High Performance Scalable Sensor Hub DSP Architecture
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 7 self-contained cores, addressing a wider range of sensor fusion and AI applications:
-The SP100 and SP50 DSPs, with 128 and 64 INT8 MACS, respectively. These DSPs offer the smallest die size and deliver a 10X performance improvement for DeepSpeech2 speech recognition neural network, compared to the Ceva-BX2 scalar DSP, and are ideal for audio AI workloads, such as conversational assistants, sound analytics, and natural language processing (NLP).
-The SP1000, SP500 and SP250 DSPs with 1024, 512, and 256 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 SPF4 and SPF2 floating point DSPs, with 64 and 32 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, Ceva-SLAM SDK, DSP functions, ClearVox noise reduction, WhisPro speech recognition, MotionEngine for Sensor Fusion, and the SenslinQ software framework.
These broad set of software and development tools help to minimize cost and improve time to market.
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Block Diagram of the High Performance Scalable Sensor Hub DSP Architecture
Sensor IP
- Secure-IC's Securyzr™ Digital Sensor: Universal and Digital Fault Injection Attack Detector can be used across all processes
- Very compact (500 LUTs) Camera Sensor Receiver Interface Converting from MIPI CSI-2 to AXI4-Stream Video Standard
- Ultra low power temperature sensor for X-FAB 350nm
- Temperature Sensor with Digital Output (High accuracy thermal sensing for reliability and optimisation), TSMC N7
- Sensor fusion solutions for augmented and virtual reality, robotics, motion controllers, and IoT
- PVT Sensor TSMC 40G