- It has been built on top of Ray on IBM Cloud Code Engine, which is an open-source distributed computing framework for machine learning applications
- IBM said that CodeFlare pipelines run with ease on IBM Cloud Code Engine, which is the company’s new serverless platform, and on Red Hat OpenShift too
IBM has launched an open-source framework called CodeFlare for simplifying the integration, scaling, and speeding up of complex multi-step analytics and machine learning pipelines on the hybrid multi-cloud. It has been built on top of Ray on IBM Cloud Code Engine, which is an open-source distributed computing framework for machine learning applications. The new open-source framework is said to extend Ray’s capabilities through the addition of specific elements for making scaling workflows easier.
Python-based interface
IBM said that for creating a machine learning model, researchers and developers are currently required to first train and optimise the model. The process is said to be simplified by CodeFlare by using a Python-based interface. The new framework’s objective is for unifying pipeline workflows across various platforms without the need for data scientists learning a new workflow language.
IBM said Data and machine-learning analytics are proliferating into just about every industry, with tasks becoming ever-more complex. Larger datasets and more systems designed for AI research are fantasti but as these workflows become more involved, researchers are spending more and more time configuring their setups than getting data science done.
IBM said that CodeFlare pipelines run with ease on IBM Cloud Code Engine, which is the company’s new serverless platform, and on Red Hat OpenShift too.
