Alternatives to AWS HPC
Compare AWS HPC alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to AWS HPC in 2026. Compare features, ratings, user reviews, pricing, and more from AWS HPC competitors and alternatives in order to make an informed decision for your business.
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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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CoreWeave
CoreWeave
CoreWeave is a cloud infrastructure provider specializing in GPU-based compute solutions tailored for AI workloads. The platform offers scalable, high-performance GPU clusters that optimize the training and inference of AI models, making it ideal for industries like machine learning, visual effects (VFX), and high-performance computing (HPC). CoreWeave provides flexible storage, networking, and managed services to support AI-driven businesses, with a focus on reliability, cost efficiency, and enterprise-grade security. The platform is used by AI labs, research organizations, and businesses to accelerate their AI innovations. -
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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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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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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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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 -
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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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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. -
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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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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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Amazon EC2 Trn2 Instances
Amazon
Amazon EC2 Trn2 instances, powered by AWS Trainium2 chips, are purpose-built for high-performance deep learning training of generative AI models, including large language models and diffusion models. They offer up to 50% cost-to-train savings over comparable Amazon EC2 instances. Trn2 instances support up to 16 Trainium2 accelerators, providing up to 3 petaflops of FP16/BF16 compute power and 512 GB of high-bandwidth memory. To facilitate efficient data and model parallelism, Trn2 instances feature NeuronLink, a high-speed, nonblocking interconnect, and support up to 1600 Gbps of second-generation Elastic Fabric Adapter (EFAv2) network bandwidth. They are deployed in EC2 UltraClusters, enabling scaling up to 30,000 Trainium2 chips interconnected with a nonblocking petabit-scale network, delivering 6 exaflops of compute performance. The AWS Neuron SDK integrates natively with popular machine learning frameworks like PyTorch and TensorFlow. -
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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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Amazon EC2 Capacity Blocks for ML enable you to reserve accelerated compute instances in Amazon EC2 UltraClusters for your machine learning workloads. This service supports Amazon EC2 P5en, P5e, P5, and P4d instances, powered by NVIDIA H200, H100, and A100 Tensor Core GPUs, respectively, as well as Trn2 and Trn1 instances powered by AWS Trainium. You can reserve these instances for up to six months in cluster sizes ranging from one to 64 instances (512 GPUs or 1,024 Trainium chips), providing flexibility for various ML workloads. Reservations can be made up to eight weeks in advance. By colocating in Amazon EC2 UltraClusters, Capacity Blocks offer low-latency, high-throughput network connectivity, facilitating efficient distributed training. This setup ensures predictable access to high-performance computing resources, allowing you to plan ML development confidently, run experiments, build prototypes, and accommodate future surges in demand for ML applications.
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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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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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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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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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Amazon Elastic Block Store (EBS) is an easy to use, high-performance, block-storage service designed for use with Amazon Elastic Compute Cloud (EC2) for both throughput and transaction intensive workloads at any scale. A broad range of workloads, such as relational and non-relational databases, enterprise applications, containerized applications, big data analytics engines, file systems, and media workflows are widely deployed on Amazon EBS. You can choose from six different volume types to balance optimal price and performance. You can achieve single-digit-millisecond latency for high-performance database workloads such as SAP HANA or gigabyte per second throughput for large, sequential workloads such as Hadoop. You can change volume types, tune performance, or increase volume size without disrupting your critical applications, so you have cost-effective storage when you need it.
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IBM Spectrum LSF Suites is a workload management platform and job scheduler for distributed high-performance computing (HPC). Terraform-based automation to provision and configure resources for an IBM Spectrum LSF-based cluster on IBM Cloud is available. Increase user productivity and hardware use while reducing system management costs with our integrated solution for mission-critical HPC environments. The heterogeneous, highly scalable, and available architecture provides support for traditional high-performance computing and high-throughput workloads. It also works for big data, cognitive, GPU machine learning, and containerized workloads. With dynamic HPC cloud support, IBM Spectrum LSF Suites enables organizations to intelligently use cloud resources based on workload demand, with support for all major cloud providers. Take advantage of advanced workload management, with policy-driven scheduling, including GPU scheduling and dynamic hybrid cloud, to add capacity on demand.
