Best HPC Software for Cloud
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Compare the Top HPC Software for Cloud as of October 2025
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What is HPC Software for Cloud?
High-Performance Computing (HPC) software are applications designed to maximize computational power, enabling complex and resource-intensive tasks to be executed efficiently. These programs optimize parallel processing, often leveraging supercomputers or distributed computing clusters to solve problems in fields like scientific research, engineering, and data analytics. HPC software includes components for workload management, data communication, and performance tuning, ensuring scalability and efficient resource utilization. Examples include simulation software, machine learning frameworks, and tools for weather modeling or molecular dynamics. By harnessing advanced algorithms and hardware, HPC software accelerates computation, reducing the time required for tasks that would otherwise take weeks or months on conventional systems. Compare and read user reviews of the best HPC software for Cloud currently available using the table below. This list is updated regularly.
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UberCloud
Simr (formerly UberCloud)
Simr (formerly UberCloud) is a cutting-edge platform for Simulation Operations Automation (SimOps). It streamlines and automates complex simulation workflows, enhancing productivity and collaboration. Leveraging cloud-based infrastructure, Simr offers scalable, cost-effective solutions for industries like automotive, aerospace, and electronics. Trusted by leading global companies, Simr empowers engineers to innovate efficiently and effectively. Simr supports a variety of CFD, FEA and other CAE software including Ansys, COMSOL, Abaqus, CST, STAR-CCM+, MATLAB, Lumerical and more. Simr automates every major cloud including Microsoft Azure, Amazon AWS, and Google GCP. -
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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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