Multi-Layer Deep Data Performance Monitoring and Optimization
By proteanTecs, Siemens Digital Industries Software
Combining functional and parametric monitoring of the real-world behavior of complex SoCs provides a powerful new approach that facilitates performance optimization during development and in the field, improves security and safety, and enables predictive maintenance to prevent field failures. proteanTecs’ Universal Chip Telemetry (UCT) and Siemens’ Tessent Embedded Analytics are complementary technologies that enable just such an approach, informed by Deep Data.
Examples based on ADAS and autonomous driving systems demonstrate how the two systems interact to shine a light on even the most complex problems in electronics design, production and deployment.
To read the full article, click here
Related Semiconductor IP
- Post-Quantum Digital Signature IP Core
- Compact Embedded RISC-V Processor
- Power-OK Monitor
- RISC-V-Based, Open Source AI Accelerator for the Edge
- Securyzr™ neo Core Platform
Related White Papers
- Processor Architecture for High Performance Video Decode
- Performance Optimization of Embedded Software for ARM Processors and AMBA Methodology-based Systems
- A Multi-Objective Optimization Model for Energy and Performance Aware Synthesis of NoC Architecture
- Performance Measurements of Synchronization Mechanisms on 16PE NOC Based Multi-Core with Dedicated Synchronization and Data NOC
Latest White Papers
- DRsam: Detection of Fault-Based Microarchitectural Side-Channel Attacks in RISC-V Using Statistical Preprocessing and Association Rule Mining
- ShuffleV: A Microarchitectural Defense Strategy against Electromagnetic Side-Channel Attacks in Microprocessors
- Practical Considerations of LDPC Decoder Design in Communications Systems
- A Direct Memory Access Controller (DMAC) for Irregular Data Transfers on RISC-V Linux Systems
- A logically correct SoC design isn’t an optimized design