Best HPC Software for Python

Compare the Top HPC Software that integrates with Python as of September 2025

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This a list of HPC software that integrates with Python. Use the filters on the left to add additional filters for products that have integrations with Python. View the products that work with Python in the table below.

What is HPC Software for Python?

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 Python currently available using the table below. This list is updated regularly.

1

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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2

Arm MAP

Arm

No need to change your code or the way you build it. Profiling for applications running on more than one server and multiple processes. Clear views of bottlenecks in I/O, in computing, in a thread, or in multi-process activity. Deep insight into actual processor instruction types that affect your performance. View memory usage over time to discover high watermarks and changes across the complete memory footprint. Arm MAP is a unique scalable low-overhead profiler, available standalone or as part of the Arm Forge debug and profile suite. It helps server and HPC code developers to accelerate their software by revealing the causes of slow performance. It is used from multicore Linux workstations through to supercomputers. You can profile realistic test cases that you care most about with typically under 5% runtime overhead. The interactive user interface is clear and intuitive, designed for developers and computational scientists.

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3

Arm Forge

Arm

Build reliable and optimized code for the right results on multiple Server and HPC architectures, from the latest compilers and C++ standards to Intel, 64-bit Arm, AMD, OpenPOWER, and Nvidia GPU hardware. Arm Forge combines Arm DDT, the leading debugger for time-saving high-performance application debugging, Arm MAP, the trusted performance profiler for invaluable optimization advice across native and Python HPC codes, and Arm Performance Reports for advanced reporting capabilities. Arm DDT and Arm MAP are also available as standalone products. Efficient application development for Linux Server and HPC with Full technical support from Arm experts. Arm DDT is the debugger of choice for developing of C++, C, or Fortran parallel, and threaded applications on CPUs, and GPUs. Its powerful intuitive graphical interface helps you easily detect memory bugs and divergent behavior at all scales, making Arm DDT the number one debugger in research, industry, and academia.

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4

Intel oneAPI HPC Toolkit

Intel

High-performance computing (HPC) is at the core of AI, machine learning, and deep learning applications. The Intel® oneAPI HPC Toolkit (HPC Kit) delivers what developers need to build, analyze, optimize, and scale HPC applications with the latest techniques in vectorization, multithreading, multi-node parallelization, and memory optimization. This toolkit is an add-on to the Intel® oneAPI Base Toolkit, which is required for full functionality. It also includes access to the Intel® Distribution for Python*, the Intel® oneAPI DPC++/C++ C¿compiler, powerful data-centric libraries, and advanced analysis tools. Get what you need to build, test, and optimize your oneAPI projects for free. With an Intel® Developer Cloud account, you get 120 days of access to the latest Intel® hardware, CPUs, GPUs, FPGAs, and Intel oneAPI tools and frameworks. No software downloads. No configuration steps, and no installations.

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5

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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