Debugging hard faults in ARM Cortex-M0 based SoCs
Shashikant Joshi & Hanumanthaiah Shruti (Cypress Semiconductors)
embedded.com (February 08, 2017)
Programmable system-on-chip (PSoC) architectures integrate a wide range of capabilities, including MCU cores like the Cortex-M0, programmable analog blocks (PAB), programmable digital blocks (PDB), programmable interconnect and routing, a wide range of interfaces and peripherals, and advanced capabilities such as capacitive touch sensing. These architectures over many advantages over traditional microcontrollers and can substantially reduce design time and system bill of materials (BOM) cost.
As the complexity of programmable system-on-chip architectures and their MCU increases, so do the issues that can occur at each stage of design. One common issue developers face in Cortex-M0-based embedded systems is the hard fault. In some cases, we might get lucky and be able to quickly locate the source of the hard fault. However, most of the time chasing down a hard fault can be very time consuming. In this article, we will discuss some common errors programmers make and how to debug the hard fault caused by these errors.
To read the full article, click here
Related Semiconductor IP
- JESD204E Controller IP
- eUSB2V2.0 Controller + PHY IP
- I/O Library with LVDS in SkyWater 90nm
- 50G PON LDPC Encoder/Decoder
- UALink Controller
Related Articles
- Method for Booting ARM Based Multi-Core SoCs
- Automating Hardware-Software Consistency in Complex SoCs
- Verification of IP Core Based SoC's
- Adapter Based Distributed Simulation of Multiprocessor SoCs Using SystemC
Latest Articles
- Crypto-RV: High-Efficiency FPGA-Based RISC-V Cryptographic Co-Processor for IoT Security
- In-Pipeline Integration of Digital In-Memory-Computing into RISC-V Vector Architecture to Accelerate Deep Learning
- QMC: Efficient SLM Edge Inference via Outlier-Aware Quantization and Emergent Memories Co-Design
- ChipBench: A Next-Step Benchmark for Evaluating LLM Performance in AI-Aided Chip Design
- COVERT: Trojan Detection in COTS Hardware via Statistical Activation of Microarchitectural Events