ANSYS Introduces RedHawk-3DX 20nm Power Sign-off Solution
ANSYS launched RedHawk-3DX, which is a fourth-generation power sign-off solution. RedHawk-3DX is designed to meet the power, performance and price demands of low-power mobile, high-performance computing, consumer and automotive electronics. RedHawk-3DX extends previous generations’ capabilities to address sub-20 nanometer (nm) designs with 3+ gigahertz performance and billions of gates. It is also architected to support the simulation of emerging chip and packaging technologies using multi-die three-dimensional ICs (3D-ICs) for smart electronic products.
RedHawk-3DX power sign-off solution improves the accuracy and coverage of dynamic power analysis. It does this by providing enhanced logic-handling capabilities. Its new event- and state-propagation technologies with vector-based and VectorLess modes utilize both the functional stimulus and statistical probability to determine the switching scenario of the design. The fast event-propagation engine uses register transfer language (RTL)-level functional stimulus to perform cycle-accurate voltage drop simulation. The robust state-propagation engine for the VectorLess mode enables time-domain transient analysis without actual input stimulus and includes proprietary techniques to eliminate underestimation of toggle rates associated with traditional activity-based propagation approaches. RedHawk-3DX also supports flexible mixed-excitation mode, in which some blocks use RTL or gate-level vectors while the rest of the design uses the VectorLess methodology.
- Highest capacity and performance with ERV and MPR technologies
- Accurate extraction engine for the latest technology nodes
- Advanced Vectorless and VCD analysis with enhanced logic handling for RTL to Gates methodology
- Spice characterization of standard cells
- Memory and macro modeling
- Design optimization with what-if and FAO
- Early design prototyping and analysis
- Multi-pane GUI for multi-die/3D-IC design analysis and debug
- RedHawk Explorer (RHE) for root cause identification
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