Cadence: Tensilica Vision Q7 DSP IP doubles vision and AI performance for automotive, AR/VR mobile

Cadence Design Systems expanded the high end of its Tensilica Vision DSP product family with the introduction of the Cadence Tensilica Vision Q7 DSP delivering up to 1.82 tera operations per second. To address the increasing computational requirements for embedded vision and AI applications, the sixth-generation Vision Q7 DSP provides up to 2X greater AI and floating-point performance in the same area compared to its predecessor, the Vision Q6 DSP. The Vision Q7 DSP is specifically optimized for simultaneous localization and mapping (SLAM), a technique commonly used in the robotics, drone, mobile and automotive markets to automatically construct or update a map of an unknown environment, and in the AR/VR market for inside-out tracking.

While performing SLAM, edge SoCs also require a computational offload engine to increase performance, reduce latency and further lower power for battery-operated devices. Because SLAM utilizes fixed- and floating-point arithmetic to achieve the necessary accuracy, any vision DSP employed for SLAM must provide higher performance for both data types.

For AI applications, the Vision Q7 DSP provides a flexible solution delivering 512 8-bit MACs, compared to 256 MACs for the Vision Q6 DSP. For greater AI performance, the Vision Q7 DSP can be paired with the Tensilica DNA 100 processor. In addition to computational performance, the Vision Q7 DSP boasts a number of iDMA enhancements including 3D DMA, compression and a 256-bit AXI interface. The Vision Q7 DSP is a superset of the Vision Q6 DSP, which preserves customers’ existing software investment and enables an easy migration from the Vision Q6 or Vision P6 DSPs.

The Vision Q7 DSP supports AI applications developed in the Caffe, TensorFlow and TensorFlowLite frameworks through the Tensilica Xtensa Neural Network Compiler, which maps neural networks into executable and highly optimized high-performance code for the Vision Q7 DSP. The Vision Q7 DSP also supports the Android Neural Network API for on-device AI acceleration in Android-powered devices, and the software environment also features complete and optimized support for more than 1,700 OpenCV-based vision library functions, enabling fast, high-level migration of existing vision applications. In addition, development tools and libraries are all designed to enable SoC vendors to achieve ISO 26262 ASIL D certification.

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