Methodology
Glossary
77 terms across 8 domains
Where sources define a term differently, the entry records the convention Scrutica uses. Related terms at the foot of an entry link to the ones this glossary also defines.
Semiconductor Manufacturing
EUV lithography
(EUV)Extreme ultraviolet lithography uses 13.5 nm light to print circuit patterns on wafers. A tin-plasma light source and multilayer mirrors operate in a vacuum.
DUV lithography
(DUV)Deep ultraviolet lithography uses 193 nm argon-fluoride or 248 nm krypton-fluoride light. Multiple patterning adds exposures and processing steps to print finer features.
Process node
A manufacturer’s name for a semiconductor process generation, such as N4 or N7. The number in a modern node name does not specify a physical gate length or permit direct comparison between manufacturers.
Wafer
A thin disc of semiconductor material on which chip dies are fabricated. Wafer starts per month measures how many wafers enter production.
Yield
The fraction of manufactured dies that meet the required specifications.
CoWoS
Chip-on-Wafer-on-Substrate: TSMC’s packaging family for connecting logic dies and high-bandwidth memory. CoWoS-S uses a silicon interposer; CoWoS-R uses redistribution layers, and CoWoS-L combines them with local silicon interconnects.
HBM
High Bandwidth Memory: stacks of DRAM dies connected vertically by through-silicon vias. Several stacks can supply memory to one accelerator package.
Foundry
A semiconductor manufacturer that fabricates chips designed by customers. A customer must use a design compatible with the foundry’s process.
Fabless
A chip company that designs chips and contracts out their fabrication. NVIDIA and AMD use this model.
IDM
Integrated Device Manufacturer: a company that both designs and fabricates chips. Intel and Texas Instruments are examples.
OSAT
Outsourced Semiconductor Assembly and Test: a company that packages and tests fabricated chips. ASE and Amkor provide these services.
FinFET
Fin Field-Effect Transistor: a transistor whose gate surrounds the sides and top of a raised silicon channel, called a fin.
GAA
Gate-All-Around transistor: a transistor whose gate surrounds the channel on all sides. Intel’s RibbonFET uses ribbon-shaped silicon channels.
Photomask
A patterned template, also called a reticle, from which a lithography system projects circuit features onto a wafer.
Advanced packaging
Techniques that connect multiple dies within one package, including side-by-side integration and vertical stacking. They allow logic and memory manufactured separately to work together.
GPU / Accelerator Architecture
FLOP
A floating-point arithmetic operation. FLOP/s measures the rate of these operations; multiplying a sustained rate by elapsed seconds gives a cumulative operation count.
TFLOP/s
One trillion (10¹²) floating-point operations per second. Hardware ratings specify the arithmetic format and whether structured sparsity contributes to the reported rate.
FP16
A 16-bit floating-point format with one sign bit, five exponent bits and ten fraction bits. Mixed-precision training can combine FP16 arithmetic with higher-precision operations.
BF16
A 16-bit floating-point format with one sign bit, eight exponent bits and seven fraction bits. Its exponent range matches FP32, with less precision for individual values.
TDP
Thermal Design Power: a manufacturer’s thermal design rating, in watts, used to size cooling.
NVLink
NVIDIA’s interconnect for high-bandwidth communication between supported processors.
InfiniBand
A network technology used for high-bandwidth, low-latency communication between servers, including servers in AI training clusters.
Tensor core
NVIDIA hardware units that accelerate matrix multiply-and-accumulate operations.
Memory bandwidth
The rate at which data can move between a processor and its memory, usually expressed in GB/s or TB/s.
SXM
NVIDIA’s module form factor for GPUs installed on a server baseboard.
PCIe
PCI Express: an interface for connecting devices within a computer.
AI Training
Training compute
The operations used to train a model, commonly counted in FLOP. A reported total needs a defined scope, including which training stages it counts.
Inference
Using a trained model to produce an output. Compute demand depends on the model, input and output lengths, and how requests are processed together.
Scaling law
An empirical relationship between model performance and inputs such as parameter count, training data and compute. Kaplan et al. (2020) and Hoffmann et al. (2022) study such relationships for language-model loss.
Chinchilla-optimal
A compute-constrained balance of model size and training data studied by Hoffmann et al. (2022). Their results favored scaling parameters and training tokens together, with about 20 tokens per parameter in the Chinchilla training run.
Parameter count
The number of learned weights in a model. The parameters used for an individual input can be a subset of the total in a mixture-of-experts model.
MFU
Model FLOP Utilization: model operations per second divided by the hardware’s theoretical peak rate. The model-operation count excludes activation recomputation; hardware FLOP utilization can include that extra work.
Fine-tuning
Further training of an existing model, often to adapt it to a task or dataset. It may update all model weights or a smaller set of parameters.
METR time horizon
METR’s estimate of the task duration at which an AI agent reaches a specified success rate, commonly 50%. Duration refers to the time human experts need for the tasks.
Data Centers
PUE
Power Usage Effectiveness: total facility energy divided by IT equipment energy over the same period. IT equipment includes servers, storage and networking.
MW
Megawatt: one million watts, a unit of power. Energy consumption also requires a duration; one megawatt sustained for one hour is one megawatt-hour.
Liquid cooling
Cooling that carries heat away in a liquid, through cold plates attached to components or by immersing equipment in a suitable fluid.
GPU cluster
A group of connected GPU servers configured to work together.
