AI Inference IP
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35
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AI inference engine for real-time edge intelligence
- Flexible Models: Bring your physical AI application, open-source, or commercial model
- Easy Adoption: Based on open-specification RISC-V ISA for driving innovation and leveraging the broad community of open-source and commercial tools
- Scalable Design: Turnkey enablement for AI inference compute from 10’s to 1000’s of TOPS
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AI inference processor IP
- High Performance, Low Power Consumption, Small Foot Print IP for Deep Learning inference processing.
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Highly scalable inference NPU IP for next-gen AI applications
- ENLIGHT Pro is meticulously engineered to deliver enhanced flexibility, scalability, and configurability, enhancing overall efficiency in a compact footprint.
- ENLIGHT Pro supports the transformer model, a key requirement in modern AI applications, particularly Large Language Models (LLMs). LLMs are instrumental in tasks such as text recognition and generation, trained using deep learning techniques on extensive datasets.
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AI SDK for Ceva-NeuPro NPUs
- Ceva-NeuPro Studio is a comprehensive software development environment designed to streamline the development and deployment of AI models on the Ceva-NeuPro NPUs.
- It offers a suite of tools optimized for the Ceva NPU architectures, providing network optimization, graph compilation, simulation, and emulation, ensuring that developers can train, import, optimize, and deploy AI models with highest efficiency and precision.
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High-Performance Memory Expansion IP for AI Accelerators
- Expand Effective HBM Capacity by up to 50%
- Enhance AI Accelerator Throughput
- Boost Effective HBM Bandwidth
- Integrated Address Translation and memory management:
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NPU / AI accelerator with emphasis in LLM
- Programmable and Model-flexible
- Ecosystem Ready
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AI accelerator
- Massive Floating Point (FP) Parallelism: To handle extensive computations simultaneously.
- Optimized Memory Bandwidth Utilization: Ensuring peak efficiency in data handling.
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AI Accelerator Specifically for CNN
- A specialized hardware with controlled throughput and hardware cost/resources, utilizing parameterizeable layers, configurable weights, and precision settings to support fixed-point operations.
- This hardware aim to accelerate inference operations, particulary for CNNs such as LeNet-5, VGG-16, VGG-19, AlexNet, ResNet-50, etc.
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Future-proof IP for training and inference with leading performance per watt and per dollar
- RISC-V-based AI IP development for enhanced training and inference.
- Silicon-proven solutions tailored for AI workload optimization.
- Energy-efficient performance with industry-leading Perf/W.
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Super low-power and high accuracy AI processing engine for Wake Word, Voice Commands, Acoustic Event Detection, Speaker ID and Sensors
- Voice control and Context detection
- High Accuracy in Noisy Conditions