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W3078E PathWave Advanced DDR AMI Modeler
Generate single-ended PAM4 AMI models quickly, easily, and accurately for GDDR6X with wizard driven AMI model generation workflow for memory interfaces
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The W3078E PathWave Advanced DDR AMI Modeler enables designers to build single ended PAM4 AMI models for memory interfaces, especially targeted for next generation memory systems including GDDR6X, GDDR7, and potentially DDR6.
Highlights
The W3078E PathWave Advanced DDR AMI Modeler includes:
- Accurate single ended PAM4 AMI model generation for next generation memory interfaces
- Advanced single ended PAM4 model features include:
- Preshoot and de-emphasis equalizations
- RLM (Level Mismatch Ratio)
- SNDR (Signal to Noise Distortion Ratio)
- PAM4 signal mapping
- Delay
- Vref calibration
- Custom CTLE
- AGC
- Compression
- DFE
- Forwarded Clocking - Streamline your AMI modeling workflow
- Full range of solutions for AMI Modeling (custom and built-in solutions)
- Packs up files to be sent off: .ami, .dll or .so, .ibs, .conf
Traditionally, PAM4 modulation has been extensively used in SerDes applications. To support higher data throughput, multi-level modulation has been adopted for memory interfaces, starting with GDDR6X applications. PathWave Advanced DDR AMI Modeler helps designers to build single ended PAM4 AMI Models for memory interfaces, allowing you to accelerate your time to market in an accurate manner. The AMI Model for transmitters include model parameters including: RLM (Level Mismatch Ratio) and SNDR (Signal to Noise Distortion Ratio). The AMI models for receivers include: Vref calibration, CTLE (standard and custom), DFE, gain compression, and forwarded clocking. Predict eye closure with confidence using jitter tracking and unmatched IO capabilities. Streamline your workflow with the wizard driven workflow. PathWave Advanced DDR AMI Modeler is the industry-first solution that provides a full range of solutions, providing custom and built-in presets for modeling options for single ended PAM4.
Note: This element license requires a host bundle to work. For recommended bundle configurations, click here.
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