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Optimium
by ENERZAi Inc.
Key Facts
- Optimium has been developed based on our proprietary programming language, Nadya. Through metaprogramming, Nadya generates optimized code for target hardware based on countless combinations of layer-specific optimization parameters. Additionally, it utilizes tens of unique optimization passes to compile the generated code into executable forms, maximizing inference speed on the target hardware.
- Optimium can maximize AI model inference on target hardware while maintaining accuracy. Based on our proprietary optimization techniques such as model tuning, layer fusion, and memory planning, it has demonstrated superior performance over existing engines.
- Optimium enables convenient deployment across various hardware platforms with a single tool. In the case of existing engines, different engines should be used for each target hardware, which hinders swift AI model deployment. With Optimium, substantial time and costs associated with AI model deployment can be effectively reduced.
Categories
- Embedded Vision
- Artificial Intelligence
- Other Tools and Software
New
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Key Facts
- Optimium has been developed based on our proprietary programming language, Nadya. Through metaprogramming, Nadya generates optimized code for target hardware based on countless combinations of layer-specific optimization parameters. Additionally, it utilizes tens of unique optimization passes to compile the generated code into executable forms, maximizing inference speed on the target hardware.
- Optimium can maximize AI model inference on target hardware while maintaining accuracy. Based on our proprietary optimization techniques such as model tuning, layer fusion, and memory planning, it has demonstrated superior performance over existing engines.
- Optimium enables convenient deployment across various hardware platforms with a single tool. In the case of existing engines, different engines should be used for each target hardware, which hinders swift AI model deployment. With Optimium, substantial time and costs associated with AI model deployment can be effectively reduced.
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