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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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HPC-AI
HPC-AI
HPC-AI is an enterprise AI infrastructure and GPU cloud platform designed to accelerate deep learning training, inference, and large-scale compute workloads with high performance and cost efficiency. It delivers a pre-configured AI-optimized stack that enables rapid deployment and real-time inference while supporting demanding workloads that require high IOPS, ultra-low latency, and massive throughput. It provides a robust GPU cloud environment built for artificial intelligence, high-performance computing, and other compute-intensive applications, giving teams the tools needed to run complex workflows efficiently. At its core, the company’s software focuses on parallel and distributed training, inference, and fine-tuning of large neural networks, helping organizations reduce infrastructure costs while maintaining performance. It is powered in part by technologies such as Colossal-AI, which significantly accelerates model training and improves productivity.Starting Price: $3.05 per hour -
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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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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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Baidu Cloud Compute
Baidu AI Cloud
Baidu Cloud Compute (BCC) is a cloud computing service based on virtualization, distributed clusters and other technologies accumulated by Baidu over the years. Baidu Cloud Compute (BCC ) supports elastic scaling, minute-level rich and flexible billing mode, with image, snapshot, cloud security, and other value-added services, to provide you with a high-performance cloud server featuring a super high efficient cost ratio. It is suitable for high network packet receiving and sending scenarios and can support up to 22Gbps intranet bandwidth to meet the extremely high demand of Intranet transmission. With the latest generation of models, based on the second generation of Intel ® XEON ® scalable processor, XEON scalable platform, it has improved the overall performance, supporting a high-performance network, and is suitable for high computing scenarios. -
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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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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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Graph Engine
Microsoft
Graph Engine (GE) is a distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine. The distributed RAM store provides a globally addressable high-performance key-value store over a cluster of machines. Through the RAM store, GE enables the fast random data access power over a large distributed data set. The capability of fast data exploration and distributed parallel computing makes GE a natural large graph processing platform. GE supports both low-latency online query processing and high-throughput offline analytics on billion-node large graphs. Schema does matter when we need to process data efficiently. Strongly-typed data modeling is crucial for compact data storage, fast data access, and clear data semantics. GE is good at managing billions of run-time objects of varied sizes. One byte counts as the number of objects goes large. GE provides fast memory allocation and reallocation with high memory ratios. -
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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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Tencent Cloud GPU Service
Tencent
Cloud GPU Service is an elastic computing service that provides GPU computing power with high-performance parallel computing capabilities. As a powerful tool at the IaaS layer, it delivers high computing power for deep learning training, scientific computing, graphics and image processing, video encoding and decoding, and other highly intensive workloads. Improve your business efficiency and competitiveness with high-performance parallel computing capabilities. Set up your deployment environment quickly with auto-installed GPU drivers, CUDA, and cuDNN and preinstalled driver images. Accelerate distributed training and inference by using TACO Kit, an out-of-the-box computing acceleration engine provided by Tencent Cloud.Starting Price: $0.204/hour -
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Google Cloud Bigtable
Google
Google Cloud Bigtable is a fully managed, scalable NoSQL database service for large analytical and operational workloads. Fast and performant: Use Cloud Bigtable as the storage engine that grows with you from your first gigabyte to petabyte-scale for low-latency applications as well as high-throughput data processing and analytics. Seamless scaling and replication: Start with a single node per cluster, and seamlessly scale to hundreds of nodes dynamically supporting peak demand. Replication also adds high availability and workload isolation for live serving apps. Simple and integrated: Fully managed service that integrates easily with big data tools like Hadoop, Dataflow, and Dataproc. Plus, support for the open source HBase API standard makes it easy for development teams to get started. -
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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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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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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 FSx for Lustre
