI applications to the edge with ease. -
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QumulusAI
QumulusAI
QumulusAI delivers supercomputing without constraint, combining scalable HPC with grid-independent data centers to break bottlenecks and power the future of AI. QumulusAI is universalizing access to AI supercomputing, removing the constraints of legacy HPC and delivering the scalable, high-performance computing AI demands today. And tomorrow too. No virtualization overhead, no noisy neighbors, just dedicated, direct access to AI servers optimized with NVIDIA’s latest GPUs (H200) and Intel/AMD CPUs. QumulusAI offers HPC infrastructure uniquely configured around your specific workloads, instead of legacy providers’ one-size-fits-all approach. We collaborate with you through design, deployment, to ongoing optimization, adapting as your AI projects evolve, so you get exactly what you need at each step. We own the entire stack. That means better performance, greater control, and more predictable costs than with other providers who coordinate with third-party vendors. -
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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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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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Azure FXT Edge Filer
Microsoft
Create cloud-integrated hybrid storage that works with your existing network-attached storage (NAS) and Azure Blob Storage. This on-premises caching appliance optimizes access to data in your datacenter, in Azure, or across a wide-area network (WAN). A combination of software and hardware, Microsoft Azure FXT Edge Filer delivers high throughput and low latency for hybrid storage infrastructure supporting high-performance computing (HPC) workloads.Scale-out clustering provides non-disruptive NAS performance scaling. Join up to 24 FXT nodes per cluster to scale to millions of IOPS and hundreds of GB/s. When you need performance and scale in file-based workloads, Azure FXT Edge Filer keeps your data on the fastest path to processing resources. Managing data storage is easy with Azure FXT Edge Filer. Shift aging data to Azure Blob Storage to keep it easily accessible with minimal latency. Balance on-premises and cloud storage. -
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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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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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Xilinx
Xilinx
The Xilinx’s AI development platform for AI inference on Xilinx hardware platforms consists of optimized IP, tools, libraries, models, and example designs. It is designed with high efficiency and ease-of-use in mind, unleashing the full potential of AI acceleration on Xilinx FPGA and ACAP. Supports mainstream frameworks and the latest models capable of diverse deep learning tasks. Provides a comprehensive set of pre-optimized models that are ready to deploy on Xilinx devices. You can find the closest model and start re-training for your applications! Provides a powerful open source quantizer that supports pruned and unpruned model quantization, calibration, and fine tuning. The AI profiler provides layer by layer analysis to help with bottlenecks. The AI library offers open source high-level C++ and Python APIs for maximum portability from edge to cloud. Efficient and scalable IP cores can be customized to meet your needs of many different applications. -
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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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AWS ParallelCluster
Amazon
AWS ParallelCluster is an open-source cluster management tool that simplifies the deployment and management of High-Performance Computing (HPC) clusters on AWS. It automates the setup of required resources, including compute nodes, a shared filesystem, and a job scheduler, supporting multiple instance types and job submission queues. Users can interact with ParallelCluster through a graphical user interface, command-line interface, or API, enabling flexible cluster configuration and management. The tool integrates with job schedulers like AWS Batch and Slurm, facilitating seamless migration of existing HPC workloads to the cloud with minimal modifications. AWS ParallelCluster is available at no additional charge; users only pay for the AWS resources consumed by their applications. With AWS ParallelCluster, you can use a simple text file to model, provision, and dynamically scale the resources needed for your applications in an automated and secure manner. -
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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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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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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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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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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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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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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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Qlustar
Qlustar
The ultimate full-stack solution for setting up, managing, and scaling clusters with ease, control, and performance. Qlustar empowers your HPC, AI, and storage environments with unmatched simplicity and robust capabilities. From bare-metal installation with the Qlustar installer to seamless cluster operations, Qlustar covers it all. Set up and manage your clusters with unmatched simplicity and efficiency. Designed to grow with your needs, handling even the most complex workloads effortlessly. Optimized for speed, reliability, and resource efficiency in demanding environments. Upgrade your OS or manage security patches without the need for reinstallations. Regular and reliable updates keep your clusters safe from vulnerabilities. Qlustar optimizes your computing power, delivering peak efficiency for high-performance computing environments. Our solution offers robust workload management, built-in high availability, and an intuitive interface for streamlined operations.Starting Price: Free -
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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 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. -
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DeepSpeed
Microsoft
DeepSpeed is an open source deep learning optimization library for PyTorch. It's designed to reduce computing power and memory use, and to train large distributed models with better parallelism on existing computer hardware. DeepSpeed is optimized for low latency, high throughput training. DeepSpeed can train DL models with over a hundred billion parameters on the current generation of GPU clusters. It can also train up to 13 billion parameters in a single GPU. DeepSpeed is developed by Microsoft and aims to offer distributed training for large-scale models. It's built on top of PyTorch, which specializes in data parallelism.Starting Price: Free -
