Cloud native EDA tools & pre-optimized hardware platforms
Every electronic system with an on-and-off switch relies on memory. From IoT to automotive and AI, each of these applications thrives on high memory bandwidth, fast throughput, and low latency. In a landscape marked by hyper-convergence, hyper-customization, digitization, and stringent reliability requirements, developing these solutions is more challenging than ever. 草榴社区 is here to help you shift left for faster turnaround times with the industry’s most complete, end-to-end solutions for memory development.
Squeezed by power, performance, and area (PPA) demands, memory designs are moving into a hyper-convergent space, consisting of multiple technologies, protocols, and architectures in one highly complex, increasingly digitized design. To facilitate development of hyper-convergent memory, 草榴社区 provides fast technology pathfinding, design-technology co-optimization (DTCO), and early design PPA assessments using early process development kit generation flow and integration between TCAD and custom/digital design tools. This is augmented by ultra-fast conventional and machine learning-driven simulation, and “digitized” memory design implementation flows using digital tools spanning timing characterization, digital-on-top verification, and place and route, to enable fast and accurate PPA optimization.
Exploring new device structures, variants, and process flavors provides a path to better PPA. As technology gaps widen, however, modeling doesn’t capture all the effects on silicon, especially at advanced nodes. To address potential silicon reliability issues early on, 草榴社区 provides higher coverage with memory-specific electrical rule checking, fast chip-level electromagnetic/IR analysis with power delivery network, functional safety solutions with ISO 26262 compliance, and multi-die system design and silicon lifecycle management tools.?
With every new memory protocol comes a big step up in performance and runtime. At the same time, the unique needs of different applications are driving increased customization. To scale up swiftly and meet the requirements of new protocols and unique specifications, you need faster design-to-signoff turnaround time. 草榴社区 can help you shift memory design left by providing faster block or chip-level simulation turnaround times, a machine learning-driven design optimization flow, faster design closure with early parasitic analysis, higher design productivity with layout reuse, and “digitized” memory design implementation flows. You can also lower integration risks and speed time-to-market with our memory IP.?
The demand for highly customized high performance memory chips to cater to the needs of HPC, AI, and automotive applications is driving the need for new design paradigms such as DTCO, Design Shift Left, Digitization, and Design-for-Reliability.
SNUG-GET Customer Testimonial: Texas Instruments
David Francis, Embedded Product Engineer
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