Deploying SIE on GPU: Embeddings, and Zero-Shot Extraction
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Title: Deploying SIE on GPU: Embeddings, and Zero-Shot Extraction
URL Source: https://medium.com/@shrinath.suresh/deploying-sie-on-gpu-embeddings-and-zero-shot-extraction-a20f525f0213?source=rss------machine_learning-5
Published Time: 2026-06-19T05:39:53Z
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# Deploying SIE on GPU: Embeddings, and Zero-Shot Extraction | by Shrinath Suresh | Jun, 2026 | Medium
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# Deploying SIE on GPU: Embeddings, and Zero-Shot Extraction
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[Shrinath Suresh](https://medium.com/@shrinath.suresh?source=post_page---byline--a20f525f0213---------------------------------------)
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In the previous article, we explored how to run the [Superlinked Inference Engine (SIE)](https://github.com/superlinked/sie) on CPU and benchmark its performance for embedding generation. While the CPU benchmark demonstrated the simplicity of the framework, many production workloads rely on GPUs for higher throughput and lower latency.
In t
URL Source: https://medium.com/@shrinath.suresh/deploying-sie-on-gpu-embeddings-and-zero-shot-extraction-a20f525f0213?source=rss------machine_learning-5
Published Time: 2026-06-19T05:39:53Z
Markdown Content:
# Deploying SIE on GPU: Embeddings, and Zero-Shot Extraction | by Shrinath Suresh | Jun, 2026 | Medium
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# Deploying SIE on GPU: Embeddings, and Zero-Shot Extraction
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In the previous article, we explored how to run the [Superlinked Inference Engine (SIE)](https://github.com/superlinked/sie) on CPU and benchmark its performance for embedding generation. While the CPU benchmark demonstrated the simplicity of the framework, many production workloads rely on GPUs for higher throughput and lower latency.
In t
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