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⇱ ROCm-DS: The AMD ROCm Data Science Toolkit


ROCm-DS: The AMD ROCm Data Science Toolkit

ROCm-DS: The AMD ROCm Data Science Toolkit#

Unlock the future of data science with the AMD ROCmβ„’ Data Science Toolkit (ROCm-DS), an innovative open-source toolkit built on the powerful ROCm platform. Tap into the unparalleled speed and efficiency of AMD Instinctβ„’ GPUs, as ROCm-DS provides you with all of the necessary tools to tackle larger datasets and execute complex data science workloads with lightning speed. Transform your data science capabilities to accelerate both new and existing projects, and boost performance and productivity across your business.

With ROCm-DS you have access to a rapidly expanding set of tools, empowering you to build, manage, and run entire data science workflows directly on AMD Instinct GPUs. Say goodbye to data-loading bottlenecks in AI workloads, accelerate your traditional data processing and analysis tasks, and manipulate immense datasets quickly and efficiently in GPU memory. Experience the exhilaration of streamlined AI and data science workloads powered by cutting-edge GPU technology.

Behind ROCm-DS lies a passionate, driven team dedicated to continuously expanding and improving this toolkit, ensuring you have everything you need to push the boundaries of data science. Get ready to revolutionize your data processing applications and unleash new possibilities with ROCm-DS.

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hipDF

GPU Accelerated DataFrames to enhance your data manipulation and analysis tasks with AMD Instinct GPUs. .

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hipGRAPH

Create, manipulate, and analyze complex networks and graphs on AMD Instinct GPUs.

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hipVS

Accelerate a variety of vector search operations on AMD Instinct GPUs.

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hipMM

Advanced memory management utilities for the various ROCm-DS libraries.

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hipRAFT

Fundamental algorithms and primitives used by the various ROCm-DS libraries.

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Github

View the source code for all ROCm-DS components on Github.

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ROCm-DS Blogs

Browse blogs detailing how to accelerate your data science workloads on AMD Instinct GPUs.