A new press release reports, “IBM today announced that it plans to incorporate the new RAPIDS™ open source software into its enterprise-grade data science platform for on-premises, hybrid, and multicloud environments. With IBM’s vast portfolio of deep learning and machine learning solutions, it is best positioned to bring this open-source technology to data scientists regardless of their preferred deployment model. ‘IBM has a long collaboration with NVIDIA that has shown demonstrable performance increases leveraging IBM technology, like the IBM POWER9 processor, in combination with NVIDIA GPUs,’ said Bob Picciano, Senior Vice President of IBM Cognitive Systems. ‘We look to continue to aggressively push the performance boundaries of AI for our clients as we bring RAPIDS into the IBM portfolio’.”
The release goes on, “RAPIDS will help bring GPU acceleration capabilities to IBM offerings that take advantage of open source machine learning software including Apache Arrow, Pandas and scikit-learn. Immediate, wide ecosystem support for RAPIDS comes from key open-source contributors including Anaconda, BlazingDB, Graphistry, NERSC, PyData, INRIA, and Ursa Labs. IBM is planning to bring RAPIDS to key areas across on-premises, public, hybrid, and multicloud environments, including: (1) PowerAI on IBM POWER9, to leverage RAPIDS to expand the options available to data scientists with new open source machine learning and analytics libraries. Accelerated workloads have been proven to get a direct benefit from the special engineering that NVIDIA and IBM have done around POWER9, including integration of NVIDIA NVLink® and NVIDIA Tesla® Tensor Core GPUs. PowerAI is IBM’s software layer that optimizes how today’s data science and AI workloads run on heterogeneous computing systems, and our goal is for this improved performance trajectory for GPU accelerated workloads on POWER9 to continue with RAPIDS.”
Read more at PR Newswire.
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