Improve your customers' search experience—easily add text plus pictures and objects to your neural search capabilities without sacrificing latency.
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GSI Technology's patented Gemini Associative Processing Unit (APU) changes the concept of computing from serial data processing—where data is moved back and forth between the processor and memory—to massive parallel data processing, compute, and search in-place directly in the memory array.
This in-memory associative computing technology provides a bit-level granular flexibility to create programming frameworks best suited for the application. Dynamic precision lets each instruction size to appropriate needs. Massive internal bus bandwidth and large L1 cache provide orders of magnitude performance-over-power ratio compared to conventional methods that use CPU and GPU, along with DRAM. |
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Processor Comparison
*Trillions of 8-bit ADD operations per second (TOPS)
This table was originally published in July 2020 by The Linley Group in their paper In-Memory Acceleration For Big Data. It has been updated here with Gemini-I production specifications.
Target Applications
GSI’s SAR solution improves dramatically the performance of the previous GSI SAR application by 10 times better, bringing Real Time (RT) and truly mobile promise to the field of SAR spotlight image construction.
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Integrated with the BIOVIA™ Pipeline Pilot scientific application, Gemini delivers exceptional performance for circular fingerprint similarity search, including threshold searches at under 0.8.
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Award-Winning Technology
(Available as hardware, turn-key servers, and IAAS.)
GSI Technology's submission to the Mobile Standoff Autonomous Indoor Capabilities (MoSAIC) Challenge won first place in the Human/Object Tagging category.
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GSI Technology was awarded the $25,000 Grand Prize after passing all the competition's formal and technical eligibility tests.
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In The World
Berlin Buzzwords is Germany's most exciting conference on storing, processing, streaming, and searching large amounts of digital data, with a focus on open source software projects.
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Bringing multimodal experience into search journey became of high interest lately: searching images with text, or looking inside an audio file, combining that with the rgb frames of a video stream.
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