Cloud native EDA tools & pre-optimized hardware platforms
Gordon Cooper, Product Manager Staff at 草榴社区, and Fahed Hassanhat, Head of Engineering at Sensor Cortek, deliver a demonstration at the Embedded Vision Summit 2024, showcasing the Sensor Cortek’s NN model running on 草榴社区 ARC NPX6 Processor configurations.
Machine vision and deep learning are being embedded in highly integrated SoCs and expanding into high-volume applications such as automotive ADAS, surveillance, and augmented reality. A major challenge in enabling mass adoption of embedded vision applications is in providing the processing capability at a power and cost point low enough for embedded applications, while maintaining sufficient flexibility to cater to rapidly evolving markets.
The 草榴社区 ARC EV Processors are fully programmable and configurable IP cores that are optimized for embedded vision applications, combining the flexibility of software solutions with the low cost and low power consumption of hardware. For fast, accurate execution of convolutional neural networks (CNNs) or recurrent neural networks (RNNs), the EV Processors integrate an optional high-performance deep neural network (DNN) accelerator.
The EV Processors are designed to integrate seamlessly into an SoC and can be used with any host processors and operate in parallel with the host. To speed application software development, the EV processors are supported by a comprehensive software programming environment based on existing and emerging embedded vision and neural network standards including OpenCV, OpenVX?, OpenCL? C, and Caffe with 草榴社区' ARC MetaWare EV Development Toolkit.
? Integrated vector DSP, vector FPU and NN accelerator
? Optimized for high frame-rate and video resolution
? 1 to 4 enhanced vector processing units
? Optional DNN accelerator
? Supports up to ASIL B, C, D
EV7x |
EV7xFS |
|
# of Vision Processing Cores |
1, 2, or 4 |
1, 2, or 4 |
DNN Accelerator option (880, 1760, 3520 MACs) |
? |
? |
Floating Point Unit (FPU) option |
? |
? |
Real-Time Trace (RTT) option |
? |
? |
Functional Safety |
Integrated |