NVIDIA Volta architecture
E758262
NVIDIA Volta architecture is a GPU microarchitecture designed for high-performance computing and AI workloads, introducing Tensor Cores to accelerate deep learning operations.
All labels observed (1)
| Label | Occurrences |
|---|---|
| NVIDIA Volta architecture canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T8822686 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: NVIDIA Volta architecture Context triple: [NVIDIA Tesla data center GPUs, architectureBasedOn, NVIDIA Volta architecture]
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A.
NVIDIA Ampere architecture
NVIDIA Ampere architecture is a GPU microarchitecture from NVIDIA that powers RTX 30-series graphics cards, delivering significant improvements in ray tracing, AI performance, and power efficiency over previous generations.
-
B.
NVIDIA Ada Lovelace architecture
NVIDIA Ada Lovelace architecture is a GPU microarchitecture from NVIDIA that powers the RTX 40-series graphics cards, delivering major advances in ray tracing, AI acceleration, and power efficiency over previous generations.
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C.
NVIDIA Tesla data center GPUs
NVIDIA Tesla data center GPUs are high-performance graphics processing units designed for accelerated computing workloads such as AI, machine learning, and high-performance computing in server and data center environments.
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D.
Nvidia Maxwell GPU
The Nvidia Maxwell GPU is a graphics processing architecture from Nvidia known for significantly improved power efficiency and performance, widely used in mid-2010s desktop, mobile, and embedded devices.
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E.
NVIDIA AI Enterprise software suite
NVIDIA AI Enterprise software suite is a comprehensive, enterprise-grade collection of AI tools, frameworks, and optimized software designed to accelerate the development and deployment of AI and data analytics workloads across modern data centers and clouds.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: NVIDIA Volta architecture Target entity description: NVIDIA Volta architecture is a GPU microarchitecture designed for high-performance computing and AI workloads, introducing Tensor Cores to accelerate deep learning operations.
-
A.
NVIDIA Ampere architecture
NVIDIA Ampere architecture is a GPU microarchitecture from NVIDIA that powers RTX 30-series graphics cards, delivering significant improvements in ray tracing, AI performance, and power efficiency over previous generations.
-
B.
NVIDIA Ada Lovelace architecture
NVIDIA Ada Lovelace architecture is a GPU microarchitecture from NVIDIA that powers the RTX 40-series graphics cards, delivering major advances in ray tracing, AI acceleration, and power efficiency over previous generations.
-
C.
NVIDIA Tesla data center GPUs
NVIDIA Tesla data center GPUs are high-performance graphics processing units designed for accelerated computing workloads such as AI, machine learning, and high-performance computing in server and data center environments.
-
D.
Nvidia Maxwell GPU
The Nvidia Maxwell GPU is a graphics processing architecture from Nvidia known for significantly improved power efficiency and performance, widely used in mid-2010s desktop, mobile, and embedded devices.
-
E.
NVIDIA AI Enterprise software suite
NVIDIA AI Enterprise software suite is a comprehensive, enterprise-grade collection of AI tools, frameworks, and optimized software designed to accelerate the development and deployment of AI and data analytics workloads across modern data centers and clouds.
- F. None of above. chosen
Statements (49)
| Predicate | Object |
|---|---|
| instanceOf | GPU microarchitecture ⓘ |
| architectureGeneration | NVIDIA Volta NERFINISHED ⓘ |
| codename | Volta NERFINISHED ⓘ |
| designedFor |
artificial intelligence workloads
ⓘ
deep learning acceleration ⓘ high-performance computing ⓘ |
| developer | NVIDIA NERFINISHED ⓘ |
| firstAnnouncementDate | 2017-05 ⓘ |
| firstGPUModel | NVIDIA Tesla V100 NERFINISHED ⓘ |
| flagshipComputeGPU | NVIDIA Tesla V100 NERFINISHED ⓘ |
| focus | energy-efficient performance for HPC and AI ⓘ |
| foundry | TSMC NERFINISHED ⓘ |
| includesProduct |
NVIDIA Quadro GV100
NERFINISHED
ⓘ
NVIDIA Tesla V100 PCIe NERFINISHED ⓘ NVIDIA Tesla V100 SXM2 NERFINISHED ⓘ NVIDIA Tesla V100S NERFINISHED ⓘ NVIDIA Titan V NERFINISHED ⓘ |
| introducedFeature | Tensor Cores NERFINISHED ⓘ |
| keyInnovation |
Tensor Cores for deep learning
ⓘ
enhanced SM (Streaming Multiprocessor) design ⓘ improved NVLink interconnect ⓘ independent thread scheduling ⓘ larger register file per SM ⓘ |
| marketSegment |
AI inference
ⓘ
AI training ⓘ HPC ⓘ data center ⓘ |
| memoryType | HBM2 NERFINISHED ⓘ |
| notableGPUCore | GV100 GENERATED ⓘ |
| predecessor | NVIDIA Pascal architecture NERFINISHED ⓘ |
| processNode | 12 nm FinFET ⓘ |
| successor |
NVIDIA Ampere architecture
NERFINISHED
ⓘ
NVIDIA Turing architecture NERFINISHED ⓘ |
| supports |
CUDA
NERFINISHED
ⓘ
ECC memory ⓘ FP16 operations ⓘ FP32 operations ⓘ FP64 operations ⓘ HBM2 memory ⓘ NVIDIA CUDA 9 NERFINISHED ⓘ NVIDIA NVLink NERFINISHED ⓘ Tensor operations ⓘ mixed-precision computing ⓘ |
| targetWorkload |
data analytics
ⓘ
high-performance computing clusters ⓘ neural network training ⓘ scientific simulation ⓘ |
| usedIn |
NVIDIA DGX-1 system (Volta version)
NERFINISHED
ⓘ
NVIDIA DGX-2 system NERFINISHED ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: NVIDIA Volta architecture Description of subject: NVIDIA Volta architecture is a GPU microarchitecture designed for high-performance computing and AI workloads, introducing Tensor Cores to accelerate deep learning operations.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.