Amazon
Amazon FSx for Lustre is a fully managed service that provides high-performance, scalable storage for compute-intensive workloads. Built on the open-source Lustre file system, it offers sub-millisecond latencies, up to hundreds of gigabytes per second of throughput, and millions of IOPS, making it ideal for applications such as machine learning, high-performance computing, video processing, and financial modeling. FSx for Lustre integrates seamlessly with Amazon S3, allowing you to link file systems to S3 buckets. This integration enables transparent access and processing of S3 data from a high-performance file system, with the ability to import and export data between FSx for Lustre and S3. The service supports multiple deployment options, including scratch file systems for temporary storage and persistent file systems for long-term storage, as well as SSD and HDD storage types to optimize cost and performance based on workload requirements.Starting Price: $0.073 per GB per month -
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MegaETH
MegaETH
MegaETH is a next-generation blockchain execution platform built to deliver extreme performance and efficiency for decentralized applications and high-throughput workloads. To achieve this, MegaETH introduces a new state trie design that scales smoothly to terabytes of state data with minimal I/O cost. It implements a write-optimized storage backend to replace traditional high-amplification databases, ensuring fast, predictable read and write latencies. It uses just-in-time bytecode compilation to eliminate interpretation overhead and bring near native code speed to compute-intensive smart contracts. MegaETH also supports a two-pronged parallel execution model; block producers use a flexible concurrency protocol, while full nodes employ stateless validation to maximize parallel speedups. For network synchronization, MegaETH features a custom peer-to-peer protocol with compression techniques that allow even nodes with limited bandwidth to stay in sync at high throughput.Starting Price: Free -
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Azure Blob Storage
Microsoft
Massively scalable and secure object storage for cloud-native workloads, archives, data lakes, high-performance computing, and machine learning. Azure Blob Storage helps you create data lakes for your analytics needs, and provides storage to build powerful cloud-native and mobile apps. Optimize costs with tiered storage for your long-term data, and flexibly scale up for high-performance computing and machine learning workloads. Blob storage is built from the ground up to support the scale, security, and availability needs of mobile, web, and cloud-native application developers. Use it as a cornerstone for serverless architectures such as Azure Functions. Blob storage supports the most popular development frameworks, including Java, .NET, Python, and Node.js, and is the only cloud storage service that offers a premium, SSD-based object storage tier for low-latency and interactive scenarios.Starting Price: $0.00099 -
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Vcinity Radical X
Vcinity
Enabling local-like network access to eliminate the effects of latency. Purpose-built for hybrid and multi-cloud high-performance computing organizations that have a parallel file system in place, the Radical X™ (RAD X™) product family extends Remote Direct Memory Access (RDMA) over WAN and removes the distance barrier from data access and movement. RAD X extends your local services, applications, and infrastructure across virtually any WAN—creating an infrastructure that’s truly location independent. It provides low-latency, high-performance connectivity — allowing businesses to take command of geographically dispersed compute and storage resources, in real-time, to accelerate time to insights and action. RAD X provides robust security for your data, including single or dual-line-rate WAN encryption, without increasing latency or reducing data throughput. Its DataPrizmTM feature provides another layer of protection by distributing data over encrypted network paths. -
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Elastic Cloud Server (ECS) provides secure, scalable, on-demand computing resources, enabling you to flexibly deploy applications and workloads. Worry-free comprehensive security protection. Use general computing ECSs, which provide a balance of computing, memory, and network resources. This ECS type is ideal for light- and medium-load applications. Use memory-optimized ECSs, which have a large amount of memory and support ultra-high I/O EVS disks and flexible bandwidths. This ECS type is ideal for applications that process large volumes of data. Use disk-intensive ECSs, which are designed for applications requiring sequential read/write on ultra-large datasets in local storage (such as distributed Hadoop computing) as well as large-scale parallel data processing and log processing. Disk-intensive ECSs are HDD-compatible, feature a default network bandwidth of 10GE, and deliver high PPS and low network latency.Starting Price: $6.13 per month
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Linaro Forge
Linaro