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Together AI
Together AI
Together AI provides an AI-native cloud platform built to accelerate training, fine-tuning, and inference on high-performance GPU clusters. Engineered for massive scale, the platform supports workloads that process trillions of tokens without performance drops. Together AI delivers industry-leading cost efficiency by optimizing hardware, scheduling, and inference techniques, lowering total cost of ownership for demanding AI workloads. With deep research expertise, the company brings cutting-edge models, hardware, and runtime innovations—like ATLAS runtime-learning accelerators—directly into production environments. Its full-stack ecosystem includes a model library, inference APIs, fine-tuning capabilities, pre-training support, and instant GPU clusters. Designed for AI-native teams, Together AI helps organizations build and deploy advanced applications faster and more affordably.Starting Price: $0.0001 per 1k tokens -
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Warewulf
Warewulf
Warewulf is a cluster management and provisioning system that has pioneered stateless node management for over two decades. It enables the provisioning of containers directly onto bare metal hardware at massive scales, ranging from tens to tens of thousands of compute systems while maintaining simplicity and flexibility. The platform is extensible, allowing users to modify default functionalities and node images to suit various clustering use cases. Warewulf supports stateless provisioning with SELinux, per-node asset key-based provisioning, and access controls, ensuring secure deployments. Its minimal system requirements and ease of optimization, customization, and integration make it accessible to diverse industries. Supported by OpenHPC and contributors worldwide, Warewulf stands as a successful HPC cluster platform utilized across various sectors. Minimal system requirements, easy to get started, and simple to optimize, customize, and integrate.Starting Price: Free -
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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. -
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Vertesia
Vertesia
Vertesia is a unified, low-code generative AI platform that enables enterprise teams to rapidly build, deploy, and operate GenAI applications and agents at scale. Designed for both business professionals and IT specialists, Vertesia offers a frictionless development experience, allowing users to go from prototype to production without extensive timelines or heavy infrastructure. It supports multiple generative AI models from leading inference providers, providing flexibility and preventing vendor lock-in. Vertesia's agentic retrieval-augmented generation (RAG) pipeline enhances generative AI accuracy and performance by automating and accelerating content preparation, including intelligent document processing and semantic chunking. With enterprise-grade security, SOC2 compliance, and support for leading cloud infrastructures like AWS, GCP, and Azure, Vertesia ensures secure and scalable deployments. -
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Moab HPC Suite
Adaptive Computing
Moab® HPC Suite is a workload and resource orchestration platform that automates the scheduling, managing, monitoring, and reporting of HPC workloads on massive scale. Its patented intelligence engine uses multi-dimensional policies and advanced future modeling to optimize workload start and run times on diverse resources. These policies balance high utilization and throughput goals with competing workload priorities and SLA requirements, thereby accomplishing more work in less time and in the right priority order. Moab HPC Suite optimizes the value and usability of HPC systems while reducing management cost and complexity. -
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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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HPE Performance Cluster Manager
Hewlett Packard Enterprise
HPE Performance Cluster Manager (HPCM) delivers an integrated system management solution for Linux®-based high performance computing (HPC) clusters. HPE Performance Cluster Manager provides complete provisioning, management, and monitoring for clusters scaling up to Exascale sized supercomputers. The software enables fast system setup from bare-metal, comprehensive hardware monitoring and management, image management, software updates, power management, and cluster health management. Additionally, it makes scaling HPC clusters easier and efficient while providing integration with a plethora of 3rd party tools for running and managing workloads. HPE Performance Cluster Manager reduces the time and resources spent administering HPC systems - lowering total cost of ownership, increasing productivity and providing a better return on hardware investments. -
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Kao Data
Kao Data
Kao Data leads the industry, pioneering the development and operation of data centres engineered for AI and advanced computing. With a hyperscale-inspired and industrial scale platform, we provide our customers with a secure, scalable and sustainable home for their compute. Kao Data leads the industry in pioneering the development and operation of data centres engineered for AI and advanced computing. With our Harlow campus the home for a variety of mission-critical HPC deployments - we are the UK’s number one choice for power-intensive, high density, GPU-powered computing. With rapid on-ramps into all major cloud providers, we can make your hybrid AI and HPC ambitions a reality. -
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NVIDIA DGX Cloud
NVIDIA
NVIDIA DGX Cloud offers a fully managed, end-to-end AI platform that leverages the power of NVIDIA’s advanced hardware and cloud computing services. This platform allows businesses and organizations to scale AI workloads seamlessly, providing tools for machine learning, deep learning, and high-performance computing (HPC). DGX Cloud integrates seamlessly with leading cloud providers, delivering the performance and flexibility required to handle the most demanding AI applications. This service is ideal for businesses looking to enhance their AI capabilities without the need to manage physical infrastructure. -
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Build, run and manage AI models, and optimize decisions at scale across any cloud. IBM Watson Studio empowers you to operationalize AI anywhere as part of IBM Cloud Pak® for Data, the IBM data and AI platform. Unite teams, simplify AI lifecycle management and accelerate time to value with an open, flexible multicloud architecture. Automate AI lifecycles with ModelOps pipelines. Speed data science development with AutoAI. Prepare and build models visually and programmatically. Deploy and run models through one-click integration. Promote AI governance with fair, explainable AI. Drive better business outcomes by optimizing decisions. Use open source frameworks like PyTorch, TensorFlow and scikit-learn. Bring together the development tools including popular IDEs, Jupyter notebooks, JupterLab and CLIs — or languages such as Python, R and Scala. IBM Watson Studio helps you build and scale AI with trust and transparency by automating AI lifecycle management.
