15,762 technical terms and definitions
computational geometry, semiconductor geometry, polygon operations, level set, minkowski, opc geometry, design rule checking, drc, cmp modeling, resist modeling
Semiconductor Manufacturing Process Geometry and Computational Geometry Mathematical Modeling 1. The Fundamental Geometric Challenge Modern semiconductor manufacturing operates…
Geotechnical Engineering: Soil Mechanics, Foundation Design, and Slope Stability Geotechnical engineering applies soil and rock mechanics to design foundations, retaining…
geothermal energy extraction, geothermal energy, energy extraction
Geothermal Energy Extraction Introduction & Motivation Geothermal Energy Extraction addresses a central problem in energy-generation process control and heat-extraction-efficiency…
germanium incorporation in sige prediction, germanium incorporation sige, incorporation sige prediction, germanium incorporation, incorporation sige, sige prediction
Germanium Incorporation in SiGe Prediction with Machine Learning Introduction & Motivation Germanium Incorporation in SiGe Prediction with Machine Learning addresses a central…
germanium pmos channel strain relaxation prediction, germanium pmos channel, pmos channel strain, channel strain relaxation, strain relaxation prediction
Germanium PMOS Channel Strain Relaxation Prediction with Machine Learning Introduction & Motivation Germanium PMOS Channel Strain Relaxation Prediction with Machine Learning…
germanium pmos mobility prediction, germanium pmos mobility, pmos mobility prediction, germanium pmos, pmos mobility, mobility prediction
Germanium pMOS Mobility Prediction with Machine Learning Introduction & Motivation Germanium pMOS Mobility Prediction with Machine Learning addresses a central problem…
gesture recognition real-time, gesture recognition, recognition real-time
Gesture Recognition Real-Time Introduction & Motivation Gesture Recognition Real-Time addresses a central problem in gesture-recognition process control…
gesture recognition robot, gesture recognition, recognition robot
Gesture Recognition Robot Introduction & Motivation Gesture Recognition Robot addresses a central problem in robotics process control and gesture-interpretation-control-command…
Gesture and Pose Recognition Introduction & Motivation Gesture and Pose Recognition addresses a central problem in multimodal learning and gesture-accuracy-classification…
getter material activation efficiency prediction machine learning, getter material, activation efficiency prediction, getter material activation efficiency prediction
Getter Material Activation Efficiency Prediction with Machine Learning Introduction & Motivation Getter Material Activation Efficiency Prediction with Machine Learning addresses…
diffusion
Gettering is the process of trapping metallic impurities (Fe, Cu, Ni, Cr, Co) away from electrically active device regions on the wafer front side by creating preferential…
gettering process metal contamination reduction prediction, gettering process metal, process metal contamination, metal contamination reduction, gettering process
Gettering Process Metal Contamination Reduction Prediction with Machine Learning Introduction & Motivation Gettering Process Metal Contamination Reduction Prediction with Machine…
llama cpp, ggml, local llm inference, quantized llm, llama-server api, model quantization
GGUF (GPT-Generated Unified Format) is the modern model file format used by llama.cpp and related local inference stacks to package LLM weights, tokenizer assets, and runtime…
model optimization
Ghost Module is an efficient feature-generation block that creates additional channels using cheap linear operations - It approximates redundant feature maps at lower cost than…
gibbs sampling markov chain prediction, gibbs sampling markov, sampling markov chain, markov chain prediction, gibbs sampling, sampling markov, markov chain, chain prediction
Gibbs Sampling Markov Chain Prediction with Machine Learning Introduction & Motivation Gibbs Sampling Markov Chain Prediction with Machine Learning addresses a central problem…
band to band tunneling, off state leakage mechanism, GIDL current
Gate-Induced Drain Leakage (GIDL) is the off-state leakage mechanism where a strong electric field in the gate-to-drain overlap region causes band-to-band tunneling (BTBT)…
gin, graph neural networks
GIN is a graph-isomorphism network that uses injective neighborhood aggregation to strengthen graph discrimination - Summation-based aggregation with multilayer perceptrons…
code ai
GitHub Copilot is an AI pair programmer providing real-time code suggestions and completions in the IDE. How it works: Analyzes context (current file, open files, comments…
gitops declarative deployment, gitops declarative, declarative deployment
GitOps Declarative Deployment Introduction & Motivation GitOps Declarative Deployment addresses a central problem in cloud process control and deployment-from-git-repository…
glam, generalist language model, foundation model
GLaM (Generalist Language Model) is Google's sparse Mixture of Experts language model containing 1.2 trillion parameters that demonstrated how MoE architectures can achieve…
glass core substrate defect prediction machine learning, glass core, substrate defect prediction, glass core substrate defect prediction, glass core substrate, core substrate
Glass Core Substrate Defect Prediction with Machine Learning Introduction & Motivation Glass Core Substrate Defect Prediction with Machine Learning addresses a central problem…
glass core substrate warpage prediction, glass core substrate, core substrate warpage, substrate warpage prediction, glass core, core substrate, substrate warpage, warpage prediction
Glass Core Substrate Warpage Prediction with Machine Learning Introduction & Motivation Glass Core Substrate Warpage Prediction with Machine Learning addresses a central problem…
Causal Process Modeling for Glass-Core Substrates Causal Process Modeling for Glass-Core Substrates Introduction Causal Process Modeling for Glass-Core Substrates is…
Edge AI Deployment for Glass-Core Substrates Edge AI Deployment for Glass-Core Substrates Introduction Edge AI Deployment for Glass-Core Substrates is an engineering workflow…
Predictive Maintenance for Glass-Core Substrates Predictive Maintenance for Glass-Core Substrates Introduction Predictive Maintenance for Glass-Core Substrates is an engineering…
Uncertainty Quantification for Glass-Core Substrates Uncertainty Quantification for Glass-Core Substrates Introduction Uncertainty Quantification for Glass-Core Substrates is…
Virtual Metrology Modeling for Glass-Core Substrates Virtual Metrology Modeling for Glass-Core Substrates Introduction Virtual Metrology Modeling for Glass-Core Substrates is…
glass frit seal hermeticity prediction machine learning, glass frit, seal hermeticity prediction, glass frit seal hermeticity prediction, glass frit seal, frit seal hermeticity
Glass Frit Seal Hermeticity Prediction with Machine Learning Introduction & Motivation Glass Frit Seal Hermeticity Prediction with Machine Learning addresses a central problem…
glass interposer via yield prediction, glass interposer via, interposer via yield, via yield prediction, glass interposer, interposer via, via yield, yield prediction
Glass Interposer Via Yield Prediction with Machine Learning Introduction & Motivation Glass Interposer Via Yield Prediction with Machine Learning addresses a central problem…
glass-to-metal seal defect prediction, glass-to-metal seal defect, seal defect prediction, glass-to-metal seal, seal defect, defect prediction
Glass-to-Metal Seal Defect Prediction with Machine Learning Introduction & Motivation Glass-to-Metal Seal Defect Prediction with Machine Learning addresses a central problem…
glass transition temperature tg prediction, glass transition temperature, transition temperature tg, temperature tg prediction, glass transition, transition temperature
Glass Transition Temperature Tg Prediction with Machine Learning Introduction & Motivation Glass Transition Temperature Tg Prediction with Machine Learning addresses a central…
glip, grounded language-image pre-training, computer vision
GLIP (Grounded Language-Image Pre-training) is a model that unifies object detection and phrase grounding — reformulating detection as a "phrase grounding" task to leverage…
neural architecture search
GLiT is global-local integrated transformer architecture search for hybrid convolution-attention models. - It balances long-range attention and local convolutional bias in one…
clock switching glitch, clock mux, clock domain crossing clock tree, pll bypass switching, clock gating wakeup
A glitch-free clock multiplexer is what a chip needs whenever it switches between two clock sources that are not already synchronized to each other — a plain combinational…
glob-top encapsulation void prediction, glob-top encapsulation void, encapsulation void prediction, glob-top encapsulation, encapsulation void, void prediction
Glob-Top Encapsulation Void Prediction with Machine Learning Introduction & Motivation Glob-Top Encapsulation Void Prediction with Machine Learning addresses a central problem…
distributed training
Global batch is the total number of samples contributing to one optimizer update across all devices and accumulation passes - it is the optimizer-facing batch size that determines…
graph neural networks
Global pooling is the aggregation of all node embeddings into a single graph-level representation - Operations such as sum, mean, max, or attention pooling compress variable-size…
routing algorithm, routing resource, maze routing, routing stages
Global Routing and Detail Routing are the two-stage process that determines the physical paths of all metal wires connecting logic cells on a chip — where global routing plans…
global routing layer utilization congestion prediction, global routing layer, routing layer utilization, layer utilization congestion, utilization congestion prediction
Global Routing Layer Utilization Congestion Prediction with Machine Learning Introduction & Motivation Global Routing Layer Utilization Congestion Prediction with Machine Learning…
SHAP Feature Dependence Plots with Interaction Coloring Introduction & Motivation SHAP Feature Dependence Plots with Interaction Coloring addresses a central problem…
global shutter pixel crosstalk prediction, global shutter pixel, shutter pixel crosstalk, pixel crosstalk prediction, global shutter, shutter pixel, pixel crosstalk
Global Shutter Pixel Crosstalk Prediction with Machine Learning Introduction & Motivation Global Shutter Pixel Crosstalk Prediction with Machine Learning addresses a central…
Global Surrogate Model Explanations Introduction & Motivation Global Surrogate Model Explanations addresses a central problem in interpretability and explanation of xai…
Global Surrogate Model Explanations (Extended Study) Introduction & Motivation Global Surrogate Model Explanations (Extended Study) addresses a central problem in interpretability…
Global Surrogate Model Explanations (Extended Study) Introduction & Motivation Global Surrogate Model Explanations (Extended Study) addresses a central problem in interpretability…
Glow Invertible Network Introduction & Motivation Glow Invertible Network addresses a central problem in generative generation and invertibility-preservation synthesis: how…
glu, neural architecture
GLU (gated linear unit) variants, including SwiGLU and GEGLU, share the same underlying structure, splitting a layer's input in half and using an activated version of one half…
gmlp, gated mlp, llm architecture
gMLP (Gated MLP) is an MLP-based architecture that introduces a gating mechanism to the spatial mixing operation, using a Spatial Gating Unit (SGU) that modulates token…
gmt, graph neural networks
GMT is graph multiset transformer pooling for hierarchical graph-level representation learning. - It pools node sets into compact graph embeddings using learned attention-based…
gnn, graph neural networks
GNN Expressiveness is the ability of a graph neural network to distinguish structures and represent target graph functions - It determines whether architecture choices can…
higher-order graph neural networks, graph neural networks
Higher-Order GNN is a graph model family that propagates information over tuples or subgraphs beyond first-order neighbors - It improves structural sensitivity by encoding…