Delivers Industry-Leading 35 TOPS Performance for Artificial Intelligence SoCs
The DesignWare EV7x Vision Processors’ heterogeneous architecture integrates vector DSP, vector FPU, and a neural network accelerator to provide a scalable solution for a wide range of current and emerging artificial intelligence applications. The ARC EV7x Vision Processors integrate up to four enhanced vector processing units (VPUs) and a DNN accelerator with up to 14,080 MACs to deliver up to 35 TOPS performance in 16-nanometer (nm) FinFET process technologies under worst case conditions, 4X the performance of the ARC EV6x processors. In addition, the new EV7x design combines clock and power gating technologies with architectural enhancements to reduce power consumption. To speed application software development for ARC EV7x Vision Processors, Synopsys’ MetaWare EV Development Toolkit provides a comprehensive software programming environment based on common embedded vision standards, including OpenVX™ and OpenCL™ C. The combination of high-performance vision engine and DNN accelerator with high productivity programming tools make the ARC EV7x Embedded Vision Processors ideal for a broad range of vision applications including advanced driver assist systems (ADAS), video surveillance, smart home, and augmented and virtual reality.
New High-Performance Multicore Architecture with Deep Neural Network Accelerator
The DesignWare ARC EV7x Vision Processors’ heterogeneous multicore architecture includes up to four high-performance VPUs. Each EV7x VPU includes a 32-bit scalar unit and a 512-bit wide vector DSP and can be configured for 8-, 16-, or 32-bit operations to perform simultaneous multiply-accumulates on different streams of data. The optional DNN accelerator scales from 880 to 14,080 MACs and employs a specialized architecture for faster memory access, higher performance, and better power efficiency than alternative neural network IP. In addition to supporting convolutional neural networks (CNNs), the DNN accelerator supports batched LSTMs (long short-term memories) for applications that require time-based results, such as predicting the location of a pedestrian based on their observed path and speed. The vision engine and the DNN accelerator work on tasks in parallel, making the EV7x particularly efficient for autonomous vehicles and ADAS applications where vision algorithms operate concurrently.
Latest Advancements for Safety
ASIL B or ASIL D Ready versions of the new processors, the ARC EV7xFS portfolio, accelerate ISO 26262 certification of automotive SoCs. The functional safety-enhanced processors offer hardware safety features, safety monitors, and lockstep capabilities that enable designers to achieve stringent levels of functional safety and fault coverage without significant impact on power or performance. In addition, a new Hybrid option enables system architects to select safety levels up to ASIL D in the software, post-silicon.
The ARC EV7x Vision Processor family is supported by MetaWare EV Development Toolkit, a comprehensive, high-productivity software development environment based on common embedded vision standards, including OpenVX™ and OpenCL™ C. The tool suite enables the development of efficient computer vision applications on the EV7x processor’s vision engine as well as automatic mapping and optimization of neural networks graphs on the dedicated DNN accelerator. The mapping tools support Caffe and Tensorflow frameworks, as well as the ONNX neural network interchange format.