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Amazon SageMaker HyperPod
Amazon
Amazon SageMaker HyperPod is a purpose-built, resilient compute infrastructure that simplifies and accelerates the development of large AI and machine-learning models by handling distributed training, fine-tuning, and inference across clusters with hundreds or thousands of accelerators, including GPUs and AWS Trainium chips. It removes the heavy lifting involved in building and managing ML infrastructure by providing persistent clusters that automatically detect and repair hardware failures, automatically resume workloads, and optimize checkpointing to minimize interruption risk, enabling months-long training jobs without disruption. HyperPod offers centralized resource governance; administrators can set priorities, quotas, and task-preemption rules so compute resources are allocated efficiently among tasks and teams, maximizing utilization and reducing idle time. It also supports “recipes” and pre-configured settings to quickly fine-tune or customize foundation models. -
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AWS Elastic Fabric Adapter (EFA)
United States
Elastic Fabric Adapter (EFA) is a network interface for Amazon EC2 instances that enables customers to run applications requiring high levels of inter-node communications at scale on AWS. Its custom-built operating system (OS) bypass hardware interface enhances the performance of inter-instance communications, which is critical to scaling these applications. With EFA, High-Performance Computing (HPC) applications using the Message Passing Interface (MPI) and Machine Learning (ML) applications using NVIDIA Collective Communications Library (NCCL) can scale to thousands of CPUs or GPUs. As a result, you get the application performance of on-premises HPC clusters with the on-demand elasticity and flexibility of the AWS cloud. EFA is available as an optional EC2 networking feature that you can enable on any supported EC2 instance at no additional cost. Plus, it works with the most commonly used interfaces, APIs, and libraries for inter-node communications. -
46
SWE-Kit
Composio
SweKit let’s you build PR agents to review code, suggest improvements, enforce coding standards, identify potential issues, automate merge approvals, and provide feedback on best practices, streamlining the review process and enhancing code quality. Automate writing new features, debug complex issues, create and run tests, optimize code for performance, refactor for maintainability, and ensure best practices across the codebase, accelerating development and efficiency. Use highly optimized code analysis, advanced code indexing, and intelligent file navigation tools to explore and interact with large codebases effortlessly. Ask questions, trace dependencies, uncover logic flows, and gain instant insights, enabling seamless communication with complex code structures. Keep your documentation in sync with your code. Automatically update Mintlify documentation whenever changes are made to the codebase, ensuring that your docs stay accurate, up-to-date, and ready for your team and users.Starting Price: $49 per month -
47
NVIDIA Base Command
NVIDIA
NVIDIA Base Command™ is a software service for enterprise-class AI training that enables businesses and their data scientists to accelerate AI development. Part of the NVIDIA DGX™ platform, Base Command Platform provides centralized, hybrid control of AI training projects. It works with NVIDIA DGX Cloud and NVIDIA DGX SuperPOD. Base Command Platform, in combination with NVIDIA-accelerated AI infrastructure, provides a cloud-hosted solution for AI development, so users can avoid the overhead and pitfalls of deploying and running a do-it-yourself platform. Base Command Platform efficiently configures and manages AI workloads, delivers integrated dataset management, and executes them on right-sized resources ranging from a single GPU to large-scale, multi-node clusters in the cloud or on-premises. Because NVIDIA’s own engineers and researchers rely on it every day, the platform receives continuous software enhancements. -
48
NeuReality
NeuReality
NeuReality accelerates the possibilities of AI by offering a revolutionary solution that lowers the overall complexity, cost, and power consumption. While other companies also develop Deep Learning Accelerators (DLAs) for deployment, no other company connects the dots with a software platform purpose-built to help manage specific hardware infrastructure. NeuReality is the only company that bridges the gap between the infrastructure where AI inference runs and the MLOps ecosystem. NeuReality has developed a new architecture design to exploit the power of DLAs. This architecture enables inference through hardware with AI-over-fabric, an AI hypervisor, and AI-pipeline offload. -
49
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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50
Qualcomm AI Hub
Qualcomm
The Qualcomm AI Hub is a resource portal for developers aiming to build and deploy AI applications optimized for Qualcomm chipsets. With a library of pre-trained models, development tools, and platform-specific SDKs, it enables high-performance, low-power AI processing across smartphones, wearables, and edge devices.