Utilization rate
The fraction of available capacity used over a stated period. For GPUs, the measure may refer to occupied device time or to a particular activity counter; the denominator needs to be specified.
Interconnect fabric
The links and switches that connect processors and servers. A cluster may combine local accelerator links with an InfiniBand or Ethernet network between servers.
Neocloud
A cloud provider focused on supplying GPU computing capacity. CoreWeave, Lambda and Nebius offer such services.
Hyperscaler
An operator of large-scale computing infrastructure, often spread across many data centers. The term includes major cloud providers and companies that operate infrastructure for their own services.
Supply Chain
Sole-source dependency
A dependency in which only one supplier can meet the requirement for a particular input or qualified process. Other suppliers may serve the wider market.
Supply chain edge
A directed connection representing a recorded business relationship. A supplier–customer pair can have separate connections for different products or services.
HHI
Herfindahl-Hirschman Index: the sum of squared market shares, expressed as percentages. A single supplier has an HHI of 10,000; splitting supply among more similarly sized firms reduces the index.
Chokepoint
A supply-chain dependency whose disruption is difficult to avoid because suitable alternatives are limited.
Cascade
Disruption that spreads through business dependencies. Scrutica’s simulator follows recorded relationships and weights transmitted impact by supply share, criticality and a scenario-level decay factor.
Licensed supply-chain database
A subscription source of business relationships. Its records can include supplier–customer links and attributes such as relationship value or price correlation.
Price correlation
A Pearson correlation between two companies’ stock prices over a stated window. Scrutica’s licensed relationship records can include a three-month value.
Substitutability
The ability to replace an input or supplier with an alternative that meets the required specifications. It depends on the product and the time available to qualify or expand replacement supply.
Export Controls
EAR
Export Administration Regulations: US rules administered by the Bureau of Industry and Security that govern covered exports, reexports and transfers, along with specified activities by US persons.
Entity List
A list maintained by BIS whose entries specify licence requirements and review policies for transactions involving the named entities.
BIS
Bureau of Industry and Security: the US Department of Commerce agency that administers the EAR, issues licences and maintains the Entity List.
License exception
An authorization under the EAR for a transaction that meets specified conditions, without an individual licence application.
Deemed export
Under the EAR, a release of controlled technology or source code to a foreign person in the United States can constitute an export to that person’s relevant country of citizenship or permanent residency.
Wassenaar Arrangement
A multilateral arrangement for coordinating controls on conventional arms and dual-use goods and technologies. Participating states agree control lists and related guidance.
End-use controls
Export restrictions tied to the intended use of an item or specified activities. They can apply in addition to controls based on the item’s technical classification.
De minimis rule
EAR rules that assess controlled US-origin content in a foreign-made item. The applicable percentage depends on the item and destination, with some categories subject to no minimum.
TOPS
Tera operations per second: 10¹² operations per second. A quoted rate needs the operation type, precision and sparsity convention.
Governance
GPAI
General-purpose AI models, as defined by the EU AI Act, have significant generality and can perform a wide range of distinct tasks, including when incorporated into other systems.
Systemic risk
Under the EU AI Act, risk associated with a general-purpose model’s high-impact capabilities that can spread at scale across the value chain, with significant effects on matters such as safety or fundamental rights.
EU AI Act
Regulation (EU) 2024/1689, which sets rules for AI systems and general-purpose AI models, with obligations that depend on the applicable category.
Compute governance
Policies that use access to computing resources, or information about their production and use, to influence AI development and deployment.
Dual-use
Goods, software or technology that can serve civilian and military purposes.
Proliferation
The spread of a capability to additional actors. In AI, this can involve access to models, computing resources or the expertise needed to use them.
Sovereign AI
National initiatives to develop AI capabilities, including domestic computing infrastructure and access arrangements with commercial providers.
Reality ratio
Scrutica’s ratio of reported disbursed spending to announced government spending. When the government figure is absent, the calculation falls back to the headline commitment, which may include private capital.
Methodology
Confidence interval
An interval produced by a statistical procedure with a specified repeated-sampling coverage rate. A 95% procedure would contain the true parameter in 95% of repeated applications under its assumptions.
Provenance
Information about where a value came from and how it was transformed. It can include a source document, the date it was accessed and the calculation applied.
is_estimated
A per-record flag, set by the pipeline step that last wrote it, under that step’s own rule. True means that step judged the record estimated, on grounds that include a modeled, derived or inferred value, an unconfirmed record and a secondary source. False means no such judgment is recorded; it is not a verification. Read the flag with the record’s authority tier.
Estimation bounds
Ranges obtained by varying assumptions in an estimate. Scrutica’s facility estimator varies inputs within each available hardware, power or cost calculation.
BFS propagation
(BFS)Breadth-first search explores a graph outward in stages from a starting point. Scrutica uses it to follow modeled disruptions through recorded business relationships.
Decay rate
In Scrutica’s cascade model, a scenario-level multiplier applied when transmitting disruption across a relationship. Supply share and criticality contribute additional multipliers.
Capex disaggregation
Allocating capital expenditure among components such as buildings, power infrastructure and computing equipment.
Petaflop-day
(PF-day)One petaFLOP/s (10¹⁵ floating-point operations per second) sustained for 86,400 seconds: 8.64 × 10¹⁹ FLOP.
Price per petaflop-day
Cloud rental price per petaflop-day = hourly instance price × 24 ÷ (GPU count × dense BF16 TFLOP/s per GPU ÷ 1,000).