Linaro Forge is an integrated HPC debugging and performance analysis suite that helps developers build reliable, optimized code for servers and high-performance computing environments by combining three core tools, Linaro DDT, a market-leading debugger for C, C++, Fortran, and Python applications; Linaro MAP, a performance profiler that highlights bottlenecks and suggests optimization strategies; and Linaro Performance Reports, which generate concise, one-page summaries of application performance. It supports a wide range of parallel architectures and programming models, including MPI, OpenMP, CUDA, and GPU-accelerated environments on x86-64, 64-bit Arm, and other CPUs and GPUs, and offers a common user interface that makes it easy to switch between debugging and profiling during development. -
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Crown Castle
Crown Castle
Our 100+ state-of-the-art, strategically located data centers, including colocation facilities all the way down to regen huts, combine with our ~80,000 route miles of fiber offering businesses and organizations high-bandwidth, low-latency connectivity between key network and enterprise locations. Data center infrastructure for accessing your most important functions, when you need them, including disaster recovery, business continuity, SaaS, cloud computing, physical redundancy and backup. A clean, secure environment with carrier-grade high-bandwidth, low-latency connectivity to store your mission-critical applications right at the network’s edge. You’ll have complete transparency to your fiber route enabling access to your most important functions, disaster recovery, business continuity, SaaS, cloud computing, physical redundancy and backup. We are a long-term data center operator with a proven track record and Network Operations Center that provides around-the-clock monitoring. -
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AWS EC2 Trn3 Instances
Amazon
Amazon EC2 Trn3 UltraServers are AWS’s newest accelerated computing instances, powered by the in-house Trainium3 AI chips and engineered specifically for high-performance deep-learning training and inference workloads. These UltraServers are offered in two configurations, a “Gen1” with 64 Trainium3 chips and a “Gen2” with up to 144 Trainium3 chips per UltraServer. The Gen2 configuration delivers up to 362 petaFLOPS of dense MXFP8 compute, 20 TB of HBM memory, and a staggering 706 TB/s of aggregate memory bandwidth, making it one of the highest-throughput AI compute platforms available. Interconnects between chips are handled by a new “NeuronSwitch-v1” fabric to support all-to-all communication patterns, which are especially important for large models, mixture-of-experts architectures, or large-scale distributed training. -
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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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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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Cirrascale
Cirrascale
Our high-throughput storage systems can serve millions of small, random files to GPU-based training servers accelerating overall training times. We offer high-bandwidth, low-latency networks for connecting distributed training servers as well as transporting data between storage and servers. Other cloud providers squeeze you with extra fees and charges to get your data out of their storage clouds, and those can add up fast. We consider ourselves an extension of your team. We work with you to set up scheduling services, help with best practices, and provide superior support. Workflows can vary from company to company. Cirrascale works to ensure you get the right solution for your needs to get you the best results. Cirrascale is the only provider that works with you to tailor your cloud instances to increase performance, remove bottlenecks, and optimize your workflow. Cloud-based solutions to accelerate your training, simulation, and re-simulation time.Starting Price: $2.49 per hour -
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NVIDIA Base Command Manager
NVIDIA
NVIDIA Base Command Manager offers fast deployment and end-to-end management for heterogeneous AI and high-performance computing clusters at the edge, in the data center, and in multi- and hybrid-cloud environments. It automates the provisioning and administration of clusters ranging in size from a couple of nodes to hundreds of thousands, supports NVIDIA GPU-accelerated and other systems, and enables orchestration with Kubernetes. The platform integrates with Kubernetes for workload orchestration and offers tools for infrastructure monitoring, workload management, and resource allocation. Base Command Manager is optimized for accelerated computing environments, making it suitable for diverse HPC and AI workloads. It is available with NVIDIA DGX systems and as part of the NVIDIA AI Enterprise software suite. High-performance Linux clusters can be quickly built and managed with NVIDIA Base Command Manager, supporting HPC, machine learning, and analytics applications. -
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Slurm
IBM
Slurm Workload Manager, formerly known as Simple Linux Utility for Resource Management (SLURM), is a free, open-source job scheduler and cluster management system for Linux and Unix-like kernels. It's designed to manage compute jobs on high performance computing (HPC) clusters and high throughput computing (HTC) environments, and is used by many of the world's supercomputers and computer clusters.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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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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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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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.
