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README.md
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<h2>Ampere Optimized AI Frameworks</h2>
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<p>Ampere helps users achieve superior performance for AI workloads by integrating optimized inference layers into common AI frameworks. Ampere Optimized AI Frameworks are designed to leverage the unique capabilities of Ampere Cloud Native Processors, unlocking a new level of AI inference capabilities. Ampere’s optimized AI frameworks stand as a testament to the synergy between hardware and software, offering many advantages that redefine the AI experience. Ampere’s software acceleration strategy goes beyond providing optimized frameworks, it offers an easy transition from AI model development to deployment. This approach streamlines the AI lifecycle, allowing businesses to swiftly operationalize their AI initiatives.</p>
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<p>Ampere focuses on delivering the most efficient solutions for AI inference, offering seamless integration with all AI applications via the support of all popular AI frameworks in the industry including PyTorch, TensorFlow, and ONNXRuntime. Ampere Optimized AI Frameworks work out of the box and do not require API changes or additional coding. This drop-in library supports all AI applications developed in the most popular frameworks and enables developers to seamlessly deploy their models across Ampere’s platforms.</p>
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<li>Conducting tests on AI architectures</li>
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<h3>AI Platform Alliance (AIPA)</h3>
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<p>
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Ampere Computing is one of the founders of the AI Platform Alliance. AIPA fosters open, efficient, and sustainable use of AI at scale working to validate joint AI solutions that provide a better alternative than the GPU-based status quo to accelerate the pace of AI innovation.
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<h2>Ampere Optimized AI Frameworks</h2>
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<p>Ampere helps users achieve superior performance for AI workloads by integrating optimized inference layers into common AI frameworks. Ampere Optimized AI Frameworks are designed to leverage the unique capabilities of Ampere Cloud Native Processors, unlocking a new level of AI inference capabilities. Ampere’s optimized AI frameworks stand as a testament to the synergy between hardware and software, offering many advantages that redefine the AI experience. Ampere’s software acceleration strategy goes beyond providing optimized frameworks, it offers an easy transition from AI model development to deployment. This approach streamlines the AI lifecycle, allowing businesses to swiftly operationalize their AI initiatives.</p>
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</P>
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<p>Ampere focuses on delivering the most efficient solutions for AI inference, offering seamless integration with all AI applications via the support of all popular AI frameworks in the industry including PyTorch, TensorFlow, and ONNXRuntime. Ampere Optimized AI Frameworks work out of the box and do not require API changes or additional coding. This drop-in library supports all AI applications developed in the most popular frameworks and enables developers to seamlessly deploy their models across Ampere’s platforms.</p>
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</P>
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<li>Conducting tests on AI architectures</li>
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</ul>
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</center>
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<h3>AI Platform Alliance (AIPA)</h3>
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<p>
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Ampere Computing is one of the founders of the AI Platform Alliance. AIPA fosters open, efficient, and sustainable use of AI at scale working to validate joint AI solutions that provide a better alternative than the GPU-based status quo to accelerate the pace of AI innovation.
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