AI Applications

Artificial Intelligence Applications for HPC

Resources for Data Scientists and Machine Learning Engineers

Many applications used by the High Performance Computing community are optimized for artificial intelligence. Neural Networks built for Machine Learning and Deep Learning require intense computation resources, and can be dramatically accelerated by parallel and distributed programming — utilizing multiple cores of both CPUs and GPUs, multiple processors, and multiple compute nodes by distributing computational tasks. This is done using libraries, frameworks and large scale applications such as OpenACC, Hadoop, and NVIDIA RAPIDS libraries, among others. Below is a collection of resources curated by Aspen Systems designed to help Data Scientists and Machine Learning Engineers find the right solution. Please call 1-800-992-9242 to speak with a sales engineer in order to assist you with finding the best solution stack, both hardware and software, for your specific needs. If there is an application, library or framework that you feel should be included here but isn’t, please send us some feedback.


Hadoop Applications - DataRobot Logo DataRobot offers a machine learning platform for data scientists of all skill levels to build and deploy accurate predictive models in a fraction of the time it used to take. The technology addresses the critical shortage of data scientists by changing the speed and economics of predictive analytics.

Industries: Finance Machine Learning Other Go to the DataRobot website for more information.
Hadoop Applications - DataRPM Logo DataRPM delivers the only cognitive data science platform that automates and operationalizes machine learning to rapidly solve critical business problems. From continuous inline data ingestion to actionable insights, you can realize immediate benefits, significant cost reductions and amplified predictive power.

Industries: Automotive Machine Learning Manufacturing Other Go to the DataRPM website for more information.
Hadoop Applications - Logo creates deep learning solutions for enterprises. analyzes images, videos, text, time series, audio, logs and binaries and provides custom software solutions using Hadoop and Apache Spark.

Industries: Machine Learning Other Go to the website for more information.
Hadoop Applications - H2O Logo H2O is an open source machine learning platform for smarter applications. Leading insurance, healthcare and financial services companies are using H2O to make smarter predictions about churn, pricing, fraud and more.

Industries: Finance Machine Learning Other Go to the H2O website for more information.


Caffe Logo Caffe is a deep learning framework made with expression, speed, and modularity in mind. Expressive architecture encourages application and innovation. Models and optimization are defined by configuration without hard-coding. Switch between CPU and GPU by setting a single flag to train on a GPU machine then deploy to commodity clusters or mobile devices.
Industries: Machine Learning Go to the Berkley Vision website for more information.
Chainer Logo Chainer is a Python based, standalone open source framework for deep learning models. Chainer provides a flexible, intuitive, and high performance means of implementing a full range of deep learning models, including state-of-the-art models such as recurrent neural networks and variational autoencoders.
Industries: Machine Learning Go to the Chainer website for more information.
CNTKLogo CNTK, or Microsoft Cognitive Toolkit, is an open source deep-learning toolkit. It can be inlcuded as a library in Python, C#, or C++, or via it’s own model description language called “BrainScript”.
Industries: Machine Learning Go to the CNTK website for more information.
Keras Logo Keras is a high-level neural networks library, written in Python and capable of running on top of either TensorFlow, CNTK or Theano. It was developed with a focus on enabling fast experimentation. It’s simplicity makes it a popular choice for educational institutions and beginners. If you are new to Deep Learning, this is a good place to start.
Industries: Machine Learning Go to the Keras website for more information.
Trakomatic Logo oSense is a facial-based system for people counting and classifies them by age group and gender. It also monitors the time they spend in a particular spot and is able to detect new and repeat visitors.
Industries: Machine Learning Go to the Trakomatic website for more information.
Pylean Logo Pylearn2 is a machine learning library. Most of its functionality is built on top of Theano. This means you can write Pylearn2 plugins (new models, algorithms, etc.) using mathematical expressions, and Theano will optimize and stabilize those expressions for you, and compile them to a backend of your choice (CPU or GPU).
Industries: Machine Learning Go to the Deep Learning website for more information.
PyTorch Logo PyTorch is an open source python implementation of the Torch machine learning library. It is quickly becoming one of the most popular libraries for Machine learning, alongside Tensorflow.
Industries: Machine Learning Go to the PyTorch website for more information.
RAPIDS Logo NVIDIA’s RAPIDS is a suite of open source libraries and APIs focusing on end-to-end processing on GPUs. It includes several implementations of common libraries used in Deep Learning, such as data frames, linear algebra, sparse matrices, linear optimization, and parallel processing that are specifically designed for NVIDIA’s GPUs, especially the latest generation of Tesla GPUs, such as the V100.
Industries: Machine Learning Go to the RAPIDS website for more information.
Tensorflow Logo TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API. TensorFlow was originally developed by researchers and engineers working on the Google Brain Team within Google’s Machine Intelligence research organization to conduct machine learning and deep neural networks research, but the system is general enough to be applicable in a wide variety of other domains as well.
Industries: Machine Learning Go to the TensorFlow website for more information.
Torch Logo Torch is a scientific computing framework with wide support for machine learning algorithms. It is easy to use and efficient, thanks to an easy and fast scripting language, LuaJIT, and an underlying C/CUDA implementation.
Industries: Machine Learning Go to the Torch website for more information.


ML Flow MLFlow is an open source platform for the machine learning life-cycle. It allows you to track and organize projects, record the metadata and results of experiments, send models to a diverse set of deployment tools, and more.

Industries: Machine Learning Other Go to the MLFlow website for more information.