Alternatives to HPCWorks
Compare HPCWorks alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to HPCWorks in 2026. Compare features, ratings, user reviews, pricing, and more from HPCWorks competitors and alternatives in order to make an informed decision for your business.
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SKUDONET
SKUDONET
SKUDONET Enterprise Edition is an Application Delivery and Security Platform built on Linux Debian 12.5 LTS for critical enterprise environments. Formerly known as Zevenet, it provides advanced L4/L7 load balancing, integrated WAF, TLS management with Let’s Encrypt and wildcard support, and protocol-aware traffic inspection across on-premises, hybrid, or cloud deployments, including SkudoCloud SaaS. A free trial is available for evaluation on the SKUDONET website. Key Features & Benefits: • High Availability: Clustering and failover to minimize downtime. • Advanced Security: WAF, L7 filtering, DoS protection, TLS with Let’s Encrypt and wildcard support. • Scalability: Optimized for high-throughput workloads with multi-core processing and efficient packet handling. • Traffic Control: Session persistence, custom routing rules, and granular L4/L7 inspection. • Centralized Management: Unified dashboard for configuration, monitoring, and policy automation.Starting Price: $1736/year/appliance -
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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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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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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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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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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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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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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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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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HPCWorks Grid Engine
Siemens
HPCWorks Grid Engine is a Siemens workload management solution designed to optimize distributed computing resources and improve performance across large HPC environments. It helps organizations increase throughput, manage shared resources, and support demanding workloads across on-premises, cloud, and hybrid infrastructures. The platform is built to handle large-scale AI and HPC workloads and has been proven with more than one million cores. HPCWorks Grid Engine supports efficient scheduling, resource utilization, containers, services, GPUs, and license-first scheduling to reduce wait times and downtime. It works with thousands of commercial and open-source applications across industries such as life sciences, manufacturing, and energy. With monitoring, reporting, quotas, limits, and priority policies, HPCWorks Grid Engine helps organizations align computing resources with business goals. -
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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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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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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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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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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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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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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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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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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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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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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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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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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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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 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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oneAPI
Intel
Intel oneAPI is an open, unified programming model designed to simplify development across CPUs, GPUs, and other accelerators. It provides developers with a highly productive software stack for AI, HPC, and accelerated computing workloads. oneAPI supports scalable hybrid parallelism, enabling performance portability across different hardware architectures. The platform includes optimized libraries, SYCL-based C++ extensions, and powerful developer tools for profiling, debugging, and optimization. Developers can build, optimize, and deploy applications with confidence across data centers, edge systems, and PCs. oneAPI is built on open standards to avoid vendor lock-in while maximizing performance. It empowers developers to write code once and run it efficiently everywhere. -
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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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UltiHash
UltiHash
UltiHash is lightning-fast object storage built for AI, analytics, and high-throughput data workloads. It is designed to make data storage more efficient by reducing storage consumption through built-in deduplication while still delivering the performance needed for modern data-intensive systems. UltiHash can run as a Kubernetes-native storage cluster on a team’s own infrastructure, ideally on flash-based storage, and connects to existing pipelines through a robust S3-compatible API. Teams can upload data, let UltiHash automatically reduce redundant storage, read data at high throughput, and connect the storage layer to GenAI, analytics, machine learning, lakehouse, and other data tools without changing their stack. It is optimized for modern flash architecture and is especially suited to “write once, read many” workloads where large datasets need to be accessed repeatedly and quickly.Starting Price: €0.15 per month -
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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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VMware HCX
Broadcom
Seamlessly extend your on-premises environments into cloud. VMware HCX streamlines application migration, workload rebalancing and business continuity across data centers and clouds. Large-scale movement of workloads across any VMware platform. vSphere 5.0+ to any current vSphere version on cloud or modern data center. KVM and Hyper-V conversion to any current vSphere version. Support for VMware Cloud Foundation, VMware Cloud on AWS, Azure VMware Services and more. Choice of migration methodologies to meet your workload needs. Live large-scale HCX vMotion migration of 1000’s of VMs. Zero downtime migration to limit business disruption. Secure proxy for vMotion and replication traffic. Migration planning and visibility dashboard. Automated migration-aware routing with NSX for network connectivity. WAN optimized links for migration across Internet or WAN. High-throughput L2 extension. Advanced traffic engineering to optimize the application migration times. -
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ByteNite
ByteNite
A SaaS platform for high-throughput computing, supporting fast and cost-effective video encoding. ByteNite implements a distributed computing system based on mobile and desktop devices as worker nodes, keeping the parallelization of video computing workflows and realizing a high-throughput computing environment. ByteNite's philosophy is captured in availability, agility, speed, security, and sustainability values. -
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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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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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Karpenter
Amazon
Karpenter simplifies Kubernetes infrastructure with the right nodes at the right time. Karpenter is an open source, high-performance Kubernetes cluster autoscaler that simplifies infrastructure management by automatically launching the appropriate compute resources to handle your cluster's applications. Designed to leverage the full potential of the cloud, Karpenter enables fast and straightforward compute provisioning for Kubernetes clusters. It enhances application availability by swiftly responding to changes in application load, scheduling, and resource requirements, efficiently placing new workloads onto a variety of available computing resources. By identifying opportunities to remove under-utilized nodes, replace costly nodes with more economical alternatives, and consolidate workloads onto more efficient compute resources, Karpenter effectively reduces cluster compute costs.Starting Price: Free -
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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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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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PipelineDB
PipelineDB
PipelineDB is a PostgreSQL extension for high-performance time-series aggregation, designed to power realtime reporting and analytics applications. PipelineDB allows you to define continuous SQL queries that perpetually aggregate time-series data and store only the aggregate output in regular, queryable tables. You can think of this concept as extremely high-throughput, incrementally updated materialized views that never need to be manually refreshed. Raw time-series data is never written to disk, making PipelineDB extremely efficient for aggregation workloads. Continuous queries produce their own output streams, and thus can be chained together into arbitrary networks of continuous SQL. -
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Azure Disk Storage
Microsoft
Designed to be used with Azure Virtual Machines and Azure VMware Solution (in preview), Azure Disk Storage offers high-performance, durable block storage for your mission- and business-critical applications. Confidently migrate to Azure infrastructure with four disk storage options for the cloud—–Ultra Disk Storage, Premium SSD, Standard SSD, and Standard HDD—to optimize costs and performance for your workload. Get high performance with sub-millisecond latency for throughput and transaction-intensive workloads such as SAP HANA, SQL Server, and Oracle. Run clustered or high-availability applications cost effectively in the cloud using shared disks. Get consistent enterprise-grade durability with a 0% annual failure rate. Meet demand without performance disruption by using Ultra Disk Storage. Secure your data with automatic encryption using Microsoft-managed keys or your own. -
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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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Substrate
Substrate
Substrate is the platform for agentic AI. Elegant abstractions and high-performance components, optimized models, vector database, code interpreter, and model router. Substrate is the only compute engine designed to run multi-step AI workloads. Describe your task by connecting components and let Substrate run it as fast as possible. We analyze your workload as a directed acyclic graph and optimize the graph, for example, merging nodes that can be run in a batch. The Substrate inference engine automatically schedules your workflow graph with optimized parallelism, reducing the complexity of chaining multiple inference APIs. No more async programming, just connect nodes and let Substrate parallelize your workload. Our infrastructure guarantees your entire workload runs in the same cluster, often on the same machine. You won’t spend fractions of a second per task on unnecessary data roundtrips and cross-region HTTP transport.Starting Price: $30 per month -
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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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Apache Doris
The Apache Software Foundation
Apache Doris is a modern data warehouse for real-time analytics. It delivers lightning-fast analytics on real-time data at scale. Push-based micro-batch and pull-based streaming data ingestion within a second. Storage engine with real-time upsert, append and pre-aggregation. Optimize for high-concurrency and high-throughput queries with columnar storage engine, MPP architecture, cost based query optimizer, vectorized execution engine. Federated querying of data lakes such as Hive, Iceberg and Hudi, and databases such as MySQL and PostgreSQL. Compound data types such as Array, Map and JSON. Variant data type to support auto data type inference of JSON data. NGram bloomfilter and inverted index for text searches. Distributed design for linear scalability. Workload isolation and tiered storage for efficient resource management. Supports shared-nothing clusters as well as separation of storage and compute.Starting Price: Free -
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NVIDIA GPU-Optimized AMI
Amazon
The NVIDIA GPU-Optimized AMI is a virtual machine image for accelerating your GPU accelerated Machine Learning, Deep Learning, Data Science and HPC workloads. Using this AMI, you can spin up a GPU-accelerated EC2 VM instance in minutes with a pre-installed Ubuntu OS, GPU driver, Docker and NVIDIA container toolkit. This AMI provides easy access to NVIDIA's NGC Catalog, a hub for GPU-optimized software, for pulling & running performance-tuned, tested, and NVIDIA certified docker containers. The NGC catalog provides free access to containerized AI, Data Science, and HPC applications, pre-trained models, AI SDKs and other resources to enable data scientists, developers, and researchers to focus on building and deploying solutions. This GPU-optimized AMI is free with an option to purchase enterprise support offered through NVIDIA AI Enterprise. For how to get support for this AMI, scroll down to 'Support Information'Starting Price: $3.06 per hour -
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Crusoe
Crusoe
Crusoe provides a cloud infrastructure specifically designed for AI workloads, featuring state-of-the-art GPU technology and enterprise-grade data centers. The platform offers AI-optimized computing, featuring high-density racks and direct liquid-to-chip cooling for superior performance. Crusoe’s system ensures reliable and scalable AI solutions with automated node swapping, advanced monitoring, and a customer success team that supports businesses in deploying production AI workloads. Additionally, Crusoe prioritizes sustainability by sourcing clean, renewable energy, providing cost-effective services at competitive rates. -
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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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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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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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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.
