AI Accelerator IP
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57
IP
from 25 vendors
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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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Low power AI accelerator
- Complete speech processing at less than 100W
- Able to run time series nerworks for signal and speech
- 10X more efficient than traditional NNs
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AI Accelerator: Neural Network-specific Optimized 1 TOPS
- Performance efficient 18 TOPS/Watt
- Capable of processing real-time HD video and images on-chip
- Advanced activation memory management
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AI Accelerator (NPU) IP - 3.2 GOPS for Audio Applications
- 3.2 GOPS
- Ultra-low <300uW power consumption
- Low latency
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Edge AI Accelerator NNE 1.0
- Minimum efforts in system integration
- Speed up AI inference performance
- Super performance for power sensitive application
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AI accelerator (NPU) IP - 32 to 128 TOPS
- Performance efficient 18 TOPS/Watt
- 36K-56K MACS
- Multi-job support
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AI accelerator (NPU) IP - 1 to 20 TOPS
- Performance efficient 18 TOPS/Watt
- Scalable performance from 2-9K MACS
- Capable of processing HD images on chip
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AI Accelerator
- Independent of external controller
- Accelerates high dimensional tensors
- Highly parallel with multi-tasking or multiple data sources
- Optimized for performance / power / area
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NPU / AI accelerator with emphasis in LLM
- Programmable and Model-flexible
- Ecosystem Ready