Memory fault models and testing
Abhilash Kaushal, Freescale
EDN (June 29, 2015)
A different set of fault models and testing techniques is required for memory blocks vs. logic. MBIST algorithms that are used to detect faults inside memory are based upon these fault models. This article discusses different types of memory fault models.
Memory fault models – Single cell faults
Stuck at (SAFs): Stuck at faults in memory is the one in which the logic value of a cell (or line in the sense amplifier or driver) is always 0 or 1.
Left: Write operation state diagram of a good memory cell; Right: State diagram for s-a-0 and s-a-1 memory cell
Transition Faults (TFs): In transition faults a cell fails to make a (0 to 1) transition or a (1 to 0) transition when it is written; up transition fault is denoted as <0w1/0/- > and a down transition fault is denoted as < 1w0/1/- >
State diagram for transition faults
Write destructive faults (WDFs): A non transition write operation in a memory cell causes the cell to flip. There are two types of Write destructive faults:
1) Memory cell in state 0, write 0 on it. Cell becomes 1. Denoted as <0w0/1/->
2) Memory cell in state 1, write 1 on it. Cell becomes 0.Denoted as <1w1/0/->
State diagram for write destructive faults
To read the full article, click here
Related Semiconductor IP
- Process/Voltage/Temperature Sensor with Self-calibration (Supply voltage 1.2V) - TSMC 3nm N3P
- USB 20Gbps Device Controller
- SM4 Cipher Engine
- Ultra-High-Speed Time-Interleaved 7-bit 64GSPS ADC on 3nm
- Fault Tolerant DDR2/DDR3/DDR4 Memory controller
Related White Papers
- Verifying embedded software functionality: fault localization, metrics and directed testing
- Accurate memory models for all
- Memory Testing - An Insight into Algorithms and Self Repair Mechanism
- QA Automation Testing with Container and Jenkins CICD
Latest White Papers
- Fault Injection in On-Chip Interconnects: A Comparative Study of Wishbone, AXI-Lite, and AXI
- eFPGA – Hidden Engine of Tomorrow’s High-Frequency Trading Systems
- aTENNuate: Optimized Real-time Speech Enhancement with Deep SSMs on RawAudio
- Combating the Memory Walls: Optimization Pathways for Long-Context Agentic LLM Inference
- Hardware Acceleration of Kolmogorov-Arnold Network (KAN) in Large-Scale Systems