EDALogic proudly introduces Atlas a comprehensive platform designed for early-stage and signoff-level thermal, power (IR), and electromigration (EM) analysis. Atlas facilitates full-spectrum, multi-physics analysis, covering electrical, thermal, signal, and power integrity. The platform consists of two distinct tools, Neo and Helius.
Neo: Chip-Level EM/IR Tool
Neo provides in-depth cross-die IR drop analysis, offering detailed insights into layout and signoff processes. It employs advanced physics-based models for electromigration (EM) and thermomigration in interposers and power grid structures. Notably, Neo mitigates pessimism inherent in heuristic-based approaches, introducing accuracy in analysis by integrating Joule heating-induced interactions.
Neo enables accurate analysis of the entire 3D package, encompassing Cu redistribution lines, micro solder bumps, through-Silicon vias, and Cu-to-Cu direct bonds.
Helius: ElectroThermal System Level Tool
In addressing widespread thermal challenges in modern 3D ICs, Helius provides a holistic approach, integrating models for both core and memory. Accurate power and current profiles of each subsystem in the entire 3D stack are incorporated.
The tool employs fine-grain and adaptive Finite Element Method (FEM) meshing strategies for detailed thermal model extraction based on local hotspot gradients. Additionally, Helius introduces a Boundary Condition independent reduced-order model extraction for core and memory modules on the chiplet, enabling fast Computational Fluid Dynamics (CFD) simulations of the entire system.
Powered by dedicated solvers and preconditioners with multi-threading and distributed processing capabilities, Helius enhances thermal simulations. The tool also offers a rapid what-if deep learning-based 3D IC thermal simulator, solving heat equations under various Partial Differential Equations (PDE) configurations.
EDALogic's Atlas platform, featuring Neo and Helius, represents a
groundbreaking advancement in 3D-IC reliability analysis, offering precise,
comprehensive, and efficient solutions for the challenges posed by
electromigration and thermal management in modern semiconductor design.
Comprehensive Reliability Platform: Atlas offers an all-in-one solution for 3D chiplet architectures, integrating advanced machine learning and simulation methodologies to perform thorough reliability analysis.
Early Detection of Hot Spots: Leveraging deep learning techniques, our platform identifies temperature hot spots that significantly impact reliability, enabling proactive measures for enhanced chiplet performance.
Accurate Simulation Engine: With precise physics models, our simulation engine evaluates reliability under varying conditions, providing valuable insights for early design optimizations and robust chiplet architectures.
Efficient Solution Methods: Equipped with innovative iterative methods, our numerical simulation modules accelerate analyses without compromising accuracy, streamlining the design process.
Industry-Driven Results: Designed to meet the demands of semiconductor companies, research institutions, and diverse industries, our solution ensures optimal 3D IC reliability, empowering clients to stay ahead in a competitive market.
Our platform combines the power of machine learning and simulation methodologies to deliver advanced reliability analysis of 3D chiplet architectures. Our deep learning approach is assessing the feasibility of a floorplan by computing the temperature distribution across the chiplet and the interposer. This enables the detection of temperature hotspots that may significantly impact signal and power integrity. By identifying these areas, we facilitate proactive measures to enhance reliability. Additionally, our simulation engine incorporates precise physics models, enabling efficient reliability evaluation under varying environmental conditions and operational scenarios. To accelerate simulations without compromising accuracy, our numerical simulation modules are equipped with innovative iterative methods and parametric model order reduction techniques. With our platform's blend of machine learning and simulation capabilities, we provide a powerful solution to optimize 3D IC reliability.