NVIDIA Tesla data center GPUs
E209943
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.
All labels observed (15)
How this entity was disambiguated
This entity first appeared as the object of triple T1893299 — 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 Tesla data center GPUs Context triple: [NVIDIA Corporation, products, NVIDIA Tesla data center GPUs]
-
A.
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.
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B.
NVIDIA DGX
NVIDIA DGX is a line of high-performance, AI-optimized computing systems designed for training and deploying large-scale machine learning and deep learning models.
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C.
NVIDIA CUDA
NVIDIA CUDA is a parallel computing platform and programming model that enables developers to use NVIDIA GPUs for general-purpose high-performance computing.
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D.
GPU
The GPU (State Political Directorate) was the Soviet Union’s early secret police and intelligence agency that operated in the 1920s, overseeing political repression and internal security before later reorganizations.
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E.
GPU
GPU is the vehicle registration code used on license plates for cars registered in Poland’s Pomeranian Voivodeship.
- 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 Tesla data center GPUs Target entity description: 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.
-
A.
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.
-
B.
NVIDIA DGX
NVIDIA DGX is a line of high-performance, AI-optimized computing systems designed for training and deploying large-scale machine learning and deep learning models.
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C.
NVIDIA CUDA
NVIDIA CUDA is a parallel computing platform and programming model that enables developers to use NVIDIA GPUs for general-purpose high-performance computing.
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D.
GPU
The GPU (State Political Directorate) was the Soviet Union’s early secret police and intelligence agency that operated in the 1920s, overseeing political repression and internal security before later reorganizations.
-
E.
GPU
GPU is the vehicle registration code used on license plates for cars registered in Poland’s Pomeranian Voivodeship.
- F. None of above. chosen
Statements (49)
| Predicate | Object |
|---|---|
| instanceOf |
GPU product line
ⓘ
data center accelerator ⓘ |
| architectureBasedOn |
NVIDIA Kepler architecture
ⓘ
Nvidia Maxwell GPU ⓘ
surface form:
NVIDIA Maxwell architecture
NVIDIA Pascal architecture ⓘ NVIDIA Volta architecture ⓘ |
| deploymentFormFactor |
PCIe add-in card
ⓘ
SXM module ⓘ |
| designedFor |
artificial intelligence workloads
ⓘ
data centers ⓘ deep learning inference ⓘ deep learning training ⓘ high-performance computing ⓘ machine learning workloads ⓘ scientific computing ⓘ servers ⓘ technical computing ⓘ |
| enables |
large-scale data analytics
ⓘ
large-scale neural network training ⓘ parallel computing ⓘ simulation and modeling workloads ⓘ |
| includesModel |
NVIDIA Tesla data center GPUs
self-linksurface differs
ⓘ
surface form:
NVIDIA Tesla K20
NVIDIA Tesla data center GPUs self-linksurface differs ⓘ
surface form:
NVIDIA Tesla K40
NVIDIA Tesla data center GPUs self-linksurface differs ⓘ
surface form:
NVIDIA Tesla K80
NVIDIA Tesla data center GPUs self-linksurface differs ⓘ
surface form:
NVIDIA Tesla P100
NVIDIA Pascal architecture ⓘ
surface form:
NVIDIA Tesla P4
NVIDIA Pascal architecture ⓘ
surface form:
NVIDIA Tesla P40
NVIDIA Pascal architecture ⓘ
surface form:
NVIDIA Tesla V100
|
| manufacturer |
NVIDIA Corporation
ⓘ
surface form:
NVIDIA
|
| marketedAs | accelerators for HPC and AI ⓘ |
| powerOptimizedFor | rack-mounted servers ⓘ |
| successorBrand | NVIDIA data center GPUs under the A100 and H100 branding ⓘ |
| supports |
NVIDIA CUDA
ⓘ
surface form:
CUDA
NVIDIA CUDA ⓘ
surface form:
NVIDIA GPU computing ecosystem
NVLink interconnect ⓘ PCI Express ⓘ
surface form:
PCI Express interface
double-precision floating point ⓘ mixed-precision computing ⓘ single-precision floating point ⓘ |
| supportsEcosystem |
GPU-accelerated libraries for HPC
ⓘ
NVIDIA CUDA ⓘ
surface form:
NVIDIA CUDA Toolkit
NCCL ⓘ
surface form:
NVIDIA NCCL
cuDNN ⓘ
surface form:
NVIDIA cuDNN
|
| targetCustomer |
cloud service providers
ⓘ
enterprise data centers ⓘ supercomputing centers ⓘ |
| usedIn |
GPU-accelerated clusters
ⓘ
GPU-accelerated servers ⓘ supercomputers ⓘ |
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 Tesla data center GPUs Description of subject: 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.
Referenced by (17)
Full triples — surface form annotated when it differs from this entity's canonical label.
subject surface form:
NVIDIA Corporation
this entity surface form:
NVIDIA A100 data center GPUs
subject surface form:
NVIDIA Corporation
this entity surface form:
NVIDIA H100 data center GPUs
subject surface form:
DLSS
this entity surface form:
NVIDIA GPU with Tensor Cores
this entity surface form:
NVIDIA Tesla GPU
this entity surface form:
NVIDIA Tesla V100 GPU
NVIDIA Tesla data center GPUs
→
includesModel
→
NVIDIA Tesla data center GPUs
self-linksurface differs
ⓘ
this entity surface form:
NVIDIA Tesla K20
NVIDIA Tesla data center GPUs
→
includesModel
→
NVIDIA Tesla data center GPUs
self-linksurface differs
ⓘ
this entity surface form:
NVIDIA Tesla K40
NVIDIA Tesla data center GPUs
→
includesModel
→
NVIDIA Tesla data center GPUs
self-linksurface differs
ⓘ
this entity surface form:
NVIDIA Tesla K80
NVIDIA Tesla data center GPUs
→
includesModel
→
NVIDIA Tesla data center GPUs
self-linksurface differs
ⓘ
this entity surface form:
NVIDIA Tesla P100
this entity surface form:
NVIDIA data center GPU
subject surface form:
CUDA
this entity surface form:
NVIDIA Tesla GPUs
subject surface form:
CUDA
this entity surface form:
NVIDIA data center GPUs
this entity surface form:
NVIDIA Tesla
this entity surface form:
NVIDIA A-series for data center
this entity surface form:
NVIDIA data center GPUs
this entity surface form:
NVIDIA Tesla GPU