Sensor Hub DSP

High Performance Scalable Sensor Hub DSP Architecture

SensPro2™ is the highly-scalable and enhanced 2nd generation high performance sensor hub DSP for multitasking sensing and AI of multiple sensors including camera, Radar, LiDar, Time-of-Flight, microphones and inertial measurement units.
SensPro2 family is designed to handle multiple sensor processing workload for contextually aware devices and can be utilized in modern intelligent systems in automotive, robotics, surveillance, AR/VR, voice assistants, wearables, mobile and smart home devices.

SensPro2 is a highly-configurable and self-contained architecture that brings together scalar and vector processing for floating point and integer data types, as well as deep learning inferencing.

The 2nd generation SensPro DSP family includes 6 self-contained cores, addressing a wider range of computer vision and Edge AI applications:

• The SP100 and SP250 DSPs, with 128 and 256 INT8 MACS, respectively. These DSPs offer the smallest die size and are ideal for a range of imaging and vision applications combined with AI workloads.
• The SP500 and SP1000 DSPs with 512 and 1024 INT8 MACs, respectively. These DSPs offer the highest performance and precision in the SensPro2 family, with optimal configurability for computer vision, SLAM, Radar, and AI workloads.
• The SPF2 and SPF4 floating point DSPs, with 32 and 64 single precision floating point MACs, respectively. These DSPs are optimized for electric vehicle powertrain control and battery management systems, complemented by a full suite of Eigen Linear Algebra, MATLAB vector libraries and support for the Glow graph compiler.

SensPro2 maximizes performance-per-watt for multi-sensor processing use cases by utilizing a combination of high performance single and half precision floating point math, point cloud creation and Deep Neural Network processing, along with parallel processing capacity for voice, imaging, and Simultaneous Localization and Mapping (SLAM).

SensPro2 platform approach is paired with advanced software and development tools that include LLVM C/C++ compiler, Eclipse based integrated development environment, CEVA Deep Neural Network (CDNN) graph compiler for neural networks including the CDNN-Invite API for inclusion of custom AI engines, TensorFlow Lite Micro support, OpenVX API, and a multitude of software libraries for OpenCL, CEVA-CV imaging functions and CEVA-SLAM SDK.
These broad set of software and development tools help to minimize cost and improve time to market.