27,049 technical terms and definitions
arima autoregressive model, arima autoregressive, autoregressive model
ARIMA Autoregressive Model Introduction & Motivation ARIMA Autoregressive Model addresses a central problem in timeseries process control and arima-parameter-selection-aic-bic…
arima exponential comparison, arima exponential, exponential comparison
ARIMA Exponential Comparison Introduction & Motivation ARIMA Exponential Comparison addresses a central problem in timeseries process control and arima-vs-exponential-smoothing…
ARIMA Forecasting Framework Introduction & Motivation ARIMA Forecasting Framework addresses a central problem in timeseries forecasting and differencing-order-selection…
arima, statistics
ARIMA modeling is the time-series modeling framework that captures autoregressive behavior, differencing trends, and moving-average noise patterns - it is widely used to model…
arima, manufacturing operations
ARIMA Process is a time-series modeling approach that combines autoregressive, differencing, and moving-average terms for process forecasting - It is a core method in modern…
optimization
Arithmetic intensity is the ratio of floating-point operations to bytes moved from memory - it indicates whether workload performance is likely limited by compute capacity…
arithmetic logic unit saturation and latency hiding, arithmetic logic unit, logic unit saturation, unit saturation latency, saturation latency hiding, arithmetic logic, logic unit
Arithmetic Logic Unit Saturation and Latency Hiding Introduction & Motivation Arithmetic Logic Unit Saturation and Latency Hiding addresses a central problem in cpu-arch process…
arm manipulator control, arm manipulator, manipulator control
Arm Manipulator Control Introduction & Motivation Arm Manipulator Control addresses a central problem in robotics process control and manipulator-endpoint-control prediction: how…
ARM CPU, ARM architecture, Cortex processor, Neoverse, ARM core
ARM processor. implements an instruction-set architecture developed by Arm and is usually obtained through a processor-core or architecture license rather than purchased as…
arrayed waveguide grating crosstalk prediction, arrayed waveguide grating, waveguide grating crosstalk, grating crosstalk prediction, arrayed waveguide, waveguide grating
Arrayed Waveguide Grating Crosstalk Prediction with Machine Learning Introduction & Motivation Arrayed Waveguide Grating Crosstalk Prediction with Machine Learning addresses…
reliability
Semiconductor reliability physics and accelerated life testing constitute the statistical, thermodynamic, and mechanical disciplines engineered to predict, quantify, and guarantee…
business & standards
Semiconductor reliability physics and accelerated life testing constitute the statistical, thermodynamic, and mechanical disciplines engineered to predict, quantify, and guarantee…
arrhenius model temperature acceleration prediction, arrhenius model temperature, model temperature acceleration, temperature acceleration prediction, arrhenius model
Arrhenius Model Temperature Acceleration Prediction with Machine Learning Introduction & Motivation Arrhenius Model Temperature Acceleration Prediction with Machine Learning…
memory, columnar
Apache Arrow is the cross-language, in-memory columnar data format that enables zero-copy data sharing between different systems and programming languages — eliminating…
arsenic channel doping prediction, arsenic channel doping, channel doping prediction, arsenic channel, channel doping, doping prediction
Arsenic Channel Doping Prediction with Machine Learning Introduction & Motivation Arsenic Channel Doping Prediction with Machine Learning addresses a central problem in arsenic…
arsenic implant amorphization layer integrity prediction, arsenic implant amorphization, implant amorphization layer, amorphization layer integrity, layer integrity prediction
Arsenic Implant Amorphization Layer Integrity Prediction with Machine Learning Introduction & Motivation Arsenic Implant Amorphization Layer Integrity Prediction with Machine…
artifact dependency tracking, artifact dependency, dependency tracking
Artifact Dependency Tracking Introduction & Motivation Artifact Dependency Tracking addresses a central problem in verification process control and dependency-analysis-latency…
machine learning, deep learning, training, inference, accelerator, GPU, NPU, model optimization
Artificial intelligence, in the sense that matters to a chip company, is a family of statistical methods that learn a function from data instead of having it specified by…
artificial neural network control, artificial neural network, neural network control, artificial neural, neural network, network control
Artificial Neural Network Control Introduction & Motivation Artificial Neural Network Control addresses a central problem in robotics process control…
artificial neural networks in photonics, artificial neural networks, neural networks photonics, artificial neural, neural networks, networks photonics
Artificial Neural Networks in Photonics Introduction & Motivation Artificial Neural Networks in Photonics addresses a central problem in photonic-neural process control…
quality
AS9100 is the aerospace, space, and defense industry quality management system standard — extending ISO 9001 with rigorous requirements for configuration management, risk…
asam, optimization
ASAM (Adaptive Sharpness-Aware Minimization) is an improvement over SAM that uses adaptive perturbation sizes for each parameter — normalizing the perturbation by the parameter…
version, manager
Conda: Package & Environment Manager Overview Conda is an open-source package management system and environment management system. Unlike `pip` (which only manages Python), Conda…
ash residue removal completeness prediction machine learning, ash residue, removal completeness prediction, ash residue removal completeness prediction, ash residue removal
Ash Residue Removal Completeness Prediction with Machine Learning Introduction & Motivation Ash Residue Removal Completeness Prediction with Machine Learning addresses a central…
application-specific integrated circuit, asic design flow, custom silicon
ASIC means application-specific integrated circuit: silicon whose transistors and interconnect are manufactured for a defined product or workload. Unlike an FPGA’s programmable…
FPGA, design, trade-offs, comparison
ASIC vs FPGA Design Trade-offs is a comparative analysis framework evaluating semiconductor design approaches based on performance, cost, flexibility, and development time…
asic design area power and performance trade-off surface, asic design area, design area power, area power performance, power performance trade-off, performance trade-off surface, asic design
ASIC Design Area, Power, and Performance Trade-Off Surface Introduction & Motivation ASIC Design Area, Power, and Performance Trade-Off Surface addresses a central problem…
asic design and custom hardware, asic design custom, design custom hardware, asic design, design custom, custom hardware
ASIC Design and Custom Hardware Introduction & Motivation ASIC Design and Custom Hardware addresses a central problem in hardware-design process control and time-to-market-months…
ai accelerator nre cost, tpu trainium inferentia, tape-out to volume ramp, asic vs gpu economics, ai compiler runtime stack
ASIC for AI means building application-specific silicon optimized for a narrow training or inference profile, trading flexibility for performance per watt and long-run unit cost…
asic timing closure margin prediction, asic timing closure, timing closure margin, closure margin prediction, asic timing, timing closure, closure margin, margin prediction
ASIC Timing Closure Margin Prediction with Machine Learning Introduction & Motivation ASIC Timing Closure Margin Prediction with Machine Learning addresses a central problem…
asic versus fpga, difference between asic and fpga, when to use fpga vs asic, custom chip vs programmable chip
An ASIC and an FPGA solve the same problem — running a custom digital circuit — with opposite tradeoffs between speed and flexibility: an ASIC is a chip permanently hardwired…
asil d functional safety test completeness prediction, asil functional safety, functional safety test, safety test completeness, test completeness prediction, asil functional
ASIL D Functional Safety Test Completeness Prediction with Machine Learning Introduction & Motivation ASIL D Functional Safety Test Completeness Prediction with Machine Learning…
euv machine, lithography equipment, scanner
ASML is the sole manufacturer of EUV lithography systems in the world — not the leading supplier, the *only* supplier. Every chip below the 7nm node, from every major foundry on…
euv machine, lithography equipment, scanner
ASML is the sole manufacturer of EUV lithography systems in the world — not the leading supplier, the *only* supplier. Every chip below the 7nm node, from every major foundry on…
why does asml have a monopoly, asml monopoly on euv, why only asml makes euv, asml lithography monopoly, euv scanner monopoly
ASML is the only company on Earth that builds extreme ultraviolet lithography scanners, and that is not an accident of market share the way one company might simply out-compete…
high-na euv, asml exe, anamorphic euv, 0.55 na euv
High-NA EUV is the next EUV scanner generation: it keeps the 13.5 nm wavelength but raises numerical aperture from 0.33 to 0.55, giving chipmakers sharper imaging for 2 nm-class…
asp, business & strategy
ASP is average selling price, the revenue per unit shipped across a defined product or customer mix - It is a core method in advanced semiconductor business execution programs.…
asp, average selling price, industry
Average Selling Price is the mean revenue per unit across all chips sold in a product line or category. ASP is a critical business metric that determines revenue and profitability…
nlp
Aspect-based sentiment analysis (ABSA) goes beyond overall document sentiment to identify sentiment toward specific aspects or features mentioned in text. Instead of saying "this…
nlp
Aspect-based sentiment is sentiment analysis that targets specific aspects of an entity rather than overall polarity - Pipelines identify aspects such as price quality or service…
aspect extraction opinion mining, aspect extraction opinion, extraction opinion mining, aspect extraction, extraction opinion, opinion mining
Aspect Extraction Opinion Mining Introduction & Motivation Aspect Extraction Opinion Mining addresses a central problem in nlp process control…
ARDE, aspect ratio dependent etching, rie lag, microloading, etch loading effect, knudsen diffusion etch, plasma etch lag, etch
Aspect-ratio-dependent etching and microloading are fundamental plasma transport phenomena in reactive ion etching where the instantaneous material removal rate diminishes…
aspect ratio, etch
Aspect ratio in semiconductor plasma etching is the fundamental geometric ratio of feature depth to top opening width ( ), governing species transport limits, ion angular…
harc etch, high-aspect-ratio etch, deep etch, contact etch
High Aspect Ratio Etch (HARC) is the plasma etching of features where the depth-to-width ratio exceeds 30:1 — a critical capability for 3D NAND channel holes (200:1+), DRAM…
deep reactive ion etch, high-aspect-ratio etch, plasma etch, etch anisotropy
High Aspect Ratio Plasma Etching is the dry etch process technology that creates deep, narrow features (aspect ratios >20:1 to >100:1) in silicon, dielectrics, and metals using…
high-aspect-ratio mol, process integration, mol process
Self-aligned silicides and nanoscale contact metallization architectures represent the material and thermodynamic interfaces engineered to establish low-resistance ohmic…
process integration
Aspect ratio trench is an interconnect trench feature whose depth-to-width ratio challenges etch and fill processes - High aspect ratios increase transport limitations…
assembly lead-free reflow profile optimization prediction, assembly lead-free reflow, lead-free reflow profile, reflow profile optimization, profile optimization prediction
Assembly Lead-Free Reflow Profile Optimization Prediction with Machine Learning Introduction & Motivation Assembly Lead-Free Reflow Profile Optimization Prediction with Machine…
assembly solder joint mechanical reliability prediction, assembly solder joint, solder joint mechanical, joint mechanical reliability, assembly solder, solder joint
Assembly Solder Joint Mechanical Reliability Prediction with Machine Learning Introduction & Motivation Assembly Solder Joint Mechanical Reliability Prediction with Machine…
production, die attach void, wire bond failure, wire sweep, molding defect, handling damage, packaging equipment health, sunk cost die loss, assembly process control
Assembly yield is the percentage of die that survive the packaging process intact and functional, measuring how well die attach, wire bonding or bumping, and molding preserve…