AI accelerator IP
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RISC-V-Based, Open Source AI Accelerator for the Edge
- Coral NPU is a machine learning (ML) accelerator core designed for energy-efficient AI at the edge.
- Based on the open hardware RISC-V ISA, it is available as validated open source IP, for commercial silicon integration.
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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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Performance AI Accelerator for Edge Computing
- Up to 16 TOPS
- Up to 16 MB Local Memory
- RISC-V/Arm Cortex-R or A 32-bit CPU
- 3 x AXI4, 128b (Host, CPU & Data)
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Performance Efficiency AI Accelerator
- Up to 6 TOPS
- Up to 6 MB Local Memory
- RISC-V/Arm Cortex-M or A 32-bit CPU
- 3 x AXI4, 128b (Host, CPU & Data)
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Lowest Power and Cost End Point AI Accelerator
- Up to 1 TOPS
- Up to 1 MB Local Memory
- RISC-V/Arm Cortex-M 32-bit CPU
- 3 x AXI4, 128b (Host, CPU & Data)
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AI Processor Accelerator
- Universal Compatibility: Supports any framework, neural network, and backbone.
- Large Input Frame Handling: Accommodates large input frames without downsizing.
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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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AI DSA Processor - 9-Stage Pipeline, Dual-issue
- NI900 is a DSA processor based on 900 Series.
- NI900 is optimized with features specifically targeting AI applications.
