GSI’s Gemini APU is an in-memory Associative Processing Unit that can eliminate von Neumann data transfer inefficiency and significantly improve large database similarity searches, high null-data database searches, and fast vector searches. The APU is used in applications such as e-commerce object recognition, bio and chem-informatics, cybersecurity, Natural Language Processing (NLP), and visual search just to name a few.
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GSI is proud to participate with OpenSearch as a partner with other leading community contributors. OpenSearch makes it easy to ingest, search, visualize, and analyze your data.
GSI Technology is the developer of the breakthrough Associative Processing Unit (APU) that allows high performance K and Approximate Nearest Neighbor (KNN and ANN) implementations and scaling similarity searches. Our contribution to the OpenSearch community is underlying APU hardware acceleration technology as a simple acceleration-as-a-service plug-in for search algorithms run in AWS.
Our service allows OpenSearch users to dramatically accelerate searches, add dense_vector support, and multimodal queries to large databases, including very large billion scale ones. This increases performance and drives down power consumption, providing lower cost per query to the OpenSearch community. The GSI APU can accelerate and provide additional capabilities to your OpenSearch workloads with a simple plug-in to your AWS workflow. Contact us to request a free trial.
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GSI Technology contributes to the OpenSearch community by providing the underlying APU hardware acceleration technology for search algorithms in AWS and on premises, allowing OpenSearch users to accelerate searches, add dense_vector support, and multimodal queries to large databases, including very large billion scale. This increases performance and drives down power consumption, providing lower cost per query to the OpenSearch community.
Additional APU Use Cases