29,259 technical terms and definitions
negf nanoelectronic device physics, self energy contact coupling, transmission coefficient caroli formula, sub 3nm gaafet quantum conductance
Non-Equilibrium Green's Functions (NEGF) and Quantum Transport in Nanostructures 1. Introduction to NEGF Formalism Non-Equilibrium Green's Functions (NEGF) provide a rigorous…
environmental & sustainability
Green Solvents is solvents selected for lower toxicity, environmental impact, and lifecycle burden - They reduce worker exposure risk and downstream treatment requirements. What…
grey wolf algorithm, grey wolf, wolf algorithm
Grey Wolf Algorithm Introduction & Motivation Grey Wolf Algorithm addresses a central problem in ml process control and convergence-iterations-to-optimum prediction: how…
hardware
Grid is the full collection of thread blocks launched for one kernel invocation - it defines total problem coverage and how work is distributed across all SMs in the device. What…
grid load balancing prediction, grid load balancing, load balancing prediction, grid load, load balancing, balancing prediction
Grid Load Balancing Prediction Introduction & Motivation Grid Load Balancing Prediction addresses a central problem in energy process control and prediction-accuracy-mape…
hyperparameter tuning, exhaustive
Grid Search is a hyperparameter tuning technique that exhaustively evaluates all combinations of specified parameter values — testing every possibility to find optimal…
model training
Grid search is a hyperparameter optimization method that exhaustively evaluates all possible combinations from a predefined grid of hyperparameter values, guaranteeing that…
grid search exhaustive parameter exploration and systematic tuning, grid search exhaustive, search exhaustive parameter, exhaustive parameter exploration, grid search
Grid Search Exhaustive Parameter Exploration and Systematic Tuning Introduction & Motivation Grid Search Exhaustive Parameter Exploration and Systematic Tuning addresses a central…
Grid Search Hyperparameter Optimization Introduction & Motivation Grid Search Hyperparameter Optimization addresses a central problem in optimization algorithm tuning…
grid tied inverter, grid connected inverter, bidirectional inverter, grid forming inverter
Grid-tied inverter. connects a DC source or storage system to an AC utility network and exchanges controlled real and reactive power while satisfying synchronization, protection…
data augmentation
GridMix is a data augmentation technique that divides images into a grid and randomly assigns each cell to one of two training images — creating a checkerboard-like mixing pattern…
grinding wheel dressing frequency prediction machine learning, grinding wheel, dressing frequency prediction, grinding wheel dressing frequency prediction, wheel dressing
Grinding Wheel Dressing Frequency Prediction with Machine Learning Introduction & Motivation Grinding Wheel Dressing Frequency Prediction with Machine Learning addresses a central…
gripper design finger, gripper design, design finger
Gripper Design Finger Introduction & Motivation Gripper Design Finger addresses a central problem in robotics process control and gripper-jaw-grasp-type prediction: how to Predict…
training phenomena
Grokking is the phenomenon where neural networks suddenly achieve perfect generalization on held-out data long after memorizing the training set and achieving near-zero training…
training phenomena
Grokking is a training phenomenon where a model suddenly generalizes long after memorizing the training data — the model first achieves perfect training accuracy (memorization)…
neural network grokking, double descent generalization, memorization to generalization transition, phase transition learning
Grokking and Delayed Generalization in Neural Networks is the phenomenon where a neural network first memorizes training data achieving perfect training accuracy, then much later…
cerebras, custom chip
Custom AI Accelerator Chips AI Chip Landscape Company Chip Focus NVIDIA H100, B200 General AI Groq LPU Low-latency inference Cerebras WSE-3 Largest chip, training Google TPU v5…
yield enhancement
Gross Die is the total number of potential die sites geometrically available on a wafer before yield loss - It defines theoretical output capacity at a given die size and wafer…
gross die per wafer forecast prediction, gross die per, die per wafer, per wafer forecast, wafer forecast prediction, gross die, die per, per wafer, wafer forecast, forecast prediction
Gross Die Per Wafer Forecast Prediction with Machine Learning Introduction & Motivation Gross Die Per Wafer Forecast Prediction with Machine Learning addresses a central problem…
industry
Gross margin is revenue minus cost of goods sold (COGS), expressed as a percentage of revenue. It measures how efficiently a semiconductor company converts revenue into profit…
business & strategy
Gross Margin is the percentage of revenue remaining after subtracting cost of goods sold, indicating core product profitability - It is a core method in advanced semiconductor…
design
Ground bounce (also called ground noise or simultaneous switching output noise on ground) is the transient voltage fluctuation on the ground (VSS) network caused by large, rapid…
signal & power integrity
Ground bounce is transient ground-potential variation caused by simultaneous switching currents through package and interconnect inductance - Rapid return-current changes create…
ground bounce ground plane design prediction, ground bounce ground, bounce ground plane, ground plane design, plane design prediction, ground bounce, bounce ground, ground plane
Ground Bounce Ground Plane Design Prediction with Machine Learning Introduction & Motivation Ground Bounce Ground Plane Design Prediction with Machine Learning addresses a central…
PCB ground plane, signal return plane, ground return path, ground stitching
A ground plane is a continuous conductive layer, in a PCB typically a dedicated copper layer, that provides a low-impedance return path for signal current and a stable voltage…
design
Grounded-gate NMOS (GGNMOS) is the most widely used ESD protection clamp in CMOS technology, leveraging the parasitic lateral NPN bipolar transistor inherent in every NMOS device…
rag
Grounded generation is the response generation approach that constrains model output to provided evidence rather than unconstrained parametric memory - it is a primary method…
robotics
Grounded Language Learning is the AI research paradigm that acquires language understanding through interaction with physical or simulated environments — learning word…
evaluation
Groundedness is the extent to which generated claims are supported by provided context or verifiable external sources - It is a core method in modern AI fairness and evaluation…
factual, knowledge
Grounding LLM Responses What is Grounding? Grounding ensures LLM outputs are based on reliable sources rather than model parameters alone. It bridges the gap between fluent…
rag
Grounding ensures AI outputs are anchored in retrieved facts rather than generated from potentially unreliable model knowledge. Problem: LLMs may generate plausible but false…
manufacturing operations
Grounding is the creation of low-impedance electrical paths that safely drain static charge to earth reference - It is a core method in modern semiconductor wafer handling…
facility
Grounding and bonding is the electrical interconnection of all conductive objects within an ESD Protected Area to a common earth ground reference — ensuring that no metal fixture…
computer vision
Grounding DINO is a state-of-the-art open-set object detector — combining the transformer-based detection of DINO (DETR variant) with grounded pre-training to detect arbitrary…
rag
Grounding in external knowledge is the practice of anchoring responses in retrieved evidence rather than relying only on model memory - Retrieval pipelines fetch supporting…
neural architecture
Group Convolutions (G-Convolutions) are the mathematical generalization of standard convolution from the translation group to arbitrary symmetry groups — including rotation…
group delay frequency dispersion prediction, group delay frequency, delay frequency dispersion, frequency dispersion prediction, group delay, delay frequency
Group Delay Frequency Dispersion Prediction with Machine Learning Introduction & Motivation Group Delay Frequency Dispersion Prediction with Machine Learning addresses a central…
Group Normalization Variants Introduction & Motivation Group Normalization Variants addresses a central problem in vision processing and small-batch-stability prediction: how…
recommendation systems
Group Recommendation is recommendation for multi-user groups instead of single-user personalization - It aggregates member preferences to rank items acceptable to the group as…
Group Recommendation Systems Introduction & Motivation Group Recommendation Systems addresses a central problem in recsys systems and (target) optimization: how to Build (subject)…
leak, prevent
GroupKFold is a cross-validation strategy that prevents data leakage by ensuring all samples from the same "group" stay together in either the training set or the test set, never…
computer vision
Grouped Convolution is a convolution where input channels are divided into G groups, and each group is convolved independently — reducing parameters and FLOPs by a factor of G…
model optimization
Grouped Convolution is a convolution method that partitions channels into groups processed by separate filter sets - It reduces parameters and compute while preserving…
gqa, kv
Grouped-query attention (GQA) has multiple query heads actually share a smaller number of key-and-value head groups, landing at a specific middle point between multi-head…
gqa, multi query attention, mqa, attention head sharing
Grouped-Query Attention (GQA) is the attention architecture variant that shares Key and Value heads among groups of Query heads — reducing the KV cache memory footprint…
grouped-query attention, gqa, llm architecture
Grouped-Query Attention (GQA) is an attention architecture that provides a tunable middle ground between Multi-Head Attention (MHA) and Multi-Query Attention (MQA) — using G…
multi query attention mqa, kv cache reduction, attention head grouping, llama 2 attention
Grouped Query Attention (GQA) is the attention mechanism that shares key and value projections across groups of query heads, interpolating between multi-head attention (MHA)…
optimization
Grouped-query KV cache is the attention approach where query heads are partitioned into groups that share key-value heads, balancing efficiency between full multi-head attention…
split-apply-combine, Hadley Wickham, GROUP BY, pivot table, window functions
Grouping is the operation of splitting a dataset into subsets that share a common value in one or more columns, so that a calculation can be applied separately to each subset…
neural architecture
GroupNorm is a normalization technique that divides channels into groups and normalizes within each group — independent of batch size, making it the preferred